Modelling of Dynamic Voltage Restorer against Balanced ... - IOSR

IOSR Journal of Electrical and Electronics Engineering (IOSR-JEEE) 

e-ISSN: 2278-1676 Volume 4, Issue 6 (Mar. - Apr. 2013), PP 01-09 

www.iosrjournals.org 

Modelling of Dynamic Voltage Restorer against Balanced and 

Unbalanced Voltage Sags in Distribution systems 

H. Lakshmi 

Electrical and Electronics Engineering, Kakatiya University, Warangal, India. 

Abstract: The Dynamic Voltage Restorer (DVR) is used to regulate the voltage at the load terminals from 

various power quality problems like sag, swell, harmonics, unbalance etc. in supply voltage. This paper 

presents modelling aspects of several types of Dynamic Voltage Restorer (DVR) working against various 

voltage sags by simulation. Dynamic voltage restorers (DVRs) are used to protect sensitive loads from the 

effects of voltage sags on the distribution feeder. Significant simulation results show that these several types of 

the modelled device can work very well against balanced and/or unbalanced voltages caused by faults in a 

distribution system. Detailed analyses illustrate that with suitable parameter setting these devices can deal with 

different levels of voltage sag severity. In addition, appropriate ways to obtain a good quality output voltage by 

a DVR during voltage sag is also presented. It then provides analyses of working performance of the device, 

including capability and quality of compensation. 

Index Terms- Dynamic Voltage Restorer (DVR), Balanced and unbalanced faults, Compensation capability, 

Power quality sag severity, voltage sag. 

I. Introduction 

Power quality (PQ) is a term which has captured increasing attention in power engineering within the 

recent years. For most of the electric power engineers, the term refers to a certain sufficiently high grade of 

electric service. Usually the term quality refers to maintaining a sinusoidal waveform of bus voltages at rated 

voltage and frequency [1]. 

One of the fundamental challenges facing utility and working staff is the need to become familiar with 

and stay informed about issues dealing with power quality. Power suppliers and also the customers are going to 

find a solid background in power quality not only useful, but necessary too, for continued productivity and 

competitiveness. These facts are supported by the utility industry which undergoes restructuring and as 

customers find their service needs changing with increased use of equipment and processes more susceptible to 

power system disturbances. 

Power quality is a growing concern for a wide range of customers. Industrial customers can experience 

interruptions of important processes during momentary voltage sags associated with faults within the utility 

system [2]. Commercial customers are installing high efficiency lighting and electronic office equipment, 

resulting in higher harmonic levels in the buildings. These harmonic sources cause excessive neutral currents 

and transformer overheating. Even residential customers are concerned about surge protection for sensitive 

electronics in the home and the impact of momentary interruptions on their electronic equipment. 

Power quality within the electric distribution system is a growing concern. Customers require higher 

quality service due to more sensitive electronic and computer-controlled loads. Capacitor switching events and 

voltage sags associated with remote faults that never caused problems in the past, now cause equipment tripping 

and even failures within customer facilities. Also, customer loads are generating increasing amounts of 

harmonic currents that can be magnified on the distribution system due to resonance conditions [3]. 

As technology becomes more advanced, equipment has become more sensitive to fluctuations in 

voltage along the distribution line. New equipment that increases productivity for a plant may also cause power 

quality problems for other equipment down the line [4]. Power quality is now viewed from a systems 

perspective rather than as an isolated instrument problem. Understanding the entire scope of the problem helps 

in identifying the solution and preventing future occurrences. 

The existence of disturbances requires analysis, monitoring and taking measures to ensure the quality 

of electricity. Therefore, disturbances are those that significantly reduce the quality of electricity affecting the 

generation, trans-mission and distribution process, but also the electricity consumption [2]. 

Voltage is the main qualitative element that conditions the proper functioning of the receptor. That is why the 

voltage quality practically defines the power quality. The paper is focusing on the power quality monitoring in 

case of an important substation within the Romanian Power System. 

One of the major concerns in electricity industry today is power quality problems to sensitive loads. 

This is due to the advent of a large numbers of sophisticated electrical and electronic equipment, such as 

computers, programmable logic controllers, variable speed drives, and so forth. The use of these equipment’s 


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Modelling of Dynamic Voltage Restorer against Balanced and Unbalanced Voltage Sags in 

very often requires power supplies with very high quality. Voltage sag, which is a momentary decrease in rms 

voltage magnitude in the range of 0.1 to 0.9 per unit (p.u.) [5], is considered as the most serious problem of 

power quality. It is often caused by faults in power systems or by starting of large induction motors. It can 

interrupt or lead to malfunction of any electric equipment which is sensitive to voltage variations. It occurs more 

frequently than any other power quality phenomenon does. Therefore, the loss resulted due to voltage sag 

problem for a customer at the load-end is huge. 

Dynamic voltage restorer (DVR) and static compensator (STATCOM) are recently being used as the 

active solution for voltage sag mitigation 

These system-equipment interface devices are commonly known as custom power devices [6], in which DVR is 

a powerful one for short-duration voltage compensation. Unlike the STATCOM which connects to the load in 

parallel, the DVR is connected in series with the load hence it possesses some certain advantages. 

For example, during power disturbances DVR installed in front of a critical load will appropriately 

provide correction to that load only. It is noteworthy that during normal operation due to the series connection a 

DVR may have to provide a small amount of voltage drop mainly at the coupling transformer. Also DVR cannot 

provide compensation during full power interruptions. 

. 

II. Voltage Sags 

Voltage sags are one of many power quality related problems the industrial process sector has to face 

[7], [8], though sags are one of the most severe. 

Voltage sags are defined as short duration reductions in the rms supply voltage that can last from a few 

milliseconds to a few cycles, with typical dip depths ranging from 0.9 to 0.5 pu of a 1-pu nominal. It has been 

shown that year on year voltage sags cause extensive disruption to the industrial process sector in terms of 

production loss [7], [9], which make them a particularly important area. 

There are various solutions to this problem, examples being: Designing inverter drives for process 

equipment to be more tolerant of voltage fluctuations or the installation of voltage correction devices. It has 

already been shown [7] that for customers of large loads, from the high kilowatt to the low 

megawatt range, a good solution is the installation of a dynamic voltage restorer (DVR); see Fig. 1. 

A DVR is primarily for use at the distribution level, where the basic principle is to inject a voltage in 

series with the supply when an upstream fault is detected. Loads connected downstream of the DVR are thus 

protected from any voltage sags caused by faults elsewhere on the network. 

The location of the DVR, in terms of the connection arrange-ment of upstream transformers (typically ) and 

the type of protection it is to offer to potentially sensitive loads, is a major factor when determining the type of 

inverter control required. The main DVR control used in conjunction with the sag detection techniques presented in 

this paper utilizes a type a vector control that only considers the positive and negative sequence information in the 

supply. The DVR is located downstream of a delta-star distribution transformer (Fig. 1), thus eliminating the need to 

control the zero sequence. 

III. Dvr Against Balanced Volatge Sags 

A. Modelling in PSCAD 

This section will briefly highlight one way of modelling a DVR in PSCAD against balanced voltage 

sags based on published literature and show the result of mitigation obtained. 

There are typically four main components to model a DVR 

[3]: 

• Coupling transformer 


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• DC voltage source 

• Multi-pulse bridge inverter 

• Control system 

A typical DVR built in PSCAD and installed into a simple power system to protect a sensitive load in a 

large radial distribution system [10] is presented in Fig. 2. Its control system block diagram is shown in Fig. 3. 

The coupling transformer with either a delta or wye connection on the DVR side is installed on the line in 

front of the protected load. Filters can be installed at the coupling transformer to block high frequency 

harmonics caused by DC- to-AC conversion to reduce distortion in the output [11]. The DC voltage source is an 

external source supplying DC voltage to the inverter to convert to AC voltage. The optimisation of the DC 

source can be determined during simulation with various scenarios of control schemes, DVR configurations, 

performance requirements, and voltage sags experienced at the point DVR is installed. 

The inverter is a six-pulse gate turn off (GTO) thyristor controlled bridge. Currents will follow in different 

directions at outputs depending on the control scheme, eventually supplying AC output power to the critical load 

during power disturbances. The control of this bridge is indeed the control of thyristor firing angles. Time to 

open and close gates will be determined by the control system. There are several methods for controlling the 

inverter. To model a DVR protecting a sensitive load against only balanced voltage sags, a simple method of 

using the measurement of three-phase rms output voltage for controlling signals can be applied. Amplitude 

modulation (AM) is then used. In addition, to provide appropriate firing angles to thyristor gates the switching 

control using pulse width modulation (PWM) technique and interpolationfiring [6] is employed. 

Fig. 3 DVR Control system block diagram 

The following two figures illustrate two different levels of voltage sags that the DVR works with. Each figure 

shows the rms voltages before and after DVR is connected during voltage sag. As can be clearly seen, 

irrespective of the voltage sag levels the output voltages recover back closely to reference value, which means 

that the DVR can cope well with voltage sag in both cases. 


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When the actual load rms voltage is set higher than the reference value, DVR also works to recover it back. In 

other words DVR should cope with voltage swell as well. 

Various simulations showed an excellent performance of this DVR to work against balanced voltage sags and 

swells. The outstanding problem is that this type of DVR can only deal with balanced voltage sags. 

IV. Dvr Against Balanced And Unbalanced Voltage Sags 

A. General 

Unbalanced voltage sags are very common in distribution systems. Voltages sags are normally caused 

by remote faults, either within the distribution systems or downward from transmission lines. While the three 

phase balanced fault is often seen as the worst case, it seldom occurs. The most frequent types of faults include 

Single phase to ground fault (SLGF) and Line to line fault (LLF), which can be grounded or non-grounded. In 

distribution systems 95% of faults are unbalanced type . They result in unbalanced sags. 

In the previous section the DVR detects 3-phase rms voltage of the critical load and then employs 

PWM technique to control the firing of GTO’s to pump up DC voltage to all three phases of load 

B. Mitigation Result 

An almost worst-case fault (local, three-phase-to-ground, and with a small impedance) by lightning 

strikes was made as shown in Fig.2. The line impedance has been taken out for simulation comparison purposes, 

which does not have any effect to the observed result. The load is a fixed load and not a motor type. 

To satisfy these three criteria rms voltages can still be measured for differential control signals but they 

have to be obtained from single-phase rms measurement not from three-phase. The control signals will be 

separately made for three phases A, B, and C. Besides, modification of DVR inverter bridge and transformer 

connection should be made and then return without affecting the other two phases. It is noted that to maintain an 

equal injecting voltage to each phase, the same value of DC voltage at each half of the source would be 

required. In Fig. 7 instead of having only one three-phase rms voltage three separate line-to-neural (L-N) values 

are now used for firing control input. Three groups of GTO’s are now working independently from each other’s. 

They start firing in case their corresponding phase rms voltage is different from one. When all the phase 

voltages of the load reach to desired value the control system stays at stable condition. Other properties of the 

DVR shown in section I are kept unchanged. Consequently, the three criteria for DVR working in both 

unbalanced and balanced voltage sags are obtained. Result of mitigation against various voltage sags are shown 

in Figs. 8,9 and 10 accordingly. Most importantly, the changes should not affect the performance of the DVR 

against balanced sags described previously because the objective of building DVR is that it should be able to 

deal with all kinds of voltage sags. 

Two methods of coupling transformer configuration were investigated: a wye-connected with 

grounding point and a delta-connected between phases. To adapt to each of these methods the control systems 

were appropriately amended. In fact, two different single-phase rms voltage detection schemes were established 

for each method. One is a detection of voltages between line to neutral for the first and the other is that between 

line to line for the second respectively. The following part will describe configuration of the wye-connected 


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method and its results of voltage sag compensation. Three different types of faults with the same fault 

impedance for comparison purposes will be created in the order: SLGF, LLF (grounded) and three-phase-toground 

fault. 

B. The Wye-connected DVR 

The connection diagram of DVR in PSCAD is shown in Fig.6. Its block diagram of the modulating 

signals in control system is shown in Fig.7. 

In Fig. 6 the transformer is wye-connected with a common connection to the midpoint of the DC source. This 

allowsthatcurrentwillpumpintoeachphasethrougheachpairofGTOvoltage three separate line-to-neural (L-N) 

values are now used for firing control input. Three groups of GTO’s are now working independently from each 

other’s. They start firing in case their corresponding phase rms voltage is different from one. When all the phase 

voltages of the load reach to desired value the control system stays at stable condition. Other properties of the 

DVR shown in section I are kept unchanged. Consequently, the three criteria for DVR working in both 

unbalanced and balanced voltage sags are obtained. Result of mitigation against various voltage sags are shown 

in Figs. 8,9 and 10. 


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In Fig. 8, a fault causes rms voltage (phase A) down to about 80%. As can be seen, the rms voltage of the 

protected 

load stays the same at around unity. The other healthy phase voltages which are not shown here still remain 

constant. Fig. 8 shows that the line-to-line fault results in a more severe voltage sag (down to about 65%, 

phase A), compared to that of single phase. Regardless of the sag magnitude critical load voltage notices a 

good compensation. Meanwhile with the worst three-phase voltage sag down to half of the nominal value 

critical load voltage the mitigation equipment still provides a good compensation. This newly simulated 

DVR shows a similar performance for voltage sag compensation with that of the DVR which uses the threephase 

rms measurement method. The response time of this DVR with three phase voltage measurement is a 

bit slower than the previous one. Still this detection and compensation time to increase rms voltage up 

to desired value is within couple of cycles, proving that DVR can work fast enough that would not result 

in equipment trouble if any severe sag occurs. 

As can be seen single-phase monitoring method gives a less stable rms voltage curve compared to the 

three-phase case making it difficult to keep an appropriate signal for control. That involves the rms 

smoothing time constant, which is a constant interval time applied for detection of a considerable differential 

signal to control the compensation process. This value on the one hand must be small enough for the system to 

be able to detect voltage sags. On the other hand the penalty is a huge fluctuation in rms value record that can 

lead to wrong differential signal for firing control. 

By applying extensive simulations when varying this detection time in PSCAD it can be concluded that 

the method can be satisfactorily employed for DVR using in systems with three phase balanced sags requiring 

measuring the three-phase rms voltage. Besides, the method can also be applied for systems with 

unbalanced sags using single-phase rms voltage measurement. In the second case appropriate modifications 

may need to be done to keep the latter to cope with worst case scenarios of voltage sag. 

IV. Analysis Of Dvr Compensation Capability & Quality Performance 

In a DVR, there are two main considerations in its working performance: the compensation capability 

and the output voltage quality. In a STATCOM, there is some influence of the capacitor size on its performance, 

including distortion . It is revealed by simulation that the value of the DC source voltage has also some side-effect 

as distortion to the output waveform. In addition, the severity of sag decides whether or not the DVR with that set 

value of DC voltage is capable of compensating. In other words, there are two main factors relating to the 

capability and performance of DVR working against voltage sags in a certain power system: the sag severity level 

and the total harmonic distortion (THD) introduced to protected load. Both of these in turn are mainly decided 

by the DC source. The study of relation among these three factors enables to select appropriate parameters for 

DVR to cope with worst-case scenarios of voltage sag. Thus, in this section, an analytical method of examining the 

changes of harmonic distortion and compensation capability according to the changes of DC source voltage is 


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presented. Based on that, considerations on DVR parameter setting and voltage sag compensation strategies can be 

addressed. 

A. Compensation Capability 

By definition [1], a value of rms voltage recovery greater than 90% nominal value is acceptable. The 

issue of how much improvement in rms voltage after compensation is also dependent on the DC voltage 

value. For example, the sag in the above case is corresponding to a new curve of load voltage (E802rms) as 

shown in Fig. 11 

Fig. 11 Improvement in voltage sag compensation 

Apparently, the load voltage value goes up to about 95%, which satisfies the above criterion. This curve would 

change if the DC source value is changed too. 

B. Simulation Results 

In this work, the DVR against balanced voltage sags described in section II is applied. For the 

two types described in section III, the same procedures can be done. Various threephase 

faults with different sag severity are created. First, a constant value of DC source voltage is set and the 

changes in total harmonic distortion and load rms voltage due to voltage sag severity changes is recorded. 

Then, it is repeated for a number of other DC voltage values. The results simulated are summarized in tables I 

and II. 

The two tables correspond to data recorded in two different severe sags. In each table, the first column 

shows variation of DC source. The second and the third columns record the values of voltage after 

compensation and THD according to this DC source variation. It is noted that for comparison purposes, 

the definition of voltage sag by how many percent is now applied. Moreover, THD in percentage is a constant for 

each case. This is because the average value of THD is applied. In fact, in Fig. 10, THD is actually not 

a constant value before, during and after fault. However, the increase in THD at the points where the fault 

occurs and cleared is quite short. Meanwhile, harmonic is more significant when it appears in a fairly 

longer time, as it is the factor which mainly causes non useful heat dissipation in load equipment and so forth. 

The last two columns in each table present the derived thresholds that voltage sag and THD must meet. Similar 

tables of results can be obtained for other voltage sags having different severity. The results in tables I and 

II are converted into two graphs shown in Fig.12 and Fig.13. 

Table I A severe voltage sag - voltage drops by 50% 

DC Load THD Sag 

voltage voltage threshold threshold 

THD 

(kV): (%) (%) (%) (%) 

0 50 0 10 5 

5 35 4 10 5 

10 20 2.5 10 5 

15 10 2 10 5 

20 6 2 10 5 

25 4 3 10 5 

30 2 4 10 5 

35 0 5 10 5 


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Table II. Very severe voltage sag - voltage drops by 75% 

DC Load THD Sag 

voltage voltage threshold threshold 

THD 

(kV): (%) (%) (%) (%) 

0 75 0 10 5 

5 60 8 10 5 

10 45 10 10 5 

15 30 9 10 5 

20 15 3.5 10 5 

25 9 3 10 5 

30 6 4 10 5 

35 5 5 10 5 

D. Result Analysis 

The results shown in Tables I and II are converted into two corresponding graphs shown in Fig. 12 and 

Fig. 13. 

Fig. 12 The severe voltage sag - voltage drops by 50% 

Fig. 13 The very severe voltage sag - voltage drops by 75% 

As can be seen, the graphs give a very clear explanation for which range of DC value source that would 

satisfy the DVR operation requirement in each case. Depending on the worst-case level of the sag in the system 

that DVR is required to be capable to compensate, the DC voltage value can be appropriately selected. 


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For example, if it is required that DVR should be robust enough to cope with balanced sag with value down to 

50% at the point of installation; it is corresponding to the case in the first graph. In this one, the sag threshold 

(10%) cuts the load voltage sag curve at a point corresponding to a DC voltage value of 15kV. It is noticed 

that the curve is relatively linear. These mean that with any value DC voltage value greater 15kV, the DVR is 

able to cope with such severe voltage sag (50%). Similarly for the harmonic curve, a less than 35kV DC 

voltage would result in a compensation in which harmonic distortion is within limit (5%). Thus, to cope with 

the above sag compensation and harmonic distortion requirements, a DC source voltage raging from 15kV to 

35kV should be selected for this DVR. 

It is important to note that the shape of THD curves in the above figures will change if a higher 

number N is selected. This explains why increasing DC source value does not result in a dramatic increase 

of THD, as seen in the graphs. However, higher frequency harmonics can be easily removed by filters as 

mentioned, they are not of important. In the case that the full impact of the harmonic distortion introduced to 

the load needs to be considered, the range of DC source value found would be changed accordingly. Still the 

selection principle remains unchanged. 

It can also be seen that while the sag curves are nearly linear, those of harmonics are not. This 

implies that increasing DC source voltage may improve the capability that DVR can cope with more severe sags; 

however, depending on the firing control scheme and other factors, harmonics injected into power system 

may differently vary. 

With a requirement of different voltage sag level, another range of the source value can be obtained. 

Generally speaking, the best case that a DVR may need is it can cope with a local and bolted balanced fault. By 

proceeding in the same way, a suitable value of DVR might be selected. In that case, DVR is said to be able to 

work with all levels of balanced voltage sag severity. 

When DC voltage is large enough but harmonic distortion requirement does not meet, there are other 

ways to change DVR parameters that can utilise a better harmonic performance. These include 

changing in PWM technique and installing filter at coupling transformer as mentioned, and so forth. 

Consequently, the criteria that decide the DVR capability and output quality stated earlier can be obtained. 

V. Conclusion 

Several aspects of voltage sag mitigation study have been examined. First, a DVR using six-pulse 

inverter and three-phase rms voltage measurement and sine wave PWM control was described. It presents 

excellent performance to protect critical loads against balanced voltage sags. Then, a DVR using singlephase 

rms voltage measurement that works very well against not only balanced voltage sags but also 

unbalanced ones resulting from both single-line and line-line faults was presented. Finally, the study of DVR 

capability and quality performance was examined thoroughly. This discusses appropriate ways to configure DVR 

so that it can deal with all types of voltage sag - balanced and unbalanced, and with all levels of sag severity - 

shadow, severe and worst. This addresses the harmonic distortion problem that DVR produces in the power 

system. The whole study was mainly involved with changes in the value of DC source voltage in DVR. 

A full simulation of DVR mitigation in a large radial system (IEEE 34-bus distribution feeder [4]) was 

performed in PSCAD. This has not been presented here due to space constraints but will be presented in a 

future paper. 

References 

[1] T.L. Tan, S. Chen, and S.S. Choi, "An overview of power quality state estimation", the 7 th International IEEE Power Engineering 

Conference, (IPEC05), 2005, pp: 1-276. 

[2] G Putms, J. Wijayakulasooriya, and P. Minns, "Power Quality: Overview and monitoring", IEEE International Conference on / 

Industrial and Information Systems (ICIIS07), 2007, pp: 551-558. 

[3] T Vmnal, K. Janson, and H. Kalda, "Analysis of power consumption and losses in relation to supply voltage quality", IEEE 13 th 

European Conference on Power Electronics and Applications EPE '09,2009, pp: 1-9. 

[4] R. Lima, D. Quiroga, C. Reineri, and F. Magnago, "Hardware and software architecture for power quality analysis." Computers & 

Electrical Engineering, Vol. 34 (6), pp. 520-530,2008..= 

[5] IEEE recommended practice for evaluating electric power system compatibility with electronic process equipment, IEEE Standard 

1346-1998. 1998. 

[6] N.H. Woodley, L. Morgan, and A. Sundaram, “Experience with an inverter-based dynamic voltage restorer”, IEEE Trans. Power 

Delivery, vol. 14, issue 3, pp. 1181 -1186, Jul. 1999. 

[7] M. H. J. Bollen, Understanding Power Quality Problems: Voltage Sags and Interruptions. New York: IEEE Press, 1999. 

[8] M. F. Mc.Granaghan, D. R. Mueller, and M. J. Samotyj, "Voltage sags Q in industrial systems," IEEE Trans. Ind. Applicat., vol. 29, pp. 397- 

403, Man/Apr. 1993. 

[9] J. C. Smith, J. Lamoree, P. Vinett, T. Duffy, and M. Klein, "The impact of i voltage sags on industrial plant loads," in Proc. Int. Conf. Power 

Quality: End-Use Applications and Perspectives (PQA'9I), 1991, pp. 171-178. [4] 

[10] W. H. Kersting, “Radial distribution test feeders”, PES summer meeting, 2000. Available: http://ewh.ieee.org/soc/pes/sacom/ 

testfeeders.html . 

[11] M.A. Hannan, and A. Mohamed, “Modeling and analysis of a 24-pulse dynamic voltage restorer in a distribution system” Research 

and Development, 2002. SCOReD 2002, pp. 192-195, student conference on 16-17 July 2002. 


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Bang-Bang Controller Based STATCOM Connected Wind 

Generating System for Mitigation of Source Current Harmonics 

Hemalatha.G. 1 , Jeyapradha . R .B 2 

#1 PG Scholar, Valliammai Engneering College, India 603203. 

#2 Assistant Professor, Department of EEE, Valliammai Engineering College, India 603203 

Abstract : This paper work is aimed at developing a STATCOM-based control scheme for mitigating source 

current harmonics in a grid-connected wind generating system. A bang-bang controller which is based on 

hysteresis current control scheme is developed for STATCOM and the performance of the control scheme is 

investigated through a test system modeled in MATLAB/SIMULINK platform. Simulation results are presented 

to demonstrate the impact of integration of wind generating system with the grid and the effectiveness of the 

STATCOM control scheme in minimizing the impact.FFT analysis carried out for the source current shows that 

the THD is considerably reduced and is clearly within limits imposed by standards with STATCOM connected 

at point of common coupling(PCC). 

Keywords - Battery Energy Storage System (BESS), Power Quality (PQ), Point Of Common Coupling (PCC) , 

Wind generating System (WGS), wind turbine generating system (WTGS). 

I. INTRODUCTION 

The need for providing reliable and secure power supply arises with an ever increasing demand for 

electricity. In recent years, the use of non-conventional sources for electricity generation has been gaining 

popularity and one such source is wind energy. The success of wind energy generating system lies in the 

capability of wind technology to be integrated into existing power system. However, the fluctuating nature of 

wind and the comparatively new types of its generators affect the power quality when the wind power is injected 

into the grid. In order to address the power quality issues that arise due to the integration of wind turbine with 

the grid, the grid operators have imposed stringent regulations requiring the wind turbines and wind farms to full 

fill power plant properties. This necessitates the use of highly sophisticates and flexible technology [3]. The 

performance of the wind turbine and thereby power quality are assessed through the guidelines specified by 

IEC-61400 standard. 

In this paper work, a grid connected wind generating system is modeled in MATLAB/SIMLINK 

environment and its performance is studied. The introduction of harmonics in the source current waveform due 

to installation wind turbine with the grid is depicted. A FACTS devices (STATCOM) is connected at the point 

of common coupling with a Battery Energy Storage System (BESS) to make the source current free of 

harmonics[8]. A simple control scheme based on hysteresis current control is developed for the STATCOM 

with the following objectives: 

Unity power factor at the source side. 

Minimize the percentage THD in source current waveform. 

The paper is organized as follows: Section II introduces the power quality standards, issues and its 

consequences. Section III describes the test system. Section IV describes the control scheme. Section V, VI, and 

VII discuss the test system waveform/results and conclusion. 

II. POWER QUALITY ISSUES AND ITS CONSEQUENCES 

2.1. Harmonics 

The harmonic results due to the switching operation of power electronic converters. The harmonic 

voltage and current should be limited to the acceptable level at the point of wind turbine connection to the 

network [10]. 

2.2. Voltage Sag (Or Dip) 

A decrease of normal voltage level between 10 to 90% of the nominal rms voltage level at power 

frequency for duration of 0.5 cycle to one minute. It occurs due to connection of heavy loads and start-up of large 

motors. 


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Bang-Bang Controller Based STATCOM Connected Wind Generating System for Mitigation of 

2.3. Voltage spikes 

Very fast variation of the voltage values for durations from a several microseconds to few milliseconds. 

It occurs due to disconnection of heavy loads. 

2.4. Voltage Swell 

Momentary increase of voltage, at the power frequency, outside the normal tolerances , with duration 

of more than one cycle and typically less than a few seconds. It is caused due to badly regulated transformers 

(mainly during off-peak hours). 

2.5. Voltage fluctuation 

A series of voltage changes or a continuous variation of the R.M.S voltage . It is caused due to frequent 

start/stop of electric motors (for instance elevators), Oscillation in loads. 

2.6. Very Short Interruption 

Total interruption of electrical supply for duration from few milliseconds to one to two seconds . It is 

caused due to insulation failure, lightning and insulator flashover. 

2.7. Long Interruptions 

Total interruption of electrical supply for duration greater than 1 to 2 seconds . It occurs due to 

equipment failure in the power system network. 

2.8. Consequences of the issues 

The voltage variation, flicker, harmonics causes the mal-function of equipment namely microprocessor 

based control system, programmable logic controller. It may lead to tripping of contractors, tripping of 

protection devices, stoppage of sensitive equipments like personal computer, programmable logic control 

system and may stop the process and even can damage of sensitive equipments. Thus it degrades the power 

quality in the grid [3]. 

III. TEST SYSTEM DESCRIPTION 

The test system in Fig.1 consists of Wind generating system connected to the grid with non linear load 

[10]. The STATCOM with battery energy storage is connected at the point of common coupling. The controller 

used with STATCOM is BANG-BANG controller that generates switching signals for STATCOM operation. 

The various parameters used with the test system for simulation are listed in Table 1. 

3.1. Wind Energy Generating System: 

The wind energy generating system considered here is based on constant speed topology with pitch 

control turbine. The wind farm model uses a Induction generator owing to its simplicity. Also, it does not 

require a separate field circuit, can accept constant and variable loads and has inherent short circuit protection 

[7]. 

3.2 STATCOM: 

The grid connected wind generating system model consists of a shunt connected STATCOM with 

Battery Energy Storage connected at the interface of induction generator and non-linear load [1]. The grid 

voltages are sensed by the controller and are synchronized to generate the current command for the inverter. The 

STATCOM inject current into the grid in such a way that the source current is harmonic free and hence power 

quality is improved. 

3.3 System Operation: 

The shunt connected STATCOM with battery energy storage is connected with the interface of the 

induction generator and non-linear load at the PCC in the grid system. The STATCOM compensator output is 

varied according to the controlled phase voltage.The grid connected Wind Generating System model consists of 

a shunt connected STATCOM with Battery Energy Storage connected at the interface of induction generator 

and non-linear load [1].The grid voltages are sensed by the controller and are synchronized to generate the 

current command for the inverter.The STATCOM injects current for the inverter.TheSTATCOM injects current 

into the grid in such a way that the source current is harmonic free and hence power quality is improved. 


11 | Page


110 kV 110 kV / 415V 415V/415V 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

415V/415V 

Y 

L 

O 

A 

D 

Y 

STATCOM 

Fig.1 Test system of Wind farm connected to grid 

VI. Control Scheme 

The control scheme approach is based on injecting the currents into the grid using “bang-bang 

controller.” The controller uses a hysteresis current controlled technique. Using such technique, the controller 

keeps the control system variable between boundaries of hysteresis area and gives correct switching signals for 

STATCOM operation. Fig 2 presents schematic of BANG-BANG controller used with STATCOM [1]. 

In three-phase balance system, the RMS voltage amplitude is calculated at the sampling frequency from the 

source phase voltage V sa ,V sb ,V sc and is expresses, as sample template Vsm , sampled peak voltage , as in (1). 

(1) 

The in-phase unit vector are obtained from AC source phase voltage and RMS value of unit vector U sc , U sb ,U sc 

as show in (2) 

= , = , = (2) 

The in-phase generated reference currents are derived using in-phase generated reference currents are derived 

using in-phase unit voltage template as, in (3). 

= I. , = I. , = I. (3) 

where I is proportional to magnitude of filtered source voltage for respective phase. This ensue source current is 

controlled to be sinusoidal. The unit vectors implement the important function in the grid connection for the 

synchronization for STATCOM. This method is simple, robust and favorable as compared with other methods 

[1]. 


12 | Page


Fig.3 Simulation model of grid connected wind generating system with STATCOM 

V. Simulink Modeling Of Statcom-Based Control Scheme For Grid Connected Wind 

Generating System 

Simulation model of grid connected wind generating system with STATCOM is shown in the Fig.3 and 

the parameters used for the simulation is listed in Table 1. 

Table 1: System parameters 

VI. Simulation Results and Discussion 

CASE 1: Test system without Wind farm and STATCOM 

In this case, the source is directly connected to non linear load without wind farm and STATCOM. Fig 

4 shows the source voltage and current waveforms for case1. It is observed from Fig 4 that the source current of 

the grid is distorted due to the effects of nonlinear load. 

Fig.4 Source voltage and current waveforms of test system without wind farm and STATCOM 

CASE 2: Wind farm connected to grid without STATCOM 


13 | Page


Here, the wind farm is connected to the grid. The current and voltage waveforms of source are depicted 

in Fig 5. From the Fig 5, it is observed that the source current waveform is highly distorted due to the integration 

of wind generating system with the grid. Fig 7 presents the FFT analysis for grid connected wind energy system 

without STATCOM. It shows that the total harmonic distortion for the source current waveform without 

STATCOM is 27.88%. 

Fig.5 Source voltage and current waveforms without STATCOM 

CASE 3: Wind farm connected to grid with STATCOM 

Here, the STATCOM is connected to the grid connected wind generating system at 0.2s.The source 

voltage and current waveforms for this case are presented in Fig 6. It is observed from Fig 6 that when the 

STATCOM controller is switched ON at 0.2s, without change in any other load condition parameters, it starts to 

mitigate the harmonics present otherwise. Fig 8 presents the FFT analysis for grid connected wind energy 

system with STATCOM. It shows that the total harmonic distortion for the source current waveform with 

STATCOM is 4.9% which is within the limits imposed by the standards. Thus the performance of the controller 

designed for STATCOM is satisfactory as it helps in successfully minimizing the source current harmonics 

introduced by the wind generating systems. 

Fig.6 Source voltage and current waveforms with STATCOM 

Fig.7FFT analysis of source current for the test system without STATCOM 


14 | Page


FIG.8 FFT ANALYSIS OF SOURCE CURRENT FOR THE TEST SYSTEM WITH STATCOM 

VII CONCLUSION 

In this paper, the effect of integrating the wind generator with the electric grid was addressed. A test 

system for grid connected wind generating system with non-linear load and STATCOM connected at point of 

common coupling (PCC) was developed in MATLAB/SIMULINK environment. A controller based on 

hysteresis current control scheme was devised for the STATCOM and its effectiveness in minimizing the 

harmonics in the source current waveform from was studied by investigating the waveform before and after 

STATCOM operation. It was observed from the simulation results that the THD in the source current waveform 

has been greatly reduced from 27.88% to 4.90% with the use of STATCOM. 

REFERENCES 

Journal Papers: 

[1] Sharad W. Mohad, and Mohan V. Aware,” A STATCOM-control scheme for Grid Connected Wind Energy System for Power Quality 

Improvement,” IEEE SYSTEMS JOURNAL, VOL 4 NO 3,SEP 2010. 

[2] H. Hassan .El- Tamaly*, Mohamed A. A. Wahab and Ali H. Kasem, “ Simulation of Directly Grid-Connected Wind Turbines for 

Voltage Fluctuation Evaluation,” International Journal of Applied Engineering Research ISSN 0973-4562 Vol.2, No.1, pp. 15– 

30,2007. 

[3] H.M. Abdel_Mageed Sayed, S.M. Sharaf, S.E. Elmasry, M.E. Elharony, “ Simulation of a Transient Fault Controller for a Grid 

Connected Wind Farm with Different Types of Generators”, International Journal of Applied Engineering Research ISSN 0973-4562 

Vol.2, No.1, pp. 15–30,2007. 

[4] Sharad W. Mohad, and Mohan V. Aware,” A STATCOM-control scheme for Grid Connected Wind Energy System for Power Quality 

Improvement,” IEEE SYSTEMS JOURNAL, VOL 4 NO 3,SEP 2010. 

[5] R.Ganesh.Harimanikyam1, R. Lakshmi Kumari, “Power Quality Improvement of Grid Connected Wind Energy System by 

STATCOM for Balanced and Unbalanced Linear and Nonlinear Loads,” International Journal of Engineering Research and 

Development,Vol 3, PP. 09-17.Aug 2012. 

[6] .R.Ganesh.Harimanikyam1, R. Lakshmi Kumari, “Power Quality Improvement of Grid Connected Wind Energy System by 

STATCOM for Balanced and Unbalanced Linear and Nonlinear Loads,” International Journal of Engineering Research and 

Development,Vol 3, PP. 09-17.Aug 2012 

[7] Sreekanth, N. Pavan Kumar Reddy, “PI & Fuzzy logic based controllers STATCOM for grid connected wind generator”, International 

journal of Engineering Research and Application (IJERA).Vol.2,Issue 5,Sep-oct-2012. 

Conference Paper: 

[8] R. S. Bhatia, S. P. Jain, D. K. Jain, and B. Singh, “Battery energy storage system for power conditioning of renewable energy sources,” 

in the Proceedings of International Conference on Power Electronic Drives System, vol. 1, pp. 501–506 Jan 2006N. 


15 | Page




Energy Analysis of LVRM Actuator 

Praveen Kumar .C 

# ME Mechatronics, Anna University Chennai Karpagam College of Engineering Coimbatore 

Abstract: In this paper energy analysis of LVRM actuator is demonstrated. Linear Variable Reluctance Motor 

Actuator (LVRM) is a modification of Switched Reluctance Motor.The motor with transverse magnetic flux 

consists of a primary part, which is moving and a secondary part which is stationary and does not have any 

windings. The motor can operate under AC or DC supply . When supplied from an AC source it must be 

equipped with a capacitor connected in series with the coil. In this case the motor operates on the basis of 

resonance in an RLC primary circuit. When supplied from a DC source it must be equipped with a controlled 

switch connected to the primary circuit.Design calculations were focused on determining the resistance, the 

inductance and the mass of the primary part .The concept of Co-Field energy ,is also demonstrated . 

Keywords: Field Energy,Co-Field Energy, LVRM, Reluctance,SRM 


A reluctance motor is an electric motor in which torque is produced by the tendency of its movable part 

to move to a position where the inductance of the excited winding is maximized [3] .A switched reluctance 

motor (SRM) is simple in construction compared to induction or synchronous machines. A linear motor can be 

defined as being the result of a cylindrical rotary electric machine, which has been mentally split along a radial 

plane, unrolled and flattened[1].The result is an electrical machine in which the primary and the secondary are 

linear and parallel as shown in Figure 1.1. In contrast to a rotational electric motor, a linear motor generates a 

linear force (thrust force) along its length, i.e. there is no torque or rotation is produced by the relationship 

between electric currents and magnetic field. By supplying suitable currents to the primary with a suitable 

excitation in the secondary of a linear motor, they will move relatively in a linear path. This makes linear motors 

have a number of advantages over rotational motors in linear motion. Linear switched reluctance machines are 

an attractive alternative due to the lack of windings on either the stator or translator structure. The windings are 

concentrated rather than distributed making them ideal for low cost manufacturing and maintenance. Further, 

the windings are always in series with a switch so that, in case of a shoot-through fault, the inductance of the 

winding can limit the rate of change of rising current and provide time to initiate protective relaying to isolate 

the faults. Moreover, the phases of the linear switched reluctance machine areindependent and in case of one 

winding failure, uninterrupted operation of the motor drives ispossible though with reduced power output [4]. 

These advantages enable the linear switchedreluctance machine drives to operate as an economical high 

performance system with better failsafereliability. The linear switched reluctance machines are the counterparts 

of the rotatingswitched reluctance machines . 

Figure 1.1 Imaginary process of splitting and unrolling a rotary machine to produce a linear motor [81] 


16 | Page

Energy Analysis Of LVRM Actuator 

Fig 1.1a Proposed LVRM Actuator 

II. MAGNETIC ENERGY ANALYSIS OFLVRM ACTUATOR 

In an electromagnet [5] the current is generated by the magnetic field. To determine the magnetic field 

energy stored in the motor let the electromagnetic structure shown inFig. 1.2 be considered. It consists of 

primary part, which does not move and the secondary part that can move and does not have the 

winding.Assuming that the secondary part does not move, the instantaneous voltage across the terminals of a 

single-phase SRM winding is related to the flux linked in the winding by Faraday‟s law, 

V = i R + dλ 

(1.1) 

dt 

V- terminal voltage , i-phase current , λ- flux linkage 

R-resistance 

The flux linkage in an SRM varies as a function of rotor position θ and the motor current i. Thus equation 

can be represented as 

V= i R+ dλ di 

+ dλ dθ 

(1.2) 

di dt dθ dt 

dλ 

is defined as winding inductance L(θ,i) which is a function of rotor position and current . Multiplying both 

di 

sides of equation by electrical current i ,gives the expression for instantaneous power in LSRM . 

V=i 2 R + i dλ 

dt 

= i 2 R+ i dλ di 

di dt 

(1.3) 

Figure 1.2 Illustration of field energy of LSRM 

The left hand side of the above equation denotes the electrical power P e delivered to LSRM . The firs term on 

the right hand side represents the ohmic losses and the second term represents the electrical power at coil 

terminal which is the sum of mechanical output and any power stored in LSRM 

. 

P e = L dI 

dt i (1.4) 

Relation between Power and Energy is 

dW e 

dt 

= P e (1.5) 


17 | Page


Where W e denote total energy delivered to winding which is the sum of energy stored in the coil W f and 

energy converted to Mechanical work W m done . 

W e = W f + W m (1.6) 

Magnetic field energy W f = 

λ 

i dλ 

0 

(1.7) 

The energy stored in the Magnetic field with air gap ‟ g‟ can be expressed I terms of magnetic flux density B g 

as 

B g 

W f = dB 

µ g . V g = B g 

V 

0 2 µ g (1.8) 

0 

The field energy is inversely proportional to permeability and directly proportional to volume of air gap . 

′ 

The area below the curve in fig 1.3 is defined as magnetic Co- field energy . Co-field energyW f is defined 

by 

′ i 

W f = λ . di 

(1.9) 

o 

If λ - i is nonlinear then W ′ f >W f 

Fig 1.3 Graphical Interpretation of magnetic field energy 

Consider Fig 1.2 if secondary part is moved slowly then current remains the same at both positions because 

coil resistance does not change and voltage is said to be a constant. 

The operating point has moved slowly from point a → b (fig 1.4) . 

Fig 1.4 Illustration to magnetic force derivation 

During the motion increment electric energy has to be send to system 

λ 2 

dW e = e . i dt = i dλ = area (a b c d) (1.10) 

λ 1 

The field energy has been changed by this increment : 

dW f = area (O b c –O a d ) (1.11) 


18 | Page


The Mechanical energy , 

dW m = dW e - dW f 

= area (a b c d ) + area (O a d) – area (O b c) (1.12) 

= area (O a b) 

is equal to mechanical work done during the motion of secondary part and is represented by the shaded area 

in fig 1.4 . This shaded area can also be seen as increase in Co- Energy : 

dW m = dW f 

′ 

(1.13) 

Since : 

dW m = f m dx (1.14) 

The force f m that is causing differential displacement is : 

f m = ∂W ′ 

f (i,x) 

i = constant (1.15) 

∂x 

In a linear system coil inductance L linearly varies with the primary position for a given current .Thus for an 

idealized system : 

λ = L (x ,i) I (1.16) 

Since the Co-field energy is given by Eq (1.9) after inserting the value of λ from Eq (1.16) into Eq (1.9) we 

obtain : 

W f 

′ 

= 

i 

L x, i . di 

0 

= 1 2 L x i2 (1.17) 

The Magnetic force acting on the secondary part is obtained from Eq (1.15 ) and Eq (1.17) . 

f m = ∂ 

∂x (1 L x 2 i2 = 1 dL (x) 

i2 

2 dx 

(1.18) 

For a linear system field energy is equal to Co–field energy 

W f = W f 

′ 

= 1 2 L(x) i2 (1.19) 

If the primary part of the reluctance motor is an electromagnet we can use Eq (1.18) to determine the force 

acting on secondary part. 

There is another force attractive force f y which can be expressed in terms of magnetic flux density B g . 

Fig 1.5 Force components in a reluctance motor 

The relation between current number of turns and field intensity is given by : 

N i =H g 2g = 

B g 

µ 0 

2g (1.20) 


19 | Page


i = 

B g 

N µ 0 

2g (1.21) 

The coil inductance L depends on the reluctance of magnetic circuit which is given by : 

L = N2 µ 

g 

A m 

(1.22) 

from equations 1.17 , 1.19 and 1.21 we obtain 

W f 

′ 

= B g 2 

2 µ 0 

A g 2g (1.23) 

from equation 1.15 and 1.23 we obtain 

f y = ∂ 

∂g ( B g 2 

2 µ 0 

A g 2g )= B g 2 

2 µ 0 

2A g (1.24) 

CONSTRUCTION OF A 1ɸ LVRM ACTUATOR 

A single phase variable reluctance motor with U shaped primary core is considered . The motor 

consists of a primary part that possess winding and secondary part .The winding of primary is supplied with 

voltage v which causes a current to flow .The current produces a magnetic flux ɸ that flows through a closed 

path that is perpendicular to the direction of motion (x axis) [9] . 

Fig 1.6 Single phase linear reluctance motor with U shaped primary core 

The primary part is affected by two forces a propulsive force f x and attractive force f y .The linear propulsive 

force is expressed as 

f x = 1 dL (x) 

i2 

2 dx 

(1.25) 

L(x) denote coil inductance which is expressed as a function of x coordinate . The higher the value of 

stronger the propulsive force . 

dL (x) 

dx 

The inductance of the primary coil is expressed as a function that depends on the shape of primary and 

secondary core .For the construction show above it may be approximated by the function 

L = L m 1 + cos ( 

π 

l 

x ) + L min (1.26) 

Shown graphically in Fig 1.7 

L m = L max − L min 

2 

The force that is proportional to 

derivative of inductance . 

d L(x) 

dx 

(1.27) 

is not only changing in value but also in its direction which is seen in 

dL (X) 

dx 

= (-) L m sin ( π l x) . π l 

(1.28) 


20 | Page

When the position of the centre of the primary is at (-x 1 ) 

dL (x) 


is positive and force is positive . The primary placed between the middle of the secondary elements is 

dx 

not affected by any force , the same is the case when primary comes in full alignment with the secondary . 

The primary is always affected by an attractive force 

f y = B g 2 

2 µ 0 

A g (1.29) 

B – magnetic flux density ,A g – air gap area 

Fig 1.7 Inductance and derivative of inductance changing 

1V MODES OF OPERATION 

A) AC SUPPLY 

LVRM actuator operates from AC source using the principle of resonance in RLC circuit of primary 

part . The primary part moves with respect to secondary in x-direction .During the motion coil inductance L 

changes since it depends on the position of primary part with respect to secondary part . The middle of primary 

coil is placed at distance (- x 1 ) ( see Fig 1.8 ) and inductance of the coil is equal to L(-x 1 ) ( see Fig 1.9) . 

2 dL (x) 

dL(x) 

Since the force acting on the primary part is f m = 0.5 i and the derivative at x =x 

dx 

dx 

1 is positive it 

will be pulled to the middle (x=0) of the secondary element .Due to the inertia of primary part it moves to the 

edge of the secondary part . During its movement it experiences a negative force beyond „0‟ point but this 

braking force is less than driving force , which the primary experiences before „0‟ point .The resultant effect is 

that primary part is leaving the secondary part and approaching the next secondary part where it is again driven 

to the positive direction of x-axis . [7] 

Fig 1.8 LVRM supplied from an AC source 


21 | Page


Fig 1.9 Inductance and derivative of inductance waveforms 

To increase the driving force a capacitor C is connected in series with the primary part .The value of 

capacitor is chosen there to give resonance in R-L-C circuit , at position (-x 1 ) ( see Fig 2.0) ) a heavy current 

flows , the primary is pulled towards „0‟ point with a strong force . The resultant effect is that primary gets a 

strong “ kick” at a place when resonance occurs , moving the actuator more effectively in x- direction .The 

capacitance at a particular position can be defined by using resonant condition formulae 

C = 

1 

2 π f 2 L ( x 1 ) 

Fig 2.0 Inductance and resonance current as a function of displacement x 

B) DC SUPPLY 

To improve the performance of LVRM energise the primary part when it is affected by a force in 

positive direction ( 

dL (x) 

dx 

is positive – see Fig 1.9) , that is when the primary moves from the edge (position - 

x 1 ) to the centre point „0‟ .This of course requires the application of a controlled switch which would switch 

the primary part ON and OFF at its particular position with respect to secondary. It means motor must be 

equipped with a switching circuit instead of a capacitor . (see fig 2.1) 


22 | Page


Fig 2.1 LVRM actuator with DC source 

An LVRM actuator with DC supply is shown in Fig 2.2Power MOFET can be used as a switch .When 

MOSFET turns on full voltage appears across the motor and inductance of coil winding causes current to flow 

through the coil . When MOSFET turns OFF energy stored in the inductance of motor winding forces diode into 

conduction . During this time current is ramping down .Fig 2.3 shows two modes of operation under DCsupply 

condition .The diode allows magnetic energy stored in the coil to be released after switching off . [11] 

Fig 2.2 Circuit diagram of a linear reluctance motor under DC supply 

a) b) 

Fig 2.3 Switch control ( a) MOSFET conduction cycle ( b )Diode fly back conduction cycle 


23 | Page


V. CONCLUSION 

The energy analysis single phase LVRM actuator was presented in this paper .LVRM work on the 

principle of Co- field energy which is found to be greater than magnetic field energy , considering non-linear 

magnetisation characteristics . It could operate both on AC supply and DC supply . The advantage of LVRM is 

that linear motion is obtained directly ,no rotary to linear conversion is required. Hence the frictional losses that 

occur in commonly used rotary to linear energy conversion mechanisms such as lead –screw ,chain drive and 

belt drive is avoided. 

Acknowledgement 

I owe a great attitude to my HOD Dr.PSathyabalan (Mechatronics DeptKarpagam College Of Engg 

Coimbatore ) for encouraging me to do work in this field .I also thank my guide Mr.ChandrasekarAsst .Prof 

PG-Mech for evaluating my performance at each stage of work . I extend gratitude to my family members for 

their patience and encouragement during the preparation of the manuscript . 

Authors Profile 

Mr . Praveen Kumar .C is working as an Asst .Prof in Electrical and Electronics Engg Dept of 

NSS College of Engineering , Palakkad ,Kerala . Currently he is pursuing his ME Degree in 

Mechatronics Engineering at Karpagam College of Engineering ,Coimbatore ( Affiliated to 

Anna University Chennai ) . His areas of interest include Special Machines , Linear Machines 

and Bio Mechatronics . 

References 

[1] P. Khong, R. Leidhold and P. Mutschler. “Magnetic guidance of the mover in a long-primary linear motor,” Industry Applications, 

IEEE Transactions – electronic publishing, DOI: 10.1109/TIA.2011.2125934, March 2011. 

[2] P. Khong, R. Leidhold and P. Mutschler. “Magnetic guidance of the mover in a long-primary linear motor,” in ECCE 2009. IEEE, 

San Jose, CA Sept. 2009, pp. 2354–2361 

[3] P. Khong, R. Leidhold and P. Mutschler.“Magnetic guiding and capacitive sensing for a passive vehicle of a long-primary linear 

motor,” in EPE/PEMC 2010, Ohrid-Macedonia, Sept. 2010, pp. S3-1 – S3-8. 

[4] R.Krishnan, R.Arumugam, James F. Lindsay, “Design procedure for switchedreluctancemotors”, IEEE Trans. on industry 

applications, Vol. 24, No.3, 1988. 

[5] Bae,Han-Kyung,Byeong-SeokLee, Praveen Vijayraghavan, and R.Krishna, “Linearswitched reluctance motor: converter and 

control”, in Conf. Rec. of the 1999 IEEE IAS Ann. Mtg., Oct. 1999, Phoenix, AZ, pp. 547-554. 

[6] T. Kenjo and S. Nagamori, “Permanent-magnet and brushless DC motors”,Clarendon Press, Oxford, 1985 

[7] E.A. Mendrela, “Comparison of the performance of a linear reluctance oscillatingmotor operating under AC supply with one under 

DC supply”, IEEE Trans. 0nenergy conversion, Vol. 14, No.3, September 1999 

[8] E.A. Mendrela, “Comparison of the performance of a linear reluctance oscillatingmotor operating under AC supply with one under 

DC supply”, IEEE Trans. Onenergy conversion, Vol. 14, No.3, September 1999 

[9] R. Krishnan. “Propulsion with and without wheels.” in IEEE International Conference on Industrial Technology (ICIT), vol. 1, no. 2, 

2005, pp. 11–19. 

[10] T. Masuda, M. Yoshikawa, M. Tawada. “Formulation of elevator door equation of motion.”JSME International Journal Series 

Dynamics Control Robotics Design and Manufacturing, vol. 39, no. 2, pp. 279–285, 1996. 

[11] P. Mutschler. Class lecture, Topic: “Control of Drives.” Institute of Power Electronics and Control of Drives, TU Darmstadt, Sep. 

2004 


24 | Page




Power Scenario Prospects for Micro Grid 

P. Nivedhitha 1 

1 Department of Electrical and Electronics Engineering, Thiagarajar College of Engineering, Madurai, India 

Abstract: This paper gives an overview of the developing Micro Grid technology for power systems. To 

overcome energy crisis, renewable energy sources prove to be an alternate. It briefs on the technical outlook, 

applications, and advantages of Micro grid over the ordinary passive macro grids, thus widening its scope for 

research and development globally. 

Keyword: Renewable energy resources, Centralised grid, Micro grid, Distributed Generation 


Energy is the lifeblood of modern civilisation. With the emerging thirst for domestic and industrial 

power, energy management has become a challenge. The time has ripened to adopt evolutionary strategies 

across the globe to provide consistent, cost effective, affordable, green and quality power for socio-economic, 

environmental and technical benefits. One such strategy is Micro Grid that integrates distributed on-site 

generation stations of end-users, with or without the Centralised grid, making electricity bidirectional. It perfects 

power for a secure and sustainable future in energy sector. 

II. BASIC CONCEPTS OF MICRO GRID 

Micro grid is an aggregated concept with participation of available supply and demand side energy 

resources in low-voltage distribution grids, via application of emerging technologies in power electronics 

interfaces, modern controls and nanotechnology. A sample Micro grid is shown in Fig. 1. Such self-sufficient 

„future guaranteed‟ systems can be operated in a non-autonomous way, if interconnected to the grid. Otherwise 

it can be operated in an autonomous way, if disconnected from the main grid. 

III. NECESSITY FOR MICRO GRID 

The global consumption of electricity is increasing alarmingly, as shown in Fig. 2. Currently two 

billion people around the world have no access to electricity at all. It is of high priority to address and change 

the existing energy scenario, making a march towards ‘Energy to All’ globally. Renewable Energy resources can 

find an acute solution to this issue. It is estimated that the renewable energy resources across the globe has the 

potential to supply 3087 times the current electricity demands. 


25 | Page

Power Scenario Prospects For Micro Grid 

Fig. 2 World Electricity Consumption 

To make use of the fullest available potential of renewable energy resources, self-sufficient on-site generation 

plants like solar power, wind, fuel cells, and biomass can be installed, ensuring the exact needs of the Micro grid 

constituents duly served while networking with the Centralised grid. 

The Government is bound to encourage such demand side generation by providing subsidies to 

consumers, in the interest of ‟energising‟ the country. The consumer can also seek revenue for the surplus 

energy generated by the domestic plant, by supplying it to the Centralised grid. This ‘Energy by All’ 

phenomenon in turn provides an opportunity for individuals to significantly participate in the active energy 

growth of a nation. Thus, Micro grids open the door for a new, innovative electrical ecosystem. 

IV. BENEFITS OF MICRO GRID 

Micro grid, though not a replacement for the national grid as a whole, improves certain aspects 

remarkably. It paves way for every remote area to have access to uninterrupted power supply. It offers a wide 

range of socio-economic, technical and environmental benefits to the consumer that includes: 

1) Economic Benefits: 

Local Consumer Benefit - Micro grids can accelerate economies opening new avenues for job opportunity at 

the local level. Cost per unit of energy is reduced. This encourages a new electricity generation business 

model that is more efficient with the available renewable resources, and likely to spur continuous innovation. 

Generates Revenue – Transmission Cost as far as the end user is concerned is reduced significantly. Supports 

new entrepreneurial energy markets, allowing customers to sell excess production of energy into the bulk 

energy market. These smart Micro grids also set the stage for additional consumer revenues from plug-in 

electric vehicles and carbon credits. Analogous to „Drops of water make an Ocean‟, Micro grids in unison 

will lead to „Energy Revolution‟. 

2) Technical benefits: 

Reliability – Local power generation and storage allow certain portions of the grid to operate independent of 

the National grid when necessary, thus avoiding black outs. Redundant sources enable continuous power 

flow even during environmental interruptions in the system. 

Better Performance Characteristics– There is nearly 82% annual transmission loss reduction in Micro grids 

than the normal passive grids, thus serving the purpose of energy management. The voltage regulation is 

reduced by 57% when compared with passive networks. Also 50% reduction in the peak load supply by the 

Centralised National Grid is observed by the use of Micro Grids. 

Stability – Independent local control of generators, batteries and loads are based on frequency droops and the 

voltage levels at the terminal of each device and hence it is highly stable. 

Compatibility – Micro grids are completely compatible with existing utility grid. They may be considered as 

functional units that support the growth of the existing system in an economically and environment – 

friendly way. 

Scalability - Micro grids can grow through additional installation of generators, storage elements and loads. 

Such an extension usually requires an incremental new planning of the Micro grid and can be performed in a 

parallel, modular manner in order to scale up to higher power production and consumption levels. 


26 | Page


3) Environmental Benefits: 

Reduces Carbon Print – The smart Micro grid can reuse the waste energy produced during generation of 

electricity to heat up buildings, sterilization and cooling. This bottom-up consumer approach reduces the 

reliance on fossil fuel and green house gases emission, thus enabling carbon credits. 

V. TECHNICAL ASPECTS OF MICRO GRID 

Prima-facie to establishing a Micro grid, the following aspects are to be analysed: 

Energy Audit on available on-site renewable energy resources, controllable loads, energy storage, combined 

heat and power facilities, cooling. 

Switchgear utility interconnection including low-cost switches, interconnection study, and protection schemes 

study. 

Standards and protocols, control algorithms and software for integration with energy management system 

utilities, real-time signals processing, local SCADA access, power electronics devices. 

Modelling & Analysis, system integration, testing, and validation of the local site. 

A Micro grid can operate in two modes namely: 

Grid Connected Mode – Micro grid is connected to the Centralised Electricity Power Grid. 

Isolated Mode – Micro grid operates autonomously, disconnected from the Centralised grid. 

. 

Fig. 3 Micro Grid Architecture 

Infrastructure of Micro grid technology, as in Fig. 3 includes the following: 

1) Micro source Controller comprising of power electronic interfaces such as inverters, DC interfaces, offer 

control possibilities that go beyond simple control of real power. 

The requirements to control a Micro grid provided by each Micro source are: 

Control of real and reactive power – In both DC and AC Micro sources, the DC voltage generated is 

converted to AC using a voltage inverter to maintain the power factor at the interfacing end, connected via 

an inductor with the Centralised grid. 

Voltage regulation through droop – Voltage regulation is necessary for reliability and stability. In a Micro 

Grid, which is typically radial, the problem of large circulating reactive currents is immense. With small 

errors in voltage set points, the circulating current can exceed the ratings of the Micro sources. Therefore, 

with Q-point should be maintained constant between the highly inductive and capacitive loads. 

Fast load tracking and storage – In isolated mode of operation, when a new load comes on line, the initial 

energy balance is satisfied by the system‟s inertia, which results in a slight reduction in system frequency. 

To balance that super capacitors or batteries are added with the Micro source. 

2) Energy Manager is a “supervisory controller” that meets operational objectives and constraints by 

dispatching devices. The objective will typically be to minimize the total energy bill within the constraints 

of the system, which might include serving heat and electrical loads, fuel costs, and equipment performance 

specifications, limitations due to safety, fuel supply limitations, and restrictions on noise or pollutant 

emissions. 

3) Protection Coordinator, which rapidly isolates feeder faults within the Micro Grid and communicates 

feeder status changes to the Energy Manager. 


27 | Page

Local 

Distributed 


4) Control Algorithms facilitates robust behaviour of energy manager and protection co-ordinator, the 

information infrastructure, as shown in Table I needs to be fault-tolerant and be able to deal with a dynamic 

environment. 

TABLE I 

MICRO GRID INFORMATION CONTROL 

Non real-time 

Real Time 

Data Aggregation, 

Logging 

Smart Metering, System 

monitoring, Demand side 

management, Peak 

shaving, Power quality 

analysis, Market & 

Trading 

Voltage droop control, 

Frequency droop control 

Load shedding (Generated 

power < Demand), Power 

quality mitigation, 

Resynchronisation after 

islanding (isolated mode). 

5) Communication Protocols, like the standard IEC 61850 series protocols which provide object models for the 

information exchange is used. 

6) Micro grid Integration Standard usually used is the IEEE 1547 series for design, operation and integration of 

Micro grids with the Centralised grid. 

VI. APPLICATIONS OF MICRO GRID 

Micro grid opens up an all new Corporate Energy Market. Germany leads the globe in production of 

electricity from renewable resources, followed by United Kingdom, Indonesia and Italy. In India, it has become 

increasingly popular in the very recent years, as shown in Fig. 4 and Micro grid is sure to make a remarkable 

mark in this sector. 

Fig. 4 Increasing share of renewable energy in India 

A. Military Bases 

Military bases are usually located in remote locations of a country; fuel is trucked to run its generators. 

Micro grid can prove to be an alternative for this fragile source of power. The Military Base could be made 

energy-sufficient by building a Micro grid with the renewable resources available on-site. US Army Fort Bragg, 

North Carolina has made the initiative and is running successfully. 

B. Industrial & Educational Campuses 

A Micro grid can be built in such campuses that ensure redundant electricity supply with the resources 

available. It eliminates outages, minimize power disturbances, moderate an ever-growing demand and curb 

greenhouse gas emissions. IIT, USA, Intel and Ford have established Micro grid in its campus. 


28 | Page


Fig. 5 Commercial Micro grid on-site 

C. Remote Villages 

This segment represents the greatest number of Micro grids currently operating globally, but it has the 

smallest average capacity. While many systems have historically featured diesel distributed energy generation, 

the largest growth sector is solar photo voltaics. Wind mills with Micro turbines are projected to play a growing 

role as well. Gram Power established by Mr. Yashraj Khaitan and Mera Gao Power in India commercialised 

Micro grid technology and turned out to be one the best clean technology innovations. 

D. Community Micro grids 

Community energy Micro grids are for people, not utility companies. CMGs are about tapping into, 

distributing, and using 100% locally produced renewable energy with local labour and materials. Community 

Micro grids can provide ample local and renewable power without connecting to the main grid. This lowers the 

energy costs and peak demand. Santa Rita Jail in California's Alameda County has built smart Micro grid and 

has saved 50% of its energy expenses. 

Fig. 6 Community Micro grid 

VII. FUTURE SCOPE OF MICRO GRID 

Micro Grid promises wide scope of research in: 

Better performance of frequency and voltage control methods under various operation modes. 

Improvement of Distributed Resource technology and development of suitable architectures and control 

technologies for Micro grid. 

Development of improved approaches for interfacing Micro grids to the centralised grid. 

Transformation of Micro grid system into an intelligent, robust energy delivery system in the future by 

providing significant reliability and security. 

To improve transition between the grid connected and isolated operating modes. 

Deployment of Micro grid business parks. 

VIII. CHALLENGES OF MICRO GRID 

The initial cost of installation of on-site production plants is more. 

Availability of funds at higher rates of interest. 

Synchronisation of Micro grid with Centralised grid is difficult. 

Quality of power generated at each Micro source should be improved. 


29 | Page


Space constraint; technology at its naive stage. 

Lack of awareness among the public. 

IX. CONCLUSION 

It is the responsibility of the Government to provide capital subsidies, and loans at cheaper rates to the 

consumers for establishment of a Micro grid. It also has to provide such consumers with energy credits for 

sharing the energy burden of the Government. Awareness campaigns should be convened. 

The intelligent transformation in infrastructure and policies of Micro grid is the key to achieve sustainable, 

environmental, and economic energy for today‟s citizens and future generations. Thus, Micro Grid promises 

energy surety for the future. 

ACKNOWLEDGMENT 

The author is thankful to the authorities of “Thiagarajar College of Engineering, Madurai – 625015”, 

for providing all the facilities to do this research work. 

References 

[1] Christine Schwaegerl, Advanced Architecture and Control Concepts for more Micro grids, Siemens AG, Germany, December, 2009. 

[2] Robert Liam Dohn, The Business Case for Micro grids, Siemens, Germany, 2009. 

[3] Robert Lasseter, Abbas Akhil, Chris Marnay, John Stephens, Jeff Dagle, Ross Guttromson, A. Sakis Meliopoulous, Robert Yinger, and 

Joe Eto, White Paper on Integration of Distributed Energy Resources -The Micro grid Concepts, Consortium for Electric Reliability 

Technology Solutions, December, 2001. 

[4] Bren Koposki, Charlie Vartanian, Micro grid Standards and Protocols, DOE Micro grid Planning Meeting. 

[5] The Value of Smart Distribution and Micro grids, Galvin Electricity Initiative, January 2010. 

BIOGRAPHIES 

P. Nivedhitha is doing her B.E. Degree in Electrical and Electronics Engineering at Thiagarajar College of Engineering, Madurai. 

Her field of interest is Power Systems and Energy. 


30 | Page




Performance Of System Functions as Effective Simulation Tool 

For Implementation Of Customized Algorithms 

P.Meena 1 , Dr. K. UmaRao 2 , Dr. Ravishankar Deekshit 3 

1 (EEE, B.M.S. College of Engineering, India) 

2 (EEE, R.V. College of Engineering, India) 

3 (EEE,B.M.S. College of Engineering, India) 

Abstract: This work presents the results obtained by using System Functions (S functions) and comparing it 

with that obtained using Matlab Code Functions to customize an algorithm. The algorithm developed is to 

detect short duration voltage disturbances in power supply systems. These disturbances cause deviations in 

voltage current and frequency from their nominal value which eventually results in failure or mis-operation of 

sensitive equipment connected to the supply. The efficient detection, record and mitigation of these disturbances 

is the prime focus of research in the area of power quality improvement. Hence quickness and accuracy 

associated with the detection process are vital parameters that govern the effectiveness of these detection 

algorithms. The customized algorithm is intended to be implemented on a Digital Signal Processor through an 

integrated Matlab/ Simulink environment. The measure of effectiveness of the methodology of implementation 

facilitates an optimal choice. The paper presents the results obtained using System Function for simulation of 

the detection algorithm and comparison with that obtained by using Matlab Code Function. 

Keywords: S-functions,Matlab-EmbeddedFunctions,effectiveness,accuracy,algorithm . 


The S-functions (system-functions) provide a powerful mechanism for extending the capabilities of 

Simulink. An S-function is a computer language description of a Simulink block [1]. S-functions can be written 

in MATLAB, C, C++, Ada, or Fortran. C, C++, Ada, and Fortran S-functions are compiled as MEX-files using 

the mex utility. 

The most common use of S-functions is to create custom Simulink blocks. We can use S-functions for 

a variety of applications, including, adding new general purpose blocks to Simulink, adding blocks that 

represent hardware device drivers, Incorporating existing C code into a simulation, describing a system as a set 

of mathematical equations and using graphical animations. An advantage of using S-functions is that, we can 

build a general-purpose block that we can use many times in a model, varying parameters with each instance of 

the block. Matlab also provides a user-defined function known as Matlab code functions which is a Matlab 

program that is created by the user, saved as a function file, and then used like a built -in function. 

In this paper the system block developed is intended to detect short duration disturbances that occur in 

power supply systems in real time using a digital signal processor through an integrated Matlab/Simulink 

environment using the embedded link to code composer studio. The disturbances have duration ranging from 

half a cycle to one minute. The frequent occurrences of these disturbances do affect the performance and life of 

sensitive digital equipment and corrupt digital data. Quick detection of these disturbances is necessary for 

initiating restoration mechanisms that follow such as activation of a power line conditioner or a dynamic 

voltage restorer. The details of the simulation stages in simulink environment and how the function can be 

developed to customize any algorithm is initially discussed, followed by the description of the detection 

algorithm The results measuring the effectiveness of detection using the system function developed over that 

using Matlab code functions for the purpose are presented. 

II. SIMULATION STAGES 

Execution of a Simulink model proceeds in stages. First comes the initialization phase. In this phase, 

Simulink incorporates library blocks into the model, propagates widths, data types, and sample times, evaluates 

block parameters, determines block execution order, and allocates memory. Then Simulink enters a simulation 

loop, where each pass through the loop is referred to as a simulation step. During each simulation step, Simulink 

executes each of the model's blocks in the order determined during initialization. For each block, Simulink 

invokes functions that compute the block's states, derivatives, and outputs for the current sample time. This 

continues until the simulation is complete. 


31 | Page

Performance Of System Functions as Effective Simulation Tool For Implementation Of Customized 

III. S-FUNCTION CALLBACK METHODS 

An S-function comprises a set of S-function call-back methods that perform tasks required at each 

simulation stage. During simulation of a model, at each simulation stage, Simulink calls the appropriate methods 

for each S-Function block in the model. Tasks performed by S-function methods include , 

3.1. Initialization 

Prior to the first simulation loop, Simulink initializes the S-function. In this stage, Simulink initializes 

the Sim Struct, a simulation structure that contains information about the S- function, Sets the number and 

dimensions of input and output ports. Sets the block sample times. allocates storage areas and the sizes array. 

3.2.Calculation of next sample hit 

If a variable sample time block is created, this stage calculates the time of the next sample hit; that is, it 

calculates the next step size. 

3.3.Update of discrete states in the major time step 

In this call, all blocks should perform once-per-time-step activities such as updating discrete states for 

next time around the simulation loop. 

3.4.Integration 

This applies to models with continuous states and/or non-sampled zero crossings. If S-function has 

continuous states, Simulink calls the output and derivative portions of S-function at minor time steps. So 

Simulink can compute the states for S-function. If S-function (C MEX only) has non-sampled zero crossings, 

Simulink calls the output and zero-crossings portions of S-function at minor time steps so that it can locate the 

zero crossings. 

IV. USING S-FUNCTION IN MODELS 

To incorporate an S-function into a Simulink model, the S-Function block is dragged from the 

Simulink User-Defined Functions block library into the model. The name of the S-function is specified in the S- 

function name field of the S-Function block's dialog box 

V. S-FUNCTION CONCEPTS 

Direct feed through means that the output (or the variable sample time for variable sample time blocks) 

is controlled directly by the value of an input port. A good rule of thumb is that an S-function input port has 

direct feed through if the outputs function is a function of the input u. That is, there is direct feed through if the 

input u is accessed in model outputs. The "time of next hit" function of a variable sample time S-function 

accesses the input u. An example of a system that requires its inputs (i.e., has direct feed through)is the 

operation y=k*u , where u is the input, k is the gain, and y is the output. 

It is very important to set the direct feed through flag correctly because it affects the execution order of the 

blocks in the model and is used to detect algebraic loops. 

Dynamically Sized Arrays-S-functions can be written to support arbitrary input dimensions. In this 

case, the actual input dimensions are determined dynamically when a simulation is started by evaluating the 

dimensions of the input vector driving the S-function. The input dimensions can also be used to determine the 

number of continuous states, the number of discrete states, and the number of outputs. 

Setting Sample Times and Offsets-Both M-file and C MEX S-functions allow a high degree of flexibility in 

specifying when an S-function executes. Simulink provides the following options for sample times, 

5.1.Continuous sample time 

For S-functions that have continuous states and/or non-sampled zero crossings for explanation. For this 

type of S-function, the output changes in minor time steps. 

5.2.Continuous but fixed in minor time step sample time 

For S-functions that need to execute at every major simulation step, but do not change value during 

minor time steps. 

5.3.Discrete sample time 

If S-Function block's behavior is a function of discrete time intervals, you can define a sample time to 

control when Simulink calls the block. we can also define an offset that delays each sample time hit. The value 

of the offset cannot exceed the corresponding sample time. A sample time hit occurs at time values determined 

by the formula, TimeHit = (n * period) + offset. Where n, an integer, is the current simulation step. The first 


32 | Page


value of n is always zero. If one defines a discrete sample time, Simulink calls the S-function model Output and 

model update routines at each sample time hit (as defined in the above equation). 

5.4.Variable sample time 

A discrete sample time where the intervals between sample hits can vary. At the start of each 

simulation step, S-functions with variable sample times are queried for the time of the next hit. Sometimes an S- 

Function block has no inherent sample time characteristics (that is, it is either continuous or discrete, depending 

on the sample time of some other block in the system).Then the block's sample time is specified as inherited 

VI. WHY CHOOSE C FOR WRITING FUNCTION RATHER THAN MATLAB? 

The set of callback methods, hence functionality, that C MEX-files can implement is much larger than 

that available for M-file S-functions. Unlike M-file S-functions, C MEX-files can access and modify the data 

structure that Simulink uses internally to store information about the S-function. This allows C MEX-files to 

implement a wider set of block features, such as the ability to handle matrix signals and multiple data types. 

C MEX-file S-functions are required to implement only a small subset of the callback methods that Simulink 

defines. If the block does not implement a particular feature, such as matrix signals, we are free to omit the 

callback methods required to implement a feature. This allows one to create simple blocks very quickly. 

VII. 

The different approaches for creating C Mex S-Functions are, 

DIFFERENT APPROACHES FOR CREATING C MEX S-FUNCTION 

7.1.Handcrafted S-Function 

This can create S-function from scratch using a skeleton S-function (Template). 

7.2.S-Function Builder 

This block builds a C MEX S-function from specifications and code fragments that are supplied using a 

graphical interface. This eliminates the need to write S-functions from scratch. 

7.3.Legacy Code Tool 

This utility builds a C MEX S-function from existing C code and specifications that are supplied using 

MATLAB M-code. 

Handcrafted S-function has been chosen in this work because although other two methods simplifies 

task of writing C-MEX S-functions they support fewer simulink features, whereas handcrafted s-function 

though difficult to write ,support widest range of simulink features.S-functions are written using an Application 

Program Interface (API) that allows to implement generic algorithms in the Simulink environment with a great 

deal of flexibility. This flexibility cannot always be maintained while using S-functions with Real-Time 

Workshop for example when implementing the algorithm with standalone devices like DSP. Although S- 

functions provide a generic and flexible solution for implementing complex algorithms in Simulink, the API 

incurs overhead in terms of memory and computation resources. In many cases in real-time embedded 

applications one can minimize memory and computational requirements by using the Target Language Compiler 

technology provided with Real-Time Workshop to inlining an S-function. One can inline S-function in two 

ways by, writing Wrapper S-function for the algorithm and callling those function using a wrapper S-function. 

An S function can also be in-lined by writing .tlc file for the algorithm. Though difficult to debug, accuracy of 

result is very high. 

So by in lining an S-function, over head incurred by API and computational complexity can be 

eliminated. So speed of execution of algorithm on standalone devices like DSP is increased and accuracy of 

result is very high. 

VIII. IMPLEMENTATION OF A DISTURBANCE DETECTION ALGORITHM 

USING S FUNCTION 

Sags and swells are short duration voltage disturbances that occur in power supply systems. Sag is said to 

occur when the voltage falls between (0.1p.u-0.9p.u).Swell is said to occur when the voltage increases 

between(1.1p.u -1.9p.u.). The algorithm for sag and swell detection [2] is implemented using S-function and 

Matlab embedded function. 

There are several detection methods for voltage sags in which sag voltages are usually expressed in terms of 

Root Mean Square (rms) values. Root Mean Square (rms) value of a signal can be used effectively to detect 

voltage sags and swells. Consider a periodic signal v(t) 

of period T which is sampled at a frequency of f s ,the 


33 | Page


sampling time being 

T 

s 

1 

.The number of samples in one cycle is 

f 

s 

T 

M .Let v(k) 

T s 

be the voltage at any 

sampling interval. For a discrete waveform, the rms values can be continuously calculated over a moving 

window of voltage samples ,the size of the window being M. Therefore, the rms value of the signal at any 

sampling interval is , 

V 

rms 

( k) 

 

k 

 

nkM 

2 

v ( n) 

M 

(1) 

During the occurrence of a disturbance say a voltage sag, the rms value drops below the nominal value. The 

drop is proportional to the level of sag. Similarly, during a voltage swell ,the rms value exceeds the nominal rms 

value by an amount proportional to the level of swell. If the rms value is calculated cumulatively, after the 

recovery of a sag or swell it takes a few cycles to come back to its nominal value. Thus there is a need to reset 

the rms calculation algorithm after the occurrence of sag or swell. The above problem can be overcome by 

calculating the rms value over a moving window encompassing a fixed number of samples M, as explained by 

the following equations. 

. (2) 

Then, 

). (3) 

The set of squared values of the samples obtained are updated by considering the latest sample as the last 

sample and discarding the oldest one.Let ,indicate the rms values of the voltage signal at any 

sampling instant k evaluated as , 

(4) 

The rms values are found out and updated every sample time.. Thus the window and hence rms values are 

refreshed after every sample. The rms values at corresponding positions of two consecutive cycles are 

compared. is compared in magnitude with the value as shown in the equation below. Let 

the difference be 

. .Then, (5) 

If the above difference is within a predetermined tolerance band the state of the system is declared as normal. 

On the other hand a trigger signal is generated when the difference is greater than a predetermined tolerance. If 

this value is >10%, then it is concluded that the voltage disturbance is a swell. If the above value is


Figure.1.Input signal with Sags and Swells for test of the algorithm 

Figure.2.RMS plot obtained from using S Function 

Figure.3.RMS plot obtained from using Matlab Code Function . 

Figure.2 and Figure.3 shows the RMS variation plot obtained for the signal using the S Function and Matlab code 

Function for the detection algorithm. There is no appreciable variations observed in the magnitude of the rms 

values evaluated using the algorithm by the two functions . However, the variation in the rms values seem to be 

evaluated faster using S Functions as seen in Figure.2 as when compared to that shown using Matlab Code 

Functions in Figure. 3. 


35 | Page


Figure.4.Percentage change in RMS plot using S Functions 

Figures 4 and 5 show the percentage variation in the rms value evaluated for the signal shown in Figure.1 , using 

the Matlab Code Function and S Function for the detection algorithm. The results shown in Figures 6 and 7 show 

the trigger signal generated in response to the short duration voltage variations in the signal shown in 

Figure.1.From the values of time indicated in the Figures 6 and 7 of the trigger signal generated in response to 

the detection of sags and swells, it is clearly seen that, the detection algorithm implemented using S function in 

Matlab is simulated faster in operation than using Matlab code function. 

Figure.5. Percentage change in RMS plot using Matlab-code Function 

Figure.6.Trigger generated in response to detection of sag using Matlab-code Function 


36 | Page


Figure.7. Trigger signal generated in response to sag detection using S Functions 

X. CONCLUSION 

The results obtained which are tabulated in the TABLE clearly distinguish the effectiveness of S 

function in quick disturbance detection when compared to use of Matlab embedded function. In situations where 

the algorithm is deployed on digital signal processing chips or other embedded processors this point is very 

crucial and useful. 

TABLE 

SAG 

SAG 

SWELL SWELL RECOVERY 

OCCURANCE RECOVERY OCCURANCE 

ACTUAL TIME 100ms 200ms 300ms 400ms 

EMBEDDED 104.7ms 202.4ms 303.9ms 405.5msc 

FUNCTION 

S-FUNCTION 100.6ms 200.4ms 300.4ms 400.5ms 

ACKNOWLEDGMENT 

The authors acknowledge the contributions of Vittal. R to this work. 

REFERENCES 

[1]. ”SIMULINK 7”, Writing S Functions by Math Works,www.mathworks.com. 

[2] .” A Simple Method For Real-Time Detection Of Voltage Sags and Swells in Practical Loads”, P.Meena,K.Uma Rao,Ravishankar 

Deekshit,EPE Journal 2011,vol.21,No.3,pp,1-8. 


37 | Page




Microcontroller Based Reprogrammable Digital Door Lock 

Security System by Using Keypad & GSM/CDMA Technology 

Mohammad Amanullah 

(Lecturer, Department of Computer Science and Engineering, International Islamic University Chittagong. 

Bangladesh. 

Abstract: Now a day’s Security has been a prime concern in the home or office management. Digital door lock 

security system provides security and safety to house or office owners, belongings, assets from being damaged 

by external agent or undesired strangers. We have used a new technology, incoming number verification system 

which gives more protection for controlling & security system. As Conventional security system does not use 

any password, there is a chance to hack or break the system. In this regard we used a desire mobile number 

without verification which doesn’t allow the door to be opend.This system is composed of the microcontroller 

based by using matrix keypad & GSM/CDMA network. The microcontroller based digital door lock security 

system is an access control system that allows only authorized persons to access restricted area. The password 

is stored in PROM so that we can change it any time. The system has a matrix keypad .When anyone enter the 

code in the matrix keypad, microcontroller verify the codes. If that code is correct the device will operate and 

the door will be open. But if someone enter wrong code a red signal will be shown which means that the entered 

code is wrong.GSM/CDMA module can be used to operate the device, when anyone make a call from his mobile 

the receiving device which is set in main circuitry will receive the call. If the call is from desired number then 

operate the device and the door will be unlocked. An IPS circuit can be used for giving backup in case of 

emergency when there is a power failure. 

Keywords: DTMF encoder and decoder, Global System for Mobile Communication, Micro-Controller, Mobile 

phone, and Matrix Keypad. 


Tones generated from DTMF keypad can identify what unit we want to control, as well as which 

unique function we want to perform. A standard 4*4 matrix keyboard can be used support either DP or DTMF 

modes.DTMF encoder technologies does not require any radiation or any laser beam, not harmful, no limitation 

of range. It can be used from any distance using a simple telephone line or mobile phone. The UM91214B is a 

single chip, silicon gate. It provides dialing pulse (DP). IC UM91214B is consists of telephone set which is 

present in the remote place (Be your workspace) signal are sent through this telephone or mobile. For 

GSM/CDMA based controlling system, press a button in the telephone set keypad, a connection is made that 

generates a resultant signal of two tones at the same time. These two tones are taken from row frequency and 

column frequency. The resultant frequency signal is called “Duel Tone Multiple Frequency “These tone are 

identical and Unique.MT-8870 operating function include a band split filter that separates the high and low 

tones of the received pair, and a digital decoder that verifies both the frequency and duration of the received 

tones before passing the resulting 4-bit code to the output bus. 


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Microcontroller Based Reprogrammable Digital Door Lock Security System By Using Keypad & 

II. System Architecture & Operation: 

Fig 1. Shows the block diagram of the system. 

In the above fig1.shows block diagram of the system keypad are a part of human machine interface where 

human interaction or human input is needed and play an important role in a small embedded system. A digital 

encoder is a device that converts tone signal into a sequence of digital pulse. By counting a single bit or by 

decoding a set of bits, the pulse can be converted to relative or absolute pulse can be converted to relative or 

absolute position measurement.DTMF decoder detects the dial tone from a cell phone and decodes the keypad 

pressed on the remote cell phone. Microcontroller units are used for special or fixed type operation. 

Microcontrollers are used in automatically controlled products and devices, such as remote control, appliances 

etc.Relay interfacing unit interface between the loads and controlling circuit. A relay is a protective device 

driven from controlling circuit directly.LED unit indicates the “ON” “OFF” position of the connected load. If 

LED is turn ON, then corresponding load is ON. When LED is OFF then corresponding load is OFF.DOOR 

have been used as LOAD. 

III. Design of System Hardware 

System hardware designing composed of ENCODER, DECODER and MICROCONTROLLER. These 

are consists of matrix keypad, IC-UM91214B, IC-(MT8870D), IC-(PIC-16F628A), Zener diode, LED, Resistor, 

Capacitor, Relay. Microcontroller verifies the codes. Encoder is a device that converts tone signal into sequence 

of digital pulse. Decoder detects the dial tone from a telephone line and decodes the keypad pressed on the 

remote telephone. Fig 2. Is the circuit diagram of digital door lock security system and Fig 3. Shows practical 

implementation. 


39 | Page


Fig 2. Circuit diagram of Digital Door lock security system. 

Fig 3. shows the practrical implementation of the circuit. 

IV. Selection Of MICROCONTROLLER: 

Microcontroller is special types of processor which we used for special or fixed type operation. A 

Microcontroller is a small computer on a signal integrated circuit containing a processor core, memory and 

programmable input/output peripherals. The main function for PIC16F628A microcontroller which specify the 

ON and OFF state of the switches. The program for the microcontroller is designed in such a way that when we 

make a call from our transmitting device, it would be automatically received by Decoder circuit and it will offer 

a password code for security purpose. After verifying the password code it will give the access to operate the 

circuit. 

V. Working of IC Mt8870: 

The MT-8870 is a full DTMF receiver that integrates both band split filter and decoder function into a 

single 18-pin DIP. Its filter section uses switched capacitor technology for both the high and low group filters 

and for dial tone rejection. Its decoder uses digital counting techniques to detector and decodes all 16 DTMF 

tone pairs into a 4-bit code. External component count is minimized by provision of an on-chip differential input 

amplifier clock generator and latched tri-state interface bus.MT-8870 operating functions include a band split 

filter that separates the high and low tones of the received pair, and a digital decoder that verifies both the 

frequency and duration of the received tones before passing the resulting 4-bit code to the output bus. 


40 | Page


VI. Working of IC Um91214b: 

This unit consists of telephone set which is present in the remote place. This may be workspace (office/ 

school) phone or mobile phone or a phone in PCO. Signals are sent through this telephone. It uses DTMF 

encoder integrated circuit, chip UM91214B.This IC produces DTMF signals. It contains four row frequencies & 

three column frequencies. The pins of the IC91214B from 12 to 14 produces high frequency column group and 

pins from 15 to 18 produces the low frequency row group. By pressing any key in the keyboard corresponding 

DTMF signal is available in its output pin at pin no 7.For producing the appropriate signals it is necessary that a 

crystal oscillator of 3.58MHz is connected across its pins 3 & 4 so that it makes a part of its internal oscillator. 

This encoder IC requires a voltage of 3V.For that IC is wired around 4.5 battery and 3V backup V CC for this IC 

is supplied by using 3.2V zener diode. By pressing the number 5 in the keypad the output tone is produced 

which is the resulting of addition of two frequencies at pin no 13 & 16 of the IC and respective tone which 

represents number „5‟ in keypad is produced at pin no 7 of the IC (This signal is sent to the local control system 

through telephone line via exchange). 

VII. Keypad Matrix: 

Password is given in our system by using keypad. Keypad may be similar as telephone set‟s keypad. 

Function of this keypad is also same as the telephone. When you press buttons on the keypad, a connection is 

made that generates two tones at the same time. A “Row” tone and a “column” tone. These two tones identify 

the key you pressed to any equipment you are controlling. If the keypad is on your phone, the telephone 

company‟s “central office “equipment knows what number you are dialing by these tones, and will switch your 

call accordingly. If you are using a DTMF keypad to remotely control equipment, the tones can identify what 

unit you want to control, as well as which unique function you want it to perform. When you press the digit 1 on 

the keypad, you generate the tones 1209 Hz and 697 Hz. Pressing the digit 2 will generate the tones 1336 Hz 

and 697 Hz. Sure, the tone 697 is the same for both digits, but it takes two tones to make a digit and the 

decoding equipment knows the difference between the 1209 Hz that would complete the digit 1, and a1336 Hz 

that completes a digit 2.There are many methods but the basic logic is same . 

VIII. GSM/CDMA BASED CONTROLLING SYSTEM 

If you press a button in the telephone set keypad, a connection is made that generates a resultant signal 

of two tones at the same time. These two tones are taken from a row frequency and a column frequency. The 

resultant frequency signal is called “DTMF”. In GSM, DTMF signal is discretized.These tones are identical and 

unique. A DTMF signal is the algebraic sum of two different audio frequencies, and can be expressed as 

follows: 

F(t)=A₀ Sin(2* *f a *f b *t)+B₀ Sin(2*∏*f a *f b *t)………>(1) 

Where f a and f b are two different frequencies A and B as their peak amplitudes. Each of the low and high 

frequency groups comprise four frequencies from the various keys present on the telephone keypad. Two 

different frequencies, one from the high frequency group and another from the low frequency group are used to 

produce a DTMF signal to represent the pressed key. The amplitude of the two sine waves should be such that 

(0.7


Steering flag(ESt). Any subsequent loss of signal condition will cause ESt to fall. Before a decoded tone pair is 

registered, the receiver checks for valid signal duration( referred to as character recognition-condition) this 

check is performed by an external RC time constant driven by ESt. a short delay to allow the output latch to 

settle, the delayed steering output flag(StD) foes high, signaling that a received tone pair has been registered. 

The contents of the output latch are made available of the 4-bit output bus by raising the three state control 

input(OE) to logic high. Inhibit mode is enabled by a logic high input to pin 5(INH). It inhibits the detection of 

1633 Hz. 

The output code will remain the same as the previous detected code. On the MT-8870 models, this pin is tied to 

ground (logic low) 

The input arrangement of the MT-8870 provides a differential input operational amplifier as well as a bias 

source (VREF) to bias the inputs at mid-rail. Provision is made for connection of a feedback resistor to the opamp 

output (GS) for gain adjustment. 

X. GSM/CDMA Network based OPERATION: 

Digital Door Lock security system can be operated in two ways. One is by using matrix keypad and 

another one is by using GSM/CDMA network. A DTMF circuit is employed which is connected to a mobile 

phone as a receiving device. For different keys of the mobile or telephone DTMF decoder decodes multiple 

frequencies which will be further used to control the household or Industrial Appliance. A program is written for 

PIC16F628A microcontroller which specify the ON and OFF state of the switches. The microcontroller program 

is loaded in the PIC16F628A microcontroller using a loader. An IPS circuit can be used for giving back up in 

case of power failure. 

And our mobile or telephone is the transmitting device of this experiment. The program for the 

microcontroller is so designed that when we make a call from our transmitting device, it would be received by 

decoder circuit and it will offer a pass code barrier for security purposes. After verifying the pass code it will 

give the access to operate the circuit. 

XI. Conclusion And Further Recommendations 

This paper presents one solution for user friendly, easily maintained, lower power consumption, less 

expensive remote door lock system. The system is based on matrix keypad and GSM/CDMA technology. In this 

project we have used a new technology incoming number verification system for controlling and security 

system. We used a desired mobile number without verification which does not allow the door to be opened. 

Some technologies are commercially available which allow remote home appliance controlling through internet 

which is undoubtedly emerging. But it lacks the true sense of real mobility. In search of a true remote and 

adequately secure solution to be really effective and realizable, mobile telephony is better than any other 

solutions. Of late, the system can also be the combination of hardware and software and Artificial intelligence 

based Door lock security system design on the future development needs. The system also can be used in 

hospitals, libraries, parks and museums, such as urgent security and remote observation of the site for the 

protection purpose from threat of damage and destruction. 

References 

[1] Syam Krishna, J. Ravindra, Design and Implementation of Remote Home Security System Based on WSNS and GSM Technology, 

IJESAT, Vol. 2, Special issue-1,PP.139-142, January-February, 2012. 

[2] Design and Implementation of Pyroelectric Infrared Sensor Based Security System Using Microcontroller, Proceeding of the 2011 

IEEE Students‟ Technology Symposium 14-16 January, 2011, IIT Kharagpur. 

[3] Automated advanced industrial and home security using GSM and FPGA, Department of Electronics and Communication Engineering 

BV.CEngineering college, Odalarevu, Amalapuram,India. 

[4] AT Commands Set for Nokia GSM and WCDMA products, version 1.2, July 2005, available. 

[5] Ren Fengyuan, Huang Haining, Lin Chuang, “Wireless sensor network”, Journal of Software Vol. 14, No. 7, PP.1282-1291, March, 

2003 (in Chinese). 

[6] http://www.scribd.com/doc/27053839/activating-an-electrical-device-via-dtmf-telephone 

[7] http://www.quasarelectronics.com/3075-pic-microcontroller-traine-with-5-function.htm 

[8] http://www.electro-tech-online.com/microcontrollers/18814-dtmf-tone-pic16f84.html 

[9] http://www.embedds.com/-software-based-dtmf-remote-control 

[10] http://www.electronics-lab.com/blog/?=microcontroller&paged=43 

[11] http://electrofriends.com/projects/basis-electronics/device-control-using-telephone 


42 | Page




Optimal Capacitor Placement for Loss Reduction in Radial 

Distribution Feeder 

Om Prakash Mahela 1 , Sheesh Ram Ola 2 Lalit Goyal 3 

1 (Graduate Student Member IEEE & Junior Engineer, RRVPNL, Jaipur, India) 

2 (Director Professional Group Institute, Jaipur, India) 

3 (Junior Engineer, Rajasthan Rajya Vidhyut Prasaran Nigam Ltd. Jaipur, India) 

Abstract : A distribution system is an interface between the bulk power transmission system and the consumer. 

Among these systems, radial distribution system is popular because of low cost and simple design. In radial 

distribution feeders, the voltage at buses reduces and loss increases as moved away from the substation due to 

insufficient amount of reactive power. The reactive power requirement is provided by the shunt capacitor banks. 

The most important benefit of capacitor placement is loss reduction, voltage profile improvement, increment of 

power factor and freeing up the power system capacity. Optimal capacitor placement in distribution systems has 

been studied for a long time. It is an optimization problem which has an objective to define the optimal sizes and 

allocations of capacitors to be installed. This paper presents an approach for optimal capacitor banks 

placement in radial distribution feeders for loss reducction. 

Keywords - capacitor banks, distribution system, optimal capacitor placement, radial distribution feeder, 

reactive power, loss reduction. 


The increase in power demand and high load density makes the operation of power system 

complicated. To provide more capacity margin for the substation to meet load demand, system loss 

minimization and voltage profile improvement techniques are employed [1]. An important method of 

controlling bus voltage is by placement of shunt capacitor banks at the buses at both transmission and 

distribution levels, along lines or at substations and loads. Essentially capacitors are a means of supplying VARs 

at the point of installation [2]. HT shunt capacitor banks provide the fixed reactive compensation in the network 

[3]. The purpose of capacitors is to minimize the power and energy losses and to maintain better voltage 

regulation for load buses and to improve system security. The amount of compensation provided with the 

capacitors that are placed in the distribution network depends upon the location, size and type of capacitors 

placed in the system [4]. 

The problem of optimal reactive power dispatch is directly concerned not only with service quality and 

reliability of supply, but also with economy and security of the power system. Therefore, the power system 

reactive power optimization problem result directly influences the power system stability and power quality [5]. 

A large variety of research work has been done on capacitor placement problem in the past. Om Prakash Mahela 

et al. [6] presented different techniques of capacitor placement in transmission and distribution system to reduce 

line losses and voltage stability enhancement. References [7]-[9] have considered optimal capacitor placement 

in networks using fuzzy logic, [10]-[11] have considered Genetic Algorithm, [12] has considered successive 

quadratic programming method, [13] has considered the tabu search, [14] has considered the Game Theory, 

[15]-[16] have considered Ant Colony Optimization and [17] has considered Body Immune Algorithm for 

optimal Placement of Capacitors. 

In this paper, a method is proposed to search for optimal HT shunt capacitor placement in radial 

distribution feeder. The objective function is to reduce the power loss in the feeder. The constraint is voltage 

limits. The proposed method is tested on the 9-bus IEEE system using MATLAB for optimum capacitor places 

and sizes. The simulation results show a considerable reduction in active power losses in the radial distribution 

feeder under study on the placement of capacitors. The active power losses are calculated for different 

arrangement and sizing of capacitors. 

II. OPTIMAL CAPACITOR PLACEMENT AND SIZING PROBLEM FORMULATION 

The power flow evaluation includes the calculation of bus voltages and line flows of a network. 

Associated with each bus, there are four quantities to be determined: the real power, the reactive power, and the 

voltage magnitude and phase angle. Fig. 1 shows the single line diagram of 9-bus IEEE system. 


43 | Page

Optimal Capacitor Placement for Loss Reduction in Radial Distribution Feeder 

1 2 3 4 5 6 7 8 9 

Fig. 1. IEEE 9-bus system 

The complex power at the i th bus is given by the relation 

P i − jQ i = V ∗ i I i (1) 

Where 

P i : Load active power 

Q i : Load reactive power 

V i : Voltage at i th bus 

I i : Load current at i th bus 

The bus voltage and line losses can be calculated by the Gauss-Seidel iterative method employing the following 

formula [18]: 

m 

(k+1) 1 P i − jQ i 

V i = − Y 

Y ∗(k) in V n 

(2) 

ii V i n=1 

n≠i 

Where 

(k) 

V i : Voltage of bus i at the k th iteration 

P i , Q i : Bus active and reactive power of bus i 

Y im = y i,m for i ≠ m 

and Y ii = y i,m−1 + y i,m+1 + y ci for i = m 

The power loss in the line section between buses i and i+1, at power frequency can be computed by: 

P loss (i,i+1) = R i,i+1 V i+1 − V i . y 2 i,i+1 (3) 

Where 

1 

y i,i+1 = 

: Admittance of the line section between buses i and i+1. 

R i,i+1 +X i,i+1 

R i,i+1 : Resistance of the line connecting bus i and i+1. 

X i,i+1 : Reactance of the line connecting bus i and i+1. 

The voltage magnitude at each bus must be maintained within its limits and is expressed as: 

V min < V i < V max (4) 

Where V i is voltage magnitude of i th bus. V min is bus minimum voltage limit. V max is bus maximum 

voltage limit. The maximum and minimum voltages limits in the suggested model used are the voltage limits 

specified by the Indian Electricity Grid Code as given in table-1. 

TABLE 1 

MAXIMUM AND MINIMUM VOLTAGE LEVEL AS PER IEGC* 

Voltage-(KV rms) 

Nominal Maximum Minimum 

765 800 728 

400 420 380 

220 245 198 

132 145 122 

110 121 99 

66 72 60 

33 36 30 

*Source L-1/18/2010-CERC [19]. 


44 | Page


The purpose of placing compensating capacitors is to obtain the lower total power loss and bring the 

bus voltages within their specified values. The total power loss is given by the relation: 

P loss = 

mn 

P loss (i,i+1) 

i=0 

(5) 

III. OBJECTIVE FUNCTION FORMULATION 

The three-phase system is considered as balanced and loads are assumed as time invariant. 

Mathematically, the objective function of the problem is minimizing the loss and voltage deviation. This 

function is: 

Where 

m 

F = W 1 × P loss + W 2 max 0, V min − V i 2 + max 0, V i − V max 2 

i=1 

W 1 : Objective function coefficient for power loss 

W 2 : Objective function coefficient for voltage deviation. 

P loss : Total loss in transmission system. 

V min : Minimum permissible bus voltage. 

V max : Maximum permissible bus voltage 

IV. PROPOSED COMPUTATIONAL ALGORITHM 

The capacitor placement and sizing is provided by calculation of objective function. The simulation has 

been done on IEEE 9-bus system shown in Fig. 1. In the first case, power flow is calculated without capacitor 

placement. In the other cases, the power flow is calculated with capacitor placed at different locations. The 

objective function is calculated in each case, if this function has the tendency of convergence then capacitors are 

again placed and process is repeated and if there is no tendency of convergence then location and size of 

capacitors is suggested. The algorithm used for the capacitor placement in this paper is shown in Fig. 2. 

(6) 

Fig. 2. Flow Chart of Proposed Algorithm for Capacitor placement in Radial Distribution System 


45 | Page


V. SIMULATION RESULTS AND DISCUSSION 

The optimal location and sizing is provided by the objective function. The simulation using MATLAB 

is carried out on IEEE 9-bus system shown in Fig. 1. The steps of algorithm shown in Fig. 2 are used. The line 

data set and network buses data set for the 9-bus IEEE system as shown in Table-2, and Table-3 respectively are 

used [20]. 

TABLE 2 

THE 9-BUS IEEE NETWORK LINE DATA SET 

Sending End Bus Receiving End Bus R (ohm) X (ohm) 

0 1 0.1233 0.4127 

1 2 0.0140 0.6050 

2 3 0.7463 1.2050 

3 4 0.6984 0.6084 

4 5 1.9831 1.7276 

5 6 0.9053 0.7886 

6 7 2.0552 1.1640 

7 8 4.7953 2.7160 

8 9 5.3434 3.0264 

TABLE 3 

THE 9-BUS IEEE NETWORK BUSES DATA SET 

Bus No. Active Power (P) in KW Reactive Power (Q) in KVAR 

1 1840 460 

2 980 340 

3 1790 446 

4 1598 1840 

5 1610 600 

6 780 110 

7 1150 60 

8 980 130 

9 1640 200 

For simulation purposes different cases have been considered. In first case, power flow calculations 

have been conducted on the network without capacitors. In second and subsequent cases, power flow 

calculations have been conducted on the network with capacitors of different ratings installed on the different 

buses. The five different cases with capacitors of different ratings placed at different buses of the radial feeder 

are studied. The active power losses in the feeder without capacitor placement for first case and with capacitor 

placement for subsequent cases are shown in Table. 4. The percentage power losses in the feeder in different 

cases of study are also shown in the Table. 4. 

TABLE 4 

POWER FLOW RESULTS OF STUDY WITH AND WITHOUT CAPACITORS 

Proposed 

Cases 

Active Power 

Losses (KW) 

1 1821.75 14.73 

2 939.41 07.59 

3 807.72 06.53 

4 654.60 05.26 

5 550.62 04.45 

6 397.06 03.21 

Active Power 

Losses (%) 

The size of capacitors at different bus locations in different cases of study are shown in Table. 5. In 

first case capacitors are not installed at any bus. The sixth case is the result of optimal capacitor placement at 

different bus locations in the proposed study with optimal capacitor sizing in the IEEE 9-bus radial distribution 

feeder. 


46 | Page

Bus 

No. 


TABLE 5 

CAPACITOR SIZES AT DIFFERENT BUS LOCATIONS IN DIFFERENT CASES OF STUDY 

Case-1 

(Without 

Capacitors) 

Case-2 

(Capacitors 

in KVAR) 

Case-3 

(Capacitor 

in KVAR) 

Case-4 

(Capacitors 

in KVAR) 

Case-5 

(Capacitors 

in KVAR) 

Case-6 (Optimal 

Capacitor in 

KVAR) 

1 0 100 40 60 80 80 

2 0 100 50 50 20 30 

3 0 100 50 50 30 30 

4 0 500 1600 1450 1400 1350 

5 0 100 100 100 80 90 

6 0 100 50 50 40 50 

7 0 50 0 20 0 0 

8 0 100 50 60 10 0 

9 0 100 100 120 50 40 

We conclude from the table (4) that the amounts of active power losses have been reduced when we 

place some capacitors at appropriate buses in the network. The voltage profile also improves with the placement 

of capacitors. The optimal sizes of capacitors for minimum active power losses and the minimum voltage 

deviation from the systems values are obtained in case-6. The suggested optimal sizing of capacitor placement 

in the network at different bus locations is shown in Table. 5 as case-6 with optimal capacitors.. 

VI. CONCLUSION 

The presented results in this paper have shown that the power loss in radial distribution feeder reduces 

significantly on the placement of capacitors of proper size at appropriate places. The power losses in the feeder 

were 14.73% without any capacitors in the network. The losses have reduced to 3.21% after optimal placement 

of capacitors. The optimal placement of capacitors in the radial distribution feeder under study has resulted in 

saving of 11.52% power. 

REFERENCES 

[1] Forough Mahmood Ianfard, Hossein Askarian Abyaneh, and Hamid Reza Salehi, “Optimal capacitor placement for loss reduction,” 

Modern Electric Power Systems, MEPS-10, Wroclaw, Poland, 2010, Paper 11.3. 

[2] Anwar S.Siddiqui, and Md. Farrukh Rahman, “Optimal capacitor placement to reduce losses in distribution systems,” WSEAS 

Transactions on Power Systems, Vol. 7, No. 1, January 2012, pp. 12-17. 

[3] Om Prakash Mahela, and Sheesh Ram Ola, “Comparison of HT shunt capacitors and SVC for active and reactive power flow 

control in transmission line,” International Journal of Electrical and Electronics Engineering, Vo. 2, No. 1, Feb-2013, pp 49-58. 

[4] S.Neelima, and P.S. Subramanyam, “Optimal capacitors placement in distribution networks using genetic algorithm: A dimension 

reducing approach,” Journal of Theoretical and Applied Information Technology, Vol. 30, No. 1, August 2011, pp. 28-34. 

[5] A.H.Mantawy, and M.S.Al-Ghamdi, “A new reactive power optimization algorithm,” Proceedings of IEEE Bologna Power Tech 

Conference, Bologna, Italy, June 23-26,2003. 

[6] Om Prakash Mahela, Devendra Mittal, and Lalit Goyal, “Optimal capacitor placement techniques in transmission and distribution 

networks to reduce line losses and voltage stability enhancement: A review,” IOSR Journal of Electrical and Electronics 

Engineering, Vol. 3, No. 4, Nov-Dec 2012, pp. 01-08. 

[7] S.K. Bhattacharya, and S.K. Goswami, “Improved Fuzzy based capacitor placement method for radial distribution system,” IEEE 

Transaction on Power Apparatus and Systems, Vol. 108, No. 4, April 2008, pp. 741-744. 

[8] H.N.Ng., N.M.A. Salam, and Y. Chikhani, “Capacitor allocation by approximate reasoning fuzzy capacitor placement,” IEEE 

Transactions on Power Delivery, Vol. 15, No. 1, January 2000, pp. 393-398. 

[9] S.M. Khana, A. Rathina Grace Monica, and S.Mary Raja Slochanal, “Fuzzy logic based optimal capacitor placement on radial 

distribution feeders,” IEEE Transaction on Power Apparatus and Systems, Vol. 100, 2007, pp. 1105-1118. 

[10] Kenji Iba, “Reactive Power Optimization by Genetic Algorithm,” IEEE Transactions on Power Systems, Vol. 9, No. 2, May 1994, 

pp. 685-692. 

[11] L. Furong, J.Pilgrim, C.Dabeedin, A.Cheebo, and R.Aggarwal, “Genetic algorithms for optimal reactive power compensation on 

the national grid system,” IEEE transactions on Power Systems, Vol. 20, No.1, 2005, pp. 493-500. 

[12] N. Gridinin, “Reactive power optimization using successive quadratic programming method,” IEEE transactions on Power Systems, 

Vol. 13, No.4, November 1998, pp. 1219-1225. 

[13] H.Mori, and Y.Ogita, “Parallel tabu search for capacitor placement in radial distribution systems,” Proceedings IEEE Power 

Engineering Society Winter Meeting, Vol. 4, 2000, pp. 2334-2339. 

[14] M.H.Sadeghi, A. Darabi, H. Yassami, M. Owladi, and A. Moeini, “Feasible method for optimal capacitor placement in a distributed 

system by using game theory,” International Journal on Technical and Physical Problems of Engineering (IJTPE), Vol. 3, No. 9, 

Dec. 2011, pp. 127-131. 

[15] Reza Sirjani, and Badiossadat Hassanpour, “A new ant colony based method for optimal capacitor placement and sizing in 

distribution systems,” Research Journal of Applied Sciences, Engineering and Technology, Vol. 4, No. 8, April 2012. 

[16] S.Bouri, and A. Zeblah, “Ant colony optimization to shunt capacitor allocation in radial distribution systems,” Acta Electrotechnica 

et Information, Vol. 5, No. 4, 2005. 

[17] Majid Davoodi, Mohsen Davoudi, Iraj Ganjkhany, Morteza Arfand, and Ali Aref, “Analysis of capacitor placement in power 

distribution networks using body immune algorithm,” Research Journal of Applied Sciences Engineering and Technology, Vol. 4, 

No. 17, pp. 3148-3153, 2012. 


47 | Page


[18] Baghzouz, Y., and Ertem, S., “Shunt capacitor sizing for radial distribution feeders with distorted substation voltages,” IEEE 

Transactions on Power Delivery, Vol. 5, No. 2, 1990, pp. 650-657. 

[19] L-1/18/2010-CERC, “Central Electricity Regulatory Commission (Indian Electricity Grid Code) Regulations, 2010,” Central 

Electricity Regulatory Commission, New Delhi, India, 2010, pp. 33-38. 

[20] Majid Davoodi, Mohsen Davoudi, Iraj Ganjkhany, and Ali Aref, “Optimal capacitor placement in distribution networks using 

genetic algorithm,” Indian Journal of Science and Technology, Vol. 5, No. 7, July 2012, pp. 3054-3058. 

BIOGRAPHIES 

Om Prakash Mahela was born in Sabalpura (Kuchaman City) in the Rajasthan state of 

India, on April 11, 1977. He studied at Govt. College of Engineering and Technology 

(CTAE), Udaipur, and received the electrical engineering degree from Maharana Pratap 

University of Agriculture and Technology (MPUAT), Udaipur, India in 2002. He is currently 

pursuing M.Tech. (Power System) from Jagannath University, Jaipur, India. 

From 2002 to 2004, he was Assistant Professor with the RIET, Jaipur. Since 2004, 

he has been Junior Engineer-I with the Rajasthan Rajya Vidhyut Prasaran Nigam Ltd., 

Jaipur, India. His special fields of interest are Transmission and Distribution (T&D) grid 

operations, Power Electronics in Power System, Power Quality and Load Forecasting. He is an author of 17 

International Journals and Conference papers. He is a Graduate Student Member of IEEE. He is member of 

IEEE Communications Society. He is Member of IEEE Power & Energy Society. He is Reviewer of TJPRC- 

International Journal of Electrical and Electronics Engineering Research. Mr. Mahela is recipient of University 

Rank certificate from MPUAT, Udaipur, India, in 2002. 

Sheesh Ram Ola was born in Jerthi (Sikar), Rajasthan, India, on June 22, 1975. He studied 

at Govt. Engineering College, Kota, and received the electrical engineering degree from RU, 

Jaipur, in 1998. He received M.Tech.(Power System) from MNIT, Jaipur, India in 2001. 

From 2001 to 2005, he was Associate Professor and HOD Dept. of Electrical 

Engineering, RIET, Jaipur. Since 2005, he has been Director with Professional Group (PG) 

Institute, Jaipur, India. His special fields of interest are Small Electrical Machines, Power 

Electronics & Drives, Reactive power management in large grids and Electromagnetic 

Fields. He is an author of 8 International Journal and Conference Papers. He authored 2 

books titled Circuit Analysis & Synthesis and Basic Electrical Engineering. 

Lalit Goyal was born in Jaipur in the Rajasthan, India, on June 18, 1977. He studied at Govt. 

College of Engineering and Technology (CTAE), Udaipur and received the electrical 

engineering degree from Maharana Pratap University, of Agriculture and 

Technology,Udaipur, India in 2002. He is pursuing M.Tech. (Research) from Jagannath 

University,Jaipur. 

His employment experience included the Rajasthan Rajya Vidhyut Prasaran Nigam 

Ltd. His special fields of interest are Special Protection Scheme in Power System, Power 

Transients. 


48 | Page




High Efficient Solar Photo Voltaic Cell 

Swatantra Prakash Singh 

Associate Prof & HOD EEE Department Aurora’s Scientific and Technological institute Ghatkesar,RR Dist, 

Hyderarbad (A P) City:-Hyderabad, (India), PIN-501301 

Abstract: World much more concerned about the fossil fuel exhaustion,eco system damage& global heating. 

Therefore researchers should always thinks about green and eco friendly electrical power generation & 

application. Solar Photo Voltaic (PV) cell is a device which directly converts solar energy into electrical energy 

by means of photovoltaic effects. Photovoltaic cells are made of semi conductors which generate electricity 

when they absorb light. PV cells generate electricity by using the renewable energy technology which generates 

green power. 

The purpose of this research paper is two folds: 

• To bring out the latest innovations to better the performance of PV module 

• Improve the conversion efficiency. 

Basically, there two approaches to increase the efficiency of PV cells: First selecting the semi 

conductures materials required energy gap which match solar spectrum and optimize there optical & electrical 

properties; and second innovative device engineering which enables more effective charge collection as well as 

better utilization of solar spectrum through single & multi junction approaches. According to current scenario 

solar cell classified into four different efficiency regimes: Moderate efficient solar cell, High efficient solar 

cell,Very high efficient solar cell, Ultra high efficient solar cell. This paper gives latest progress in solar PV cell 

efficiency base on PV technologies. 

Key words: Renewable energy sources ,Semi conductor, solar photo voltaic cell, , PV technologies, optical, 

efficiency, innovation, green power 

I. Introduction:- 

World is much more concerned about the fosil fuel exhaustion,eco system damage and finally global 

warming .Photovoltaic cell is generate green power but it has low efficiency with high cost of material. These 

issued needs to solve in near future. By use of better material and latest innovation, conversion efficiency of 

solar cell will improve. In this research paper there are two ways to increase efficiencies of PV cells: first 

selecting the semiconductor materials with proper energy gaps to match the solar spectrum and optimizing their 

optical, electrical and structural properties and secondly innovative device engineering which enables more 

effective charge collection as well as better utilization of solar spectrum through single and multi junction 

approaches .Utilizing above theory, solar cells are classified on four selected group as per their different 

efficiencies regimes: ultra high efficiency(UHE) solar cells ,very high efficiency(VHE) solar cells, high 

efficiency(HE) solar cells, moderate efficiency(ME) solar cells. The efficiency of any electrical device is 

defined as ratio of output power to input power. To better way understand performance of any electrical device, 

efficiency should express in percentage(%).Ultra high efficient solar PV cells efficiency are more than 30% 

while moderate solar cells efficiency are less than 12%. 

Moderate Efficiency Low Cost Solar Cells: 

This type of solar cells have less efficiency and they are having very low cost. This type cells have 

efficiency less than 12%.The highest efficiency of dye sensitized photochemical solar cell is about to 11%. This 

type solar cells based on dye sensitization of nano crystalline film of TiO 2 in contacts with a non aqueous 

electrolyte. The cell is very much simple to fabricate and its colour can be tuned through visible spectrum from 

transparent to black opaque by changing the absorption characteristics of dye. Due to low cost option, this cell 

use to PV power window and photo electro-chromic windows. 

High Efficiency Solar cell: 

This type of solar cells have efficiency between 12% to 20% ( Multi crystalline& 

thin film solar cells are belong to this PV technology. They are used large scale commercial purpose. Under this 

group cells are poly crystalline silicon solar cells, Amorphous silicon thin film Solar cell ,Copper indium 

gallium Diselenide (CIGS) solar cell, Cadmium telluride thin film solar cell. Brief note on innovation & 

conversion efficiency of these cells are following:- 


49 | Page


POLY CRYTALLINE SILICON PV SOLAR CELL : 

Polly crystalline silicon cell are made from square cast ingots. These cell are less expensive due to 

manufacturing process than mono-crytalline cells. Presently cast of poly crystalline solar silicon(Mc-Si), 

accounting for nearly 50% of Si based solar cells manufactured worldwide, is a dominated PV technology. This 

solar cells have efficiency of 18.2%. Further improvement in cell efficiency to 18.6 has been achieved by 

decreasing the rear surface recombination velocity 20 m/second (or 0.02 km/second) with deeper Al alloys. 

THIN FILM SILICON PV SOLAR CELLS (CdTe, A-Si, CIGS):- 

Thin film PV is fastest growing sector of the solar cell manufacturing industry. Thin film cells are 

manufactured by applying very thin layers of semi conductor material to inexpensive material such as glass, 

plastic or metal. Thin film semi conductor materials are absorb light very easily than c-Si. It has theoretical 

possibility to achieve 17% efficiency in a 2 micro- m thick silicon if grain size is larger than 10 micro m and 

dislocation density is less than 10 cm- 2 .A 17.6 conversion efficiency for thin film silicon solar cell deposited by 

chemical vapour deposition into a highly doped, electrically inactive Si wafer has been reported by New South 

Wale University(NSWU).Doping is process by which adding some suitable trivalent or pentavalent atoms are 

added in pure semiconductors. "STAR" cell has achieved 9.8% efficiency in 3.5 micro- m poly silicon thin film. 

AMORPHOUS SILICON THIN FILM SOLAR CELLS;- 

Thin film amorphous silicon(a-Si) solar cells are commonly known as hydrogen generated amorphous(a-Si-H) 

SOLAR cells .Currently laboratory scale cell achieve conversion efficiency of 12.5% where cell manufacture 

high volume processes have efficiency ranging from 6% to 9%.The most efficient a-Si solar cells are typically 

produce by silane base glow discharge induce by RF voltage or plasma enhance chemical vapour 

deposition(PECVD) with other gases added for doping & alloy. 


50 | Page

THIN FILM COPPER INDIUM GALLIUM DISELENIDE(GIGS) SOLAR CELLS 


Copper Indium Gallium Diselenide has been able to reach to the highest efficiencies in production 13- 

20%.Recent,a record efficiency of 18.8% has been achieved in typical device structure consisting of 

glass/mo/CIGS/CdS/ZnO Fabricated by physical vapour deposition(PVD) techniques, PVD techniques are 

prefered method for high efficiency CIGS solar cell fabrication but variety of techniques can use. These 

techniques are sputtering, spray pyrolysis, close space sublimation(CSS),molecular beam epitaxy (MBE) and 

electro deposition are currently be in use. Among these techniques electro deposition technique is very popular 

and having very low cost option for fabricating. 

CADMIUM TELLURIDE THIN FILM SOLAR CELLS: 

This cells have efficiency between 10% to 16 %. Most recently, a record of 16% efficiency has been reported in 

this cell. High efficiency solar cell use a superstrate device configuration in which CdTe is deposited on the Cds 

window layer. In this cell a typical structure consist of glass/CdS/CdTe/Cu-C/Ag .In most cases, the post 

deposition heat treatment of CdTe layer in the presence of CdCl 2 essential for optimization of device 

performance. 

(3)VERY HIGH EFFICIENCY SOLAR CELL: 

Very high efficiency solar cells have efficiency more than 20%.When single cristal silicon material grown by 

the Czochralski(CZ) AND Float zone(FZ) methods show 22%& 24 respectively. Passive Emitter rear 

localized(PERL) is developed by New South Wales University(NSWU). Recent research and development team 

modified the PERL cell by random pyramid passivated emitter and rear cell(RP-PERC). RP-PERC has more 

advantage over PERL.RP-PERC has led to a new record value of 22% of efficiency for CZ-_Si. 


51 | Page


PV solar cell conversion efficiencies more than 25% have obtained on single junction cell fabricating on 

epitaxially grown GaAs on a single crystal substrate. 

ULTRAHIGH EFFIENCY III-V SOLAR CELL:- 

Ultra high efficiency solar cells have efficiency between 30% to 40%.Tandem cells structures can 

designed two ways: In first method individual cells are grown by separately and then mechanically stacked one 

above the other and in second method each cell can grown monolithically with atunnel junction interconnected. 

The tandem cell combination of GaInP 2 and GaAs theoretical efficiency of about 36%. Monolithic tandem cell 

which consist of GaInP 2 at top & GaAs at bottom give 29.5% efficiency. The efficiency of two junction tandem 

cell has reached a practical limit and any further improvement will require incorporation of third junction 

consisting of a semi conductor. The additon of a third junction involving Ge has been boost the efficiency 

further and the efficiency can be increase more than 35% if third junction can be fabricated by 1 e V material. 

II. Conclusion: 

PV solar cells efficiencies are improving by selecting appropriate semi conducters matterials and 

innovative device engineering .The three junctions ultra high silicon solar cells have more than 30 % efficiency 

which are use for space application. Remarkable progress has made in recent year in improving the conversion 

efficiencies of a number PV solar cells. 

Acknowledgment:- 

I would like to express my profound sence of appreciation and gratitude full team of IOSR 

members for publicing of my PhD research paper. I am very grateful to my guide Dr A Prasad professor in 

mechanical engineering dept JNT university Hyderabad for his precious suggestion& moral support. 

Swatantra Prakash Singh 

Refereces:- 

[1] www.quantum msp.com/en/solar energy/ acomparision of pv technology 

[2] www.nrel.gov 

[3] Technology Road map solar pv energy, IEA Publications,9rue de la federation,75739 paris cedex , October2010 

[4] SESI JOURNAL 2007 Volume 17 Nos.1&244 Cost Analysis of Solar Photovoltaics 

[5] Pernick, R. and C. Wilder (2008), Utility Solar Assessment (USA) Study: Reaching Ten Percent Solar by 

[6] 2025, Clean Edge Inc. and Co-op America 

[7] Philibert, C. (2011), Interactions of Policies for Renewable Energy and Climate, International Energy 

[8] Agency, Paris. http://www.iea.org/publications/free_new_Desc.asp?PUBS_ID=23NY. 

[9] Solar Junction (2011), Solar Junction Breaks World Record with 43.5% Efficient CPV Production Cell, 

[10] http://www.sj-solar.com/downloads/Solar_Junction_World 

[11] IOSR VOLUME 3,ISSUE:2 NOV-DEC2012: COST REDUCTION TECHNIQUES IN PV CELLS: AUTH; SWATANTRA 

PRAKASH SINGH. 

[12] www.wikipedia.org 


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A comparative analysis of UPFC as a Power Flow controller with 

applications 

Ch.Kiran Kumar, M.Sudheer Kumar, V.SriramBabu, S.Nagulmeera 

Abstract: Flexible alternating current transmission systems (FACTS) technology opens up new opportunities 

for controlling power and enhancing the usable cap-acity of present, as well as new and upgraded lines. FACTS 

technology reveals up new opportunities for controlling power and enhancing the usable capacity of present, as 

well as new and upgraded lines.This project describes the real and reactive power flow control through a 

transmission line by placing the UPFC at the sending end of an electrical power transmission system. The 

Unified Power Flow Controller (UPFC) is a second generation FACTS device which enables independent 

control of active and reactive power besides improving reliability and quality of the supply.The power flow 

control performance of the UPFC is compared with that of the other FACTS device called Static Synchronous 

Series Compensator(SSSC),TCSC,STATCOM Simulations are carried out in Matlab/Simulink environment to 

validate the performance of the UPFC.Finally, an introduction to the basic circuits of several FACTS 

controllers was provided with a focus on their system performance characteristics. In addition, some of the 

utility experience, real-world installations, and semiconductor technology development have been reviewed and 

summarized. TCSC provide reactive power control on transmission lines. In this respect, UPFC has the 

advantage over TCSC and phase shifter that it can control not only real power but also reactive power flow on 

transmission lines simultaneouslyIndex Terms - Flexible AC transmission systems (FACTS), FACTS 

Controllers, Power flow, Real and reactive power, SSSC, TCSC, Unified power flow controller (UPFC). 


The main objective of the power system operation is to match supply/demand, provide compensation 

for transmission loss, voltage and frequency regulation, reliability provision etc. The need for more efficient and 

fast responding electrical systems has given rise to innovative technologies in transmission using solid-state 

devices. These are called FACTS devices which enhance stability and increase line loadings closer to thermal 

limits.Flexible AC transmission systems (FACTS) have gained a great interest during the last few years, due to 

recent advances in power electronics. FACTS devices have been mainly used for solving various power system 

steady state control problems such as voltage regulation, power flow control, and transfer capability 

enhancement.The development of power semiconductor devices with turn-off capability (GTO, MCT) opens up 

new perspectives in the development of FACTS devices. FACTS devices are the key to produce electrical 

energy economically and environmental friendly in future.The latter approach has two inherent advantages over 

the more conventional switched capacitor- and reactor- based compensators. Firstly, the power electronics-based 

voltage sources can internally generate and absorb reactive power without the use of ac capacitors or reactors. 

Secondly, they can facilitate both reactive and real power compensation and thereby can provide independent 

control for real and reactive power flow. Its main objectives are to increase power transmission capability, 

voltage control, voltage stability enhancement and power system stability improvement. Its first concept was 

introduced by N.G.Hingorani[2] in April 19, 1988. Since then different kind of FACTS controllers have been 

recommended. FACTS controllers are based on voltage source converters and includes devices such as Static 

Var Compensators (SVC), static Synchronous Compensators (STATCOM), Thyristor Controlled Series 

Compensators (TCSC), Static Synchronous Series Compensators (SSSC) and Unified Power Flow Controllers 

(UPFC)[2].Among them UPFC is the most versatile and efficient device which was introduced in 1991. In 

UPFC, the transmitted power can be controlled by changing three parameters namely transmission magnitude 

voltage, impedence and phase angle. 

II. Unified Power Flow Controller 

Combining the STATCOM and the SSSC into a single device with a common control system 

represents the third generation of FACTS known as Unified Power Flow Controller (UPFC). It has the unique 

ability to control real and reactive power flow independently. The first utility demonstration of a UPFC is being 

constructed at the Inez substation of American Electric Power in 1998 [6]. Recently, 80 MVA UPFC is being 

constructed at Gangjin substation in South Korea. Table 3 shows the details of UPFCs installed in two locations. 


53 | Page

A comparative analysis of UPFC as a Power Flow controller with applications 

Figure: Basic circuit arrangement of unified power flow controller 

2.1 OPERATION OF UPFC 

Inverter 2 provides the main function of the UPFC by injecting an ac voltage Vpq with controllable 

magnitude Vpq (0 VpqVpqmax) and phase angle (0 360), at the power frequency, in series with the line 

via an insertion transformer. The injected voltage is considered essentially as a synchronous voltage source. The 

transmission line current flows through this voltage source resulting in real and reactive power exchange 

between it and the ac system.The real power exchanged at the ac terminal (i.e., at the terminal of insertion 

transformer) is converted by the inverter into dc power that appears at the dc link as positive or negative real 

power demanded. The reactive power exchanged at the ac terminal is generated internally by the inverter. 

The basic function of Inverter 1 is to supply or absorb the real power demanded by Inverter 2 at the 

common dc link [1]. This dc link power is converted back to ac and coupled to the transmission line via a shuntconnected 

transformer. Inverter 1 can also generate or absorb controllable reactive power, if it is desired, and 

there by it can provide independent shunt reactive compensation for the line. It is important to note that where as 

there is a closed “direct” path for the real power negotiated by the action of series voltage injection through 

Inverters 1 and 2 back to the line, the corresponding reactive power exchanged is supplied or absorbed locally 

by inverter 2 and therefore it does not flow through the line. Thus, inverter 1 can be operated at a unity power 

factor or be controlled to have a reactive power exchange with the line independently of the reactive power 

exchanged by the by the Inverter 2. This means there is no continuous reactive power flow through UPFC. 

Basic control functions: 

Operation of the UPFC from the standpoint of conventional power transmission based on reactive 

shunt compensation, series compensation, and phase shifting, the UPFC can fulfill thesefunctions and 

therebymeet multiple control objectives by adding the injected voltage Vpq, with appropriate amplitude and 

phase angle, to the terminal voltage Vo. Using phasor representation, 

the basic UPFC power flow control functions are illustrated in Figure.2. Terminal voltage regulation, similar to 

that obtainable with a transformer tap- changer having infinitely small steps, as shown at (a) where Vpq = V 

(boldface letters represent phasors) is injected in-phase (or anti-phase) with Vo [ 4 ]. 

Series capacitor compensation, is shown at (b) where Vpq =Vc is in quadrate with the line current I. 

Transmission angle regulation, (phase shifting) is shown at (c) where Vpq=Vo is injected with angular 

relationship with respect to Vo that achieves the desired s phase shift (advance or retard) with out any change in 

magnitude. 

Figure– Basic UPFC Control Functions 

Figure (a) – Voltage regulation 

Figure (b) – Line impedance compensation 

Figure (c) – Phase shifting 

Figure (d) – Simultaneous control of voltage, impedance, and angle 


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Multifunction power flow control, executed by simultaneous terminal voltage regulation, series capacitive 

compensation, and phase shifting, is shown at (d) where Vpq =V +Vc+Vo. 

Figure:UPFC test system 

Specifications of the system taken for testing the control strategy are: 

Xse=0.075, Rse=0.0075,Xsh=0.15, Rsh=0.01, gcap= 0.02, bcap= 2.Vr=10, Load 3p.u with p.f.0.8 (lag). All 

the above quantities are on the UPFC MVA base (33.33 MVA), which is assumed to be 1/3rd of the 

transmission line MVA base. 

The proposed control strategy was tested for the following cases: 

Case(i) :Vs=10, initially shunt control is OFF, shunt control on at T=0.04s, Pref=0, load switch on at 

t=0.08sec, at t=0.25s load throughout and subsequently shunt control OFF. 

2.2Modeling of UPFC : 

The control system described in the previous chapter was derived by assuming that the series and 

parallel converters are treated as ideal controllable voltage sources, that the values of the fundamental 

components of the line currents are locally available. The UPFC is modeled by combining the shunt and series 

branches coupled by the DC voltage control branch.Local load is added at port 1 of the UPFC. The 

Organization of UPFC modeling blocks are shown in below figure. 

Figure : Organization of UPFC modeling blocks 

III. Control Of Power Systems 

3.1Generation,Transmission,Distribution 

When discussing the creation, movement,and consumption of electrical power, it can be separated 

into three areas,which traditionally determined the way in which electric utility companies had been 

organized.These are illustrated as; 

Generation 


55 | Page


 

 

Transmission 

Distribution 

3.2Power System Constraints 

As noted in the introduction, transmission systems are being pushed closer to their stability and thermal 

limits while the focus on the quality of power delivered is greater than ever. The limitations of the transmission 

system can take many forms and may involve power transfer between areas (referred to here as transmission 

bottlenecks) or within a single area or region (referred to here as a regional constraint) and may include one or 

more of the following characteristics: 

• Voltage Stability Limit 

• Dynamic Voltage Limit 

• Steady-State Power Transfer Limit 

• Transient Stability Limit 

• Short-Circuit Current Limit 

• Power System Oscillation Damping Limit 

• Thermal Limit 

• Short-Circuit Current Limit 

Each transmission bottleneck or regional constraint may have one or more of these system-level problems. 

3.3 Controllability of Power Systems 

To illustrate that the power system only has certain 

variablesthatcanbeimpactedbycontrol,considerthebasand well-known power-angle curve,shown.Although this is 

a steady-state curve and the implementation of FACTS is primarily for dynamic issues, this illustration 

demonstrates the point that there are primarily three main variables that can be directly controlled in the power 

system[4,5] to impact its performance. These are: 

• Voltage 

• Angle 

• Impedance 

With the establishment of “what” variables can be controlled in a power system, the next question is “how” 

these variables can be controlled. The answer is presented in two parts: namely conventional equipment and 

FACTS controllers[6]. Some of the examples of Conventional Equipment For Enhancing Power System 

Control like,Transformer LTC, Switched Shunt-Capacitor and Reactor, Synchronous Condenser etc, which 

Controls voltage. Phase Shifting Transformer, and Series Capacitor which Controls angle and impedance 

respectively. Special Stability Controls, Typically focuses on voltage control but can often include direct control 

of power. Some of the examples of FACTS Controllers for Enhancing Power System Control are Thyristor 

Controlled Series Compensator (TCSC), which Controls Impedance. Static Var Compensator (SVC) which 

Controls Voltage.Static Synchronous Compensator (STATCOM) which Controls Voltage. Static Synchronous 

Series Controller (SSSC), Unified Power Flow Controller (UPFC), Inter-phase 

Power Flow Controller (IPFC) Each of the aforementioned (and similar) controllers impact voltage, impedance, 

and/or angle (& power)) Thyristor Controlled Phase Shifting Transformer (TCPST) which Controls angle. 

3.4 Benefits of Control of Power Systems 

Once power system constraints are identified and through system studies viable solutions options are 

identified, the benefits of the added power system control must be determined. The following offers a list of 

such benefits. 

Improved Power System Stability 

Increased System Reliability 

Increased System Security 

Increased Loading and More Effective Use of Transmission Corridors 

Added Flexibility in Siting New Generation 

The advantages in this list are important to achieve in the overall planning and operation of power systems. 

However, for justifying the costs of implementing added power system control and for comparing conventional 

solutions to FACTS controllers, more specific metrics of the benefits to the power system are often required. 

IV. Facts Applications 

FACTS controllers can be used for various applications to enhance power system performance. One of 

the greatest advantages of using FACTS controllers is that it can be used in all the three states of the power 

system, namely: 


56 | Page


(1) Steady state, 

(2) Transient 

(3) Post transient steady state. 

However, the conventional devices find little application during system transient or contingency condition. 

4.1STEADY STATE APPLICATION 

Various steady state applications of FACTS controllers includes voltage control (low and high), 

increase of thermal loading, post-contingency voltage control, loop flows control, reduction in short circuit level 

and power flow control. SVC and STATCOM can be used for voltage control while TCSC is more suited for 

loop flow control and for powerflow control. 

4.2CONGESTION MANAGEMENT 

Congestion management is a serious concern for Independent System Operator (ISO) in present 

deregulated electricity markets as it can arbitrarily increase the prices and hinders the free electricity trade. 

FACTS devices like TCSC, TCPAR (Thyristor Controlled Phase Angle Regulator) and UPFC can help to 

reduce congestion, smoothen locational marginal prices (LMP) and to increase the social welfare by redirecting 

power from congested interface to under utilised lines. 

4.3ATC IMPROVEMENT 

In many deregulated market, the power transaction between buyer and seller is allowed based on 

calculation of ATC. Low ATC signifies that the network is unable to accommodate further transaction and 

hence does not promote free competition. FACTS controllers like TCSC, TCPAR and UPFC can help to 

improve ATC by allowing more power transactions. 

4.4 REACTIVE POWER AND VOLTAGE CONTROL 

The use of shunt FACTS controllers like SVC and STATCOM for reactive power and voltage control 

is well known. 

4.5 LOADING MARGIN IMPROVEMENT 

Several blackouts in many part of the world occurs mainly due to voltage collapse at the 

maximumloadability point. Series and shunt compensations are generally used to increase the maximum transfer 

capabilities of power networks. The recent advancement in FACTS controllers have allowed them to be used 

more efficiently for increasing the loading margin in the system. 

4.6POWER FLOW BALANCING AND CONTROL 

FACTS controllers, especially TCSC, SSSC and UPFC, enable the load flow on parallel circuits and 

different voltage levels to be optimized and controlled, with a minimum of power wheeling, the best possible 

utilization of the lines, and a minimizing of overall system losses at the same time. 

4.7DYNAMIC APPLICATION 

Dynamic application of FACTS controllers includes transient stability improvement, oscillation damping 

(dynamic stability) and voltage stability enhancement. One of the most important capabilities expected of 

FACTS applications is to be able to reduce the impact of the primary disturbance. The impact reduction for 

contingencies can be achieved through dynamic voltage support (STATCOM), dynamic flow control (TCSC) or 

both with the use of UPFC. 

4.8 TRANSIENT STABILITY ENHANCEMENT 

Transient instability is caused by large disturbances such as tripping of a major transmission line or a 

generator and the problem can be seen from the first swing of the angle. FACTS devices can resolve the 

problem by providing fast and rapid response during the first swing to control voltage and power flow in the 

system. 

4.9OSCILLATION DAMPING 

Electromechanical oscillations have been observed in many power systems worldwide and may lead to 

partial power interruption if not controlled. Initially, power system stabilizer (PSS) is used for oscillation 

damping in power system. Now this function can be more effectively handled by proper placement and setting 

of SVC, STATCOM and TCSC. 


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4.10 DYNAMIC VOLTAGE CONTROL 

Shunt FACTS controllers like SVC and STATCOM as well as UPFC can be utilized for dynamic 

control of voltage during system contingency and save the system from voltage collapse and blackout. 

4.11 POWER SYSTEM INTERCONNECTION 

Interconnection of power systems is becoming increasingly widespread as part of power exchange 

between countries as well as regions within countries in many parts of the world. There are numerous examples 

of interconnection of remotely separated regions within one country. Such are found in the Nordic countries, 

Argentina and Brazil. In cases of long distance AC transmission, as in interconnected power systems, care has to 

be taken for safeguarding of synchronism as well as stable system voltages, particularly in conjunction with 

system faults. With series compensation, bulk AC power transmission over distances of more than 1,000 km are 

a reality today and hasbeen used in Brazil north- south interconnection. With the advent of TCSC, further 

potential as well as flexibility is added to AC power transmission. 

4.12 APPLICATION IN DEREGULATED ENVIRONMENT 

Apart from its traditional application for voltage control, power flow control and enhancing steady state 

and dynamic limits, FACTS controllers are finding new applications in the present deregulated environment. 

One of the applications is in controlling the “parallel flow” or “loop flow”. Loop flow results in involuntary 

reduction in transmission capacity that may belong to some other utility and hence foreclose beneficial 

transactions through that line. Utilities can also make use of FACTS controllers in their tie lines, either to shield 

it from the neighbouring effects, such as wheeling transactions or to participate in such transaction. FACTS 

devices can also be implemented to ensure the economy in operation by placing it in a suitable line such that 

least cost generators can be dispatched more. It can also be used to reduce the losses in the system. Yet, another 

application is to use FACTS to relieve the congestion in the system. FACTS devices can be strategically placed 

such that congestion cost is reduced, curtailment is decreased and price volatility due to congestion is 

minimized. 

V. Benefits And Costs 

The benefits from the use of FACTS devices are many, however, not all are tangible. Similarly, the 

cost of FACTS devices are also huge. The world second UPFC came into operation at the end of year 2004 in 

Keepco power system in Korea. It was the largest single procurement order ever placed by Keepco. From this, it 

is clear how expensive these technologies are. But, the cost has to computed against anticipated benefits. One of 

the reasons for low deployment of FACTS is because very little has been done to show their profitableness. 

FACTS devices can save the system from potential threat of system collapse, which can have very serious 

consequences on other economic sector as well. It can help to avoid the wide spread blackout. The opportunity 

cost of FACTS controllers in these situations has to taken into consideration. 

5.1ENVIRONMENTAL BENEFIT 

The construction of new transmission line has negative impact on the environment. FACTS devices 

help to distribute the electrical energy more economically through better utilization of existing installation there 

by reducing the need for additional transmission lines. For example, in Sweden, eight 400 kV systems run in 

parallel to transport electrical energy from the north to the south. Each of these transmission systems is equipped 

with FACTS. Studies have shown that four additional 400 kV transmission systems would be necessary, if 

FACTS were not utilized on the existing systems. 

5.2 INCREASED STABILITY 

Instabilities in power system are created due to long length of transmission lines, interconnected grid, 

changing system loads and line faults in the system. These instabilities results in reduced line flows or even line 

trip. FACTS devices stabilize transmission systems with increased transfer capability and reduced risk of line 

trips. 

5.3 INCREASED QUALITY OF SUPPLY 

Modern industries require high quality of electricity supply including constant voltage and frequency, 

and no supply interruptions. Voltage dips, frequency variations or the loss of supply can lead to interruptions in 

manufacturing processes with high economic losses. FACTS devices can help to provide the required quality of 

supply. 


58 | Page


5.4 FLEXIBILITY AND UPTIME 

Unlike new overhead transmission lines that take several years to construct, FACTS installation 

requires only 12 to 18 months. FACTS installation has the flexibility for future upgrades and requires small land 

area. 

5.5FINANCIAL BENEFIT 

Financial benefit from FACTS devices comes from the additional sales due to increased transmission 

capability, additional wheeling charges due to increased transmission capability and due to delay in investment 

of high voltage transmission lines or even new power generation facilities. Also, in a deregulated market, the 

improved stability in a power system substantially reduces the risk for forced outages, thus reducing risks of 

cost revenue and penalties from power contracts. 

5.6 REDUCED MAINTENANCE COST 

The overhead transmission lines need to be cleared from the surrounding environment (e.g. tree 

branches) from time to time. In comparison to this, the FACTS maintenance cost is very minimum. In addition, 

as the number of transmission line increases, the probability of fault occurring in a line is also high. So, by 

utilizing the transmission systems optimally with the use of FACTS, the total number of line fault is minimized, 

thus reducing the maintenance costs. 

VI. Costs 

As compared to conventional devices, FACTS controllers are very expensive. The approximate cost per 

kVar output of various conventional devices and FACTS controllers are shown in Table 4 [19]. However, the 

cost per kVar decreases for higher capacity of FACTS controllers. The total cost also depends on the size of 

fixed and controlled portion of the FACTS controllers. The FACTS equipment cost represent only half of the 

total FACTS project cost. Other costs like civil works, installation, commissioning, insurance, engineering and 

project management constitute the other half of the FACTS project cost. 

Table : Cost of conventional and FACTS controllers 

FACTS Controllers Cost (US $) 

Shunt Capacitor 

Series Capacitor 

SVC 

TCSC 

STATCOM 

UPFC Series Portions 

UPFC Shunt Portions 

8/kVar 

20/kVar 

40/ kVar controlled portions 

40/ kVar controlled portions 

50/ kVar 

50/ kVar through power 

50/ kVar controlled 

VII. Simulation results and discussion 

Notations used to represent simulated waveforms are: 

Ese = Series inverter output voltage. 

Esh = Shunt inverter output voltage. 

Eshrms= RMS value of series converter output voltage 

Eserms= RMS value of series converter output voltage 

power flow from sending end to port1 measured at port1. 

Q1=Reactive power flow from sending end to port1 measured at port1 

P2= Real power flow from port2 t= R o receiving end bus measured at port2 

Q2=Reactive power flow from port2 to receiving end measured at port2 

Psh = Real power flow from port1 to shunt converter measured at port1 

Qsh= Reactive power flow from port1 to shunt converter measured at port1 

PL =Real power flow from port1 to load measured at port1 

QL=Reactive power flow from port1 to load measured at port1. 

Pse= Real power flow from series converter to port2 measured at port2. 

Qse=Reactive power flow from series converter to port2 measured at port2. 

VDC= Voltage across DC capacitor 

V1-A=Port1phase-A voltage. 

V2-A= Port 2 phase-A voltage. 

V1rms = RMS value of port 1 voltage 


59 | Page


V2rms= RMS value of port2 voltage. 

In all the plots below X-axis represents time in seconds. 

Results of a P1eal sample simulation run using the model developed follow. 

Study Case: Vs = 1 0, load 3p.u with lagging power factor 0.8, initially shunt control is OFF, shunt control 

ON at T=0.04sec, P Ref = 0, load switch on at t=0.08sec.The plot of the simulation results shown in Figures 

below. 

Figure: Simulation result of V1 Angle 

Figure: Simulation result of V 1rms 

Figure: Simulation result of V 2 rms 

Figure:Simulation result of V2 angle 

VIII. ISSUES 

High cost and high losses, appropriate size and setting, location and procurement availability are some 

major issues with the use of FACTS controllers. Even with the long history of development, proven technology 

and long list of benefits, FACTS controllers are not yet widely deployed because of the high cost as compared to 

the conventional counterpart. 

The procurement availability of FACTS controllers is also a major issue. Market for SVC is widely 

developed and can be procured competitively. While, very limited competition exists regarding the procurement 

of TCSC and STATCOM. For the case of UPFC, it is more likely that there will be no competition at all. 

Another important concern is the losses, which increase with higher loading and FACTS devices produce more 

loss than the conventional ones. So, more effort is needed in the development of semiconductor switches that are 

fast and, at the same time, have low switching and conduction losses. Size of FACTS controllers also bears 

significance, since cost increases proportionally with the size. Similarly appropriate setting and location are 

important to obtain the desired performance. These are to be addressed during the planning stage of the FACTS 

project. As the number of FACTS controllers increases in the power system, the interactions among the 

controllers itself will be a serious concern that requires separate in-depth study. 

IX. CONCLUSION 

Finally, an introduction to the basic circuits of several FACTS controllers was provided with a focus on 

their system performance characteristics. The FACTS controllers clearly enhance power system performance, 

improve quality of supply and also provide an optimal utilization of the existing resources. It has been 

concluded that none of the existing FACTS devices namely, TCSC provide reactive power control on 

transmission lines. In this respect, UPFC has the advantage over TCSC and phase shifter that it can control not 


60 | Page


only real power but also reactive power flow on transmission lines simultaneously Future systems can be 

expected to operate at higher stress levels so the FACTS could provide means to control and alleviate stress. All 

these will hasten the broad application of the FACTS concepts and the achievement of its ultimate goal, the 

higher utilization of electric power systems. 

References 

[1] N.G. Hingorani and L. Gyugyi “Understanding FACTS concepts and technology of flexible AC transmission systems”, IEEE Press, 

New York, 2000. 

[2] L. Gyugyi, “Unified power-flow control concept for flexible ac transmission systems”, IEE Proceedings-C, Vol. 139, NO.4, pp:323-33 

I , July 1992 

[3] John J. Paserba, Fellow, IEEE, “ How FACTS Controllers Benefit FACTS AC Transmission Systems” 

[4] P. Kundur, Power System Stability and Control, McGraw- Hill Inc., 1994, pp:813-816 

[5] Yong Hua Song and Allan T Johns, Flexible ac transmission system (FACTS), IEE power and energy series, 1999. 

[6] S. Y. Ge T S Chung „Optimal active power flow incorporating power flow control needs in flexible ac transmission systems” 

[7] R. MihaliE and P. hnko, Member, D. Povh, Fellow IEEE “Improvement of transient stability using unified power flow controller‟ 

[8] R.M. Mathur, R.K. Varma, 2002, “Thyristor-based FACTS Controllers for Electrical Transmission Systems,” IEEE Press, Piscataway. 

[9] Preeti Singh, Mrs.Lini Mathew, Prof. S. Chatterji „MATLAB Based Simulation of TCSC FACTS Controller” 

[10] K.K. Sen, 1998, “SSSC – Static Synchronous Series Compensator: Theory, Modeling and Application”, IEEE Trans. on Power 

Delivery, 13(1), pp. 241-246. 

[11] SongpakitKaewniyompanit, YasunoriMitani and Kiichiro Tsuji “Optimal allocation and type selection of a power system stabilizing 

FACTS device in a multi-machine system by micro- GA” 

[12] Kannan. S, SheshaJayaram and M.M.A.Salama.(2007) „Real and Reactive Power Coordination for a Unified Power Flow 

Controller‟ IEEE Transactions on Power Systems, 2007, vol.19.No.3, pp. 1454 – 1461. 


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e-ISSN: 2278-1676, p-ISSN: 2320–3331, Volume 4, Issue 6 (Jan. - Feb. 2013), PP 62-68 


Battery Voltage Control System to Avoid Deep Charging in 

Control Battery Unit (CBU) 

Deni Permana Kurniadi 1 , Arief Budi Santiko 2 

1,2 (Research Center for Electronics and Telecommunication - Indonesian Institute of Sciencies (LIPI), LIPI – 

Campus, Sangkuriang Street, Building 20-4 th floors, Cisitu, Bandung – Indonesia 40135) 

ABSTRACT: Has done research on the voltage of the battery management system to avoid the phenomenon of 

deep charging. The phenomenon of deep charging is a situation where the over current in the process of 

charging the battery because the battery voltage is below the allowed minimum voltage levels, this course can 

shorten the life of the battery or even permanently damage the battery. To prevent this, it is a regulatory system 

that serves to regulate the use of electric current to the battery, so when battery voltage is approach the level 

minimum, so electric current flowing from the battery to the load is automatically disconnected. The working 

principle of the system is to use a comparative setting, where these systems will compare the desired voltage as 

the voltage of the signal, with the other insert voltage as a reference. When all requirements are met 

comparators, then the outcome of the comparison system will measured increase in the voltage that will make a 

switch transistor saturation. To increase the switching currents, then used a relay that placed the series between 

the collector and voltage sources. Regulatory system is designed using components easily available in the 

market, and has the same functionality as the functions contained in the Battery Control Unit (CBU) 

Keywords: deep charging, over current, comparator, voltage reference 


Battery capacity 100 Ah (ampere hour), it means when the load used for 100 Ampere, battery current 

will empty in an hour. Battery discharge level or minimum threshold level Voltage that recommended is up to 

1.75 Volt per cell. The battery wil be damaged if the voltage per cell is less than 1.75 Volt (or 10.5 Volt 

recommended for battery type 12Volt) [1]. Battery life times counted in the number of cycle, one cycle is one 

time of use (discharge condition) and charging (charge condition). Depth of discharge (DoD) is the number 

usage of Battery ampere, affect the cycle number of battery. The condition at a temperature of 25 degrees 

celcius [1]: 

Full discharge is for 100% depth of discharge with the use of approximately 100-200 cycle 

Partial is for 50% depth of discharge with the use of approximately 400-500 cycle 

Shallow discharge is for 100% depth of discharge 100% of approximately 1000 cycle atau lebih. 

Extended battery lifetime, the battery requires discharge periodic, discharge performed only abour 10 

percent of total capacity. The use of full discharge of a battery is not recommended because it will reduce of 

battery lifetime. 

Figure 1. Deep Charging Curve [2] 


62 | Page

Battery Voltage Control System to Avoid Deep Charging in Control Battery Unit (CBU) 

II. DISCUSSION AND THEORY 

Battery voltage regulator system using a operational amplifier (op-amp) are used as comparison. 

Comparison system is use a single voltage on one input will be compared with a reference voltage at the another 

input. The condition Non-Inverting input voltage is greater than Inverting Input voltage, comparator generate 

high voltage output and applies to the opposite situation [3]. 

Figure 2. A schematic drawing System 

Operating Amplifier used as comparator it becomes important to know the value transfer point will 

occur. Transfer point (threshold point or reference point) it means define as the value of the input voltage 

magnitude when the output voltage become to the condition switching state[3]. 

Figure 3. Operating Amplifier system for comparison with Symmetrical Supply[3] 18-163 

Transfer point same with Vref because when this input voltage have a value, on the other side the 

output voltage become the condition switching state. Condition Vin greater than Vre f , then output value is high 

level. Conversely, if Vin less than Vref, output value is low level. 

Dimana : 

V acu 

R 1 dan R 2 

V CC 

= Voltage Reference 

= Resistor as Voltage Divide 

= Voltage Source 

Avoid ripple from power supply and roar on Voltage Inverting Input mounted bypass capasitor to 

ground. In order to work properly, the value of main frequency this simple circuit must less than value of ripple 

frequency. The calculation for determine frequency on main circuit : 


63 | Page


Simplify the design, created a NOT simple circuit made from a single low power class A Transistor 

inserted between Op-Amp Output and input of the gate switch circuit. Thus, when the condition of OpAmp on 

low level, the Output of NOT simple circuit will be high level, as did the oposite. Measure the level Basis 

Voltage on NOT simple circuit, use the equation : 

............................................................................................... (3) 

Because the value Voltage basis-emitter (V BE ) is about 0.7 Volt for Silicon Transistor types and 0.3 

Volt for Germanium Transistor types so the values of Emitter Current (I E ) which also considered nearly equal to 

Quiet Collector Current (I CQ ), can be calculated by the following equation : 

........................................................................................... (4) 

By knowing, the quiet collector current which is idenctical Emitter Current, so the value of DC Voltage emittercollector 

can be calculated by the following equation : 

............................................................................... (5) 

For DC cut-off voltage is Vcc, so the value of DC saturated current can be calculated [3] : 

..................................................................................... (6) 

On the quiet condition or the condition when Basis Voltage equal to zero, transistor can be operates 

at a Q point on the DC load line. Meanwhile, when the condition of the Basis Voltage equal to half the Vcc 

Voltage,then the Q point operates or oscillate along AC load line. This is due to DC load resistance different 

with AC load resistance[3]. 

Basicly DC saturated point and cutoff point different with AC saturated point and cutoff point, the 

methode used to get the AC load line is summing all close looping AC voltage’s on Basis and Collector, so to 

determining value AC saturated current and AC cut-off Voltage calculated by the following equation : 

.. ........................................................................... (7) 

where : 

I C-(SAT)-AC = AC saturated current 

I CQ = DC collector current 

V CEQ = DC voltage collector-emitter 

r C = AC resistance on collector 

V CE – (CUT) = AC cut-off voltage 

............................................................................. (8) 

The switch system, used VMOS type (metal-oxide semiconductor vertical) where V in on low level or high level 

so VMOS operate as switch that can cutoff and conduct current. While the Condition of V in low level, then 

VMOS is cutoff and V out (voltage out) same with supply voltage and aplicable to the contrary [2]. Detemine 

the value of Current that flows on Load resistance (R D ), used following equation : 

(9) 

......................................................................................................... (10) 


64 | Page

where: 

I D sat 

V DD 

V DS on 

R D 


= Drain Current Satturated 

= Voltage Source 

= Voltage Drain Source 

= Drain Resistor 

III. DESIGN SYSTEM 

The first planning in this experiment ist to determine the lowest point of the battery is still safe to do 

discharge. Generally, the recomended discharge level until 1.75 Volt per cell. The battery wil be damaged if the 

voltage per cell is less than 1.75 Volt (or 10.5 Volt recomended for battery type 12Volt) [1]. It also 

recommended charging current is about 10% from batery capacity, its is to keep the battery from damage due to 

the charging current is too large (deep charge) and maintain the lifetime battery becomes longer. Recomended 

for minimum voltage is 1.75 voltX6 cell = 10.5 volt 

By known value of the source voltage is 12 Volt (nominal voltage of the battery), refference voltage is 

10.5Volt which is the recomended for minimum threshold voltage and setting the divide resistor at 10 K so the 

value of the resistance on Series Circuit (R 1 ) can be determined by the following equation : 

By known both of Divide Resistance on Inveting Input, for condition V in is greater than 10.5 Volt, so 

Output value will be high level, otherwise condition while V in is smaller than 10.5 Volt so Output value will be 

low level, with positive polarity at the both condition. Determine value of Voltage Basis on NOT circuit , 

choose 

R 1 = 100 Ω; R 2 = 100 Ω ; R E = 680 Ω ; 

R C = 470 Ω ; R L = 10 Ω ; V CC = 12 Volt 

Because the value of Emitter Current (I E ) same with Collector Current (I CQ ), then the value Voltage collectoremitter 

(V CEQ ) can be calculated: 

Determine the value of AC saturated current and AC cut-off Voltage, firstly it must be calculated the 

value of AC Thevenin Resistance that drive the basis voltage and AC load resistance which is views by collector 

on OpAmp: 


65 | Page


By calculate series resistance on gate base the result is 47 , so the value of current on gate base can 

be calcualted and the current on gate base known is 65.3 mA, this current value sufficient to drive switch circuit 

on saturated level. The condition while switch circuit on saturated level, the value of current on load circuit can 

be calcualted by knowing Voltage Drain-Source obtained from datasheet is 1.8Volt. Because the load of switch 

circuit shaped from relay coil, the value Load resistance can be obtained with doing measuring the value of 

Inductance that exist in coil. Measurement of relay coli inductance obtained the value is 2.195mH. By knowing, 

the value of the relay coil inductance, so value of inductive reactance can be calculated by frequency that used at 

the time of measurement. 

By entering all result calculation on fig.3 (OpAmp as comparision) and added a switch circuit 

combained with a single relay on Load resistance, it can be made a regulator system to cutoff short circuit 

between battery and load system while Voltage Comparator Input close to Voltage minimum level (10.5 volt). 

IV. CHARACTERIZATION AND IMPLEMENTATION 

Measurement has been done for all system by using Instrumentation LCR Meter type “Escort ELC – 

131D” to measure value of Inductance, Capacitance dan Reactance. Multimeter type “Fluke 8060A” to measure 

the value of the Voltage and Current in the circuit and Tektronix Oscilloscope type “TDS 3032” to measure the 

value of Input Voltage on switch circuit. 

Table 1. Measurement on Coil 

NO BASIC QUANTITY MEASUREABLE UNIT 

1. L 2,195 X 10 -3 H 

2. C 5,201 X 10 -9 F 

3. R 163,9 

4. Q 5,97 

By Measurement on relay coil which function as Load Resistance (R D ) measureable the value of 

Induktance, Capacitance, Resistance and magnitude of Q factor at frequency 1 KHz , as shown in table 1. 

NO 

NON-INVERTING 

VOLTAGE 

Table 2. Measurement Output Voltage Comparator 

OP-AMP OUTPUT 

1. 13.50 Volt 1.64 Volt 

2. 13.40 Volt 1.66 Volt 

4. 13.20 Volt 1.66 Volt 

5. 13.10 Volt 1.66 Volt 

6. 13.00 Volt 1.67 Volt 

3. 13.30 Volt 1.65 Volt 

7. 12.90 Volt 1.65 Volt 


66 | Page


8. 12.80 Volt 1.64 Volt 

23. 11.30 Volt 1.64 Volt 

9. 12.70 Volt 1.64 Volt 

10. 12.60 Volt 1.65 Volt 

11. 12.50 Volt 1.64 Volt 

12. 12.40 Volt 1.64 Volt 

13. 12.30 Volt 1.65 Volt 

14. 12.20 Volt 1.64 Volt 

15. 12.10 Volt 1.64 Volt 

16. 12.00 Volt 1.64 Volt 

17. 11.90 Volt 1.65 Volt 

18. 11.80 Volt 1.64 Volt 

19. 11.70 Volt 1.64 Volt 

20. 11.60 Volt 1.64 Volt 

21. 11.50 Volt 1.65 Volt 

24. 11.20 Volt 1.64 Volt 

25. 11.10 Volt 1.65 Volt 

26. 11.00 Volt 1.64 Volt 

27. 10.90 Volt 1.64 Volt 

28. 10.80 Volt 1.64 Volt 

29. 10.70 Volt 10.14 Volt 

30. 10.60 Volt 10.10 Volt 

31. 10.50 Volt 10.15 Volt 

32. 10.40 Volt 10.11 Volt 

33. 10.30 Volt 10.14 Volt 

34. 10.20 Volt 10.17 Volt 

35. 10.10 Volt 10.15 Volt 

36. 10.00 Volt 10.15 Volt 

22. 11.40 Volt 1.64 Volt 

Figure 4. Measurment Output Voltage Comparator 

Result of measurement has shown in fig.4 performed 3 times trial experiment with almost same 

result, while the value of Battery voltage at minimum level (10.5 Volt) as in the design system, then Voltage 


67 | Page


Output of comparator is 10 Volt enough to drives switch-Transistor Saturated which ultimately can drives relay 

components to break/cutoff short circuit between the Battery to the Load. 

Figure 5. Voltage Input on VMOS from Comparator Output. 

V. CONCLUSION 

From all the measurement result and performance overall system, it can be concluded that the system 

can work well and functionate as regulator Battery voltage. From the measurement shown, the output of the 

comparator will be in high level when the Input comparator having the specified minimum level. 

Acknowledgement 

This project was supported by all crew RADAR project on Research Center for Electronics and Telecommunication - 

Indonesian Institute of Sciencies (PPET-LIPI). 

References 

[1] http://www.panelsurya.com/index.php/id/batere/baterai-deep-cycle. 

[2] http://www.idea2ic.com/FUN_DOCUMENTS/Battery%20Life%20(and%20Death).pdf 

[3] A.P. Malvino, Barmawi, “Electronic Principal”, Erlangga - Jakarta, Vol.2, 3 rd Edition, 1992, Page 53- 67. 

[4] Trinidad F, Saez F, Valenciano J, "High power valve regulated lead-acid batteries for new vehicle requirements", Journal of Power 

Spurces vol.95 , 2001 , pp 24-37 

[5] Moseley P.T, "Improving the valve- regulated lead–acid battery", Journal of Power Spurces vol.88 , 2000 , pp 71-77 

[6] Electropaedia, "Battery and Energy technologies",from: http://www.mpoweruk.com/life.htm 

[7] A. F. Hollenkamp, et. al., “Effects of grid alloy on the properties of positive-plate corrosion layers in lead/acid batteries: Implications 

for premature capacity loss under repetitive deepdischarge cycling service”, Journal of Power Sources, 48 (1994), pp. 195-215. 

[8] M. Perry & T. Fuller, “A historical perspective of fuel-cell technology in the 20th Century,” Journal of the Electrochemical Society, 

V149, S59 (2002). 

[9] D. Permana dan S. Ismail, “Battery voltage Control System on Device Uninterruptible Power Supply (UPS)” Telecommunication and 

Electronic Journal PPET LIPI; No.1 Vol.8, Januari - Juni 2008 ISSN 1411-8289, Akreditasi LIPI No. 72/Akred-LIPI/P2MBI/5/2007. 

[10] D. Permana, “Design and Realization The Current Amplifier System for Ignition Gasoline Motor” Telecommunication and Electronic 

Journal PPET LIPI ; No.3, Vol.II / ISSN 1411-8289, October - November 2002, ISSN 1411-8289. 


68 | Page


e-ISSN: 2278-1676, p-ISSN: 2320–3331, Volume 4, Issue 6 (Mar. -Apr. 2013), PP 69-74 


Parametric Optimization and Analysis of Adaptive Equalization 

Algorithms for Noisy Speech Signals 

G.R. Mishra, Mudit Shukla * , O. P. Singh, Sachin Kumar, Kamal Ahmad 

Department of Electronics & Communication Engineering, Amity School of Engineering & Technology 

Amity University Uttar Pradesh, Lucknow Campus, India 

Abstract: Adaptive equalization technique plays key role in modern digital communication systems. Adaptive 

digital filters are widely used in the area of signal processing such as echo cancellation, noise cancellation, 

channel equalization and beamforming. This paper presents the performance analysis of RLS and CMA 

algorithm in presence of noisy audio signal. The analysis shows that in CMA algorithm the convergence rate is 

low as compare to RLS algorithm whereas CMA algorithm requires low computing power and relatively better 

performance. The parameters of proposed equalizer have been optimized and simulated using Simulink. 

Index Terms— CMA, Equalization, Noisy audio signal, RLS algorithms 


In the digital communication system, when the signal passes through a channel, signal gets distorted 

due to various causes. One of the most common causes is Inter symbol interference (ISI). In presence of ISI, 

receiver does not clearly understand the received samples. The linear distortion which is produced by the 

channel is minimized by the most important part of the receiver called equalizer by a process called 

equalization. Equalization is defined as process of change in the frequency of a signal in order to maintain the 

signal at the normal level [1]. If a signal is transmitted through a channel, its frequency can vary. So an equalizer 

is most essential element of a receiver system, which removes emphasized frequency from the transmitted signal 

[2]. 

If the characteristics of the channel are known than optimum setting for equalizer can be computed. But 

in the practical system the characteristics of the channel is the big problem, so adaptive equalizers are used. 

Adaptive filter can be used in the system for different purposes such as system identification, noise cancellation, 

echo cancellation and equalization. When adaptive filter theory converges with the equalizer then we get an 

adaptive equalizer. Adaptive equalizer has capability to change the coefficients of transfer function as per 

system requirement [3]. 

The adaptive equalization is of two types: trained equalization and blind equalization. 

A) Trained Equalization 

Trained equalization is based on the pseudo random sequence. Which is the random pattern of bits 

consists of ones and zeros called training sequence known both to the transmitter and receiver. In this paper we 

use two types of trained equalization algorithms named LMS and RLS. 

Least Mean Square (LMS) Algorithm: The LMS algorithm is a stochastic gradient algorithm, which means that 

the gradient of the error performance surface with respect to the free parameter vector changes randomly from 

one iteration to the next. The LMS algorithm achieves simplicity of implementation by using instantaneous 

estimates of the autocorrelation matrix of the input signal vector, and the cross-correlation vector between the 

input vector and the desired response. The LMS algorithm has two major shortcomings: slow rate of 

convergence, and sensitivity to the eigen value spread (i.e., the ratio of the largest eigen value to the smallest 

eigen value) of the correlation matrix of the input signal vector [4]. 

Recursive Least Square (RLS): The RLS algorithm utilizes continuously updated estimates of autocorrelation 

matrix of the input signal vector, and the cross-correlation vector between the input vector and the desired 

response quantities, which go back to the beginning of the adaptive process. Accordingly, the RLS algorithm 

exhibits the following properties: 

• Rate of convergence that is typically an order of magnitude faster than the LMS algorithm. 

• Rate of convergence that is invariant to the eigen value spread of the correlation matrix of the input Vector [4]. 

B) Blind Equalization 

In the blind equalization no training sequence is used. However blind equalization is capable to 

compensate amplitude and delay distortion of a communication channel. The channel equalization performed 

without help of training sequence. The term blind indicate that the equalization is performed blindly on the data 

without a reference signal. The blind equalization depends on the knowledge of signal’s structure and its 


69 | Page

Parametric Optimization and Analysis of Adaptive Equalization Algorithms for Noisy Speech Signals 

statistical properties. One of the most important advantages of the blind equalization is that no bandwidth is 

wasted by its transmission because no training sequence is used at the start up [5]. The algorithm which we use 

in this paper of blind equalization is Godard or constant modulus algorithm (CMA). 

Godard or Constant Modulus Algorithm (CMA): Godard developed algorithm for the complex valued signal is 

the most popular algorithm for the blind equalization of QAM signal is called the constant modulus algorithm 

[6]. CMA tries to minimize the constant modulus cost function J CM. Consider a input data symbol {a k }. The 

squared magnitude of received sample z(n) and Godard dispersion constant R 2 depends only on the {a k }. CMA 

minimizes the difference between these two by adjusting the weights of the equalizer. This gives the value of 

J CM . 

J CM =E [ (abs (z(n)) 2 -R 2 ) 2 ] 

Where z(n) is the equalizer output at time n. The equalizer coefficient update equalization in CMA uses a 

gradient descent to minimize J CM. The equation is given by Godard as- 

C (n+1) =C (n)-µ y(n)z(n) [(abs(z(n)) 2 -R 2 )] 

For determining the value of R 2 

R 2 =E [a(n) 4 ]/ E[abs(a(n)) 2 ] 

Where a(n) is the signal to be transmitted and E[] is the exception over all possible transmitted data sequence. In 

this paper we use three adaptive algorithms. Out of these three algorithms, two algorithms are based on trained 

equalization LMS and RLS. The LMS algorithm is taken as a reference algorithm during this work. One blind 

equalization algorithm CMA is used [7]. We evaluate the performance of the adaptive equalizer in the presence 

of noisy audio source on the basis of their mean square error (MSE) convergence rate. 

II. Proposed Adaptive Equalizer Combined With Noisy Audio Source 

Fig 1 shows the proposed block diagram of the adaptive equalizer combined with the noisy audio 

source. At the transmitter side the noise is added with the audio signal and then signal is encoded by the help of 

differential encoder. Encoded data is modulated using QAM modulation scheme and BPSK is considered as 

symbol constellation. After that this modulated data is transmitted through an AWGN channel. The signal is 

received by a receiver having an equalizer. Three adaptive algorithms are performed simultaneously to make the 

equalizer adaptive and evaluate the performance of the adaptive equalizer in the term of mean square error 

convergence rate. 

Fig 1- Simulink Diagram of Proposed Adaptive Equalizer Combined With Noisy Audio Source 

III. Simulation Parameters 

The proposed model for the adaptive equalizer combined with the noisy audio source is simulated on 

the MATLAB10.0 Simulink. Table 1 shows the parameters and its corresponding value/technique consider 

during this work. The step size is taken as 0.01 for the LMS and CMA. A slight change in the step size can give 

other outputs. We consider a mono audio signal of 8000Hz, 16-bit. The LMS and RLS is operated in the 

training/decision direct mode, we can switch between the modes during the simulation. 


70 | Page


Table 1: Simulation Parameters 

IV. 

Simulation Results 

Fig 2- Received Signal at the Output of the Channel (RLS) 

Fig 3- Received Signal at the Output of the Channel (CMA) 

Fig 2 shows a scatter plot of the received signal at the output of the channel when the configurable algorithm is 

RLS. This shows that during implementation of RLS algorithm while the noisy audio signal passes through 

AWGN channel, the output is deviated from desired value. The simulation result of CMA algorithm is shown in 

Fig 3. This result shows scatter plot of the received signal at the output of the channel, which is similar to result 

of RLS. 


71 | Page


Fig 4- Signal Equalized by LMS 

Fig 4 shows a scatter plot of the signal equalized by the reference equalizer. We consider LMS as a reference 

equalizer. 

Fig 5- Signal Equalized by RLS 

Fig 5 shows a scatter plot of the signal equalized by the RLS equalizer. This result is comparable to the 

reference signal (Shown in figure 4). It indicates that the performance of RLS algorithm in presence of noisy 

speech signal. 

Fig 6- Signal Equalized by CMA 

Fig 6 shows a scatter plot of the signal equalized by the CMA equalizer. This result is also similar to the 

reference signal (Shown in figure 4). These results show that the signal equalization capabilities of both 

algorithms are similar. 

Fig 7- Frequency Response of Equalizer (RLS), Channel and 

Combined 


72 | Page


Fig 8- Frequency Response of Equalizer (CMA), Channel and Combined 

Fig 7 and 8 shows the frequency response of the equalizer (RLS and CMA), channel and combined. We can see 

that in the presence of noisy audio source RLS equalizer has very poor frequency response as compare to the 

CMA equalizer. The frequency response of the combination of channel and CMA equalizer is approximately 

desired, which shows that in the case of noisy audio source the CMA equalizer has better frequency response. 

Fig 9- MSE Convergence Plot for RLS 

Fig 9 shows the MSE convergence plot of the RLS equalizer. We can see that the convergence rate of RLS 

equalizer is very much fast, almost in 0.001 sec it converges from 0.24 towards the minimum mean square error 

(MMSE) but for a very short period of time 0.008. After 0.008 Sec the RLS equalizer not succeeds to achieve 

that convergence rate. 

Fig 10- MSE Convergence Plot for CMA 

Fig 10 shows the MSE convergence plot of the CMA equalizer. We can see that the CMA equalizer converges 

from 0.24 to 0.05 in almost 0.05sec. Although it is slower than RLS but successfully maintain the convergence 

rate. On the other hand the LMS equalizer takes time to converge [8, 15]. During the simulation process various 

values of the step size have been taken and the desired results have been found at optimum value of 0.01. MSE 

is one of the important parameter which decides the performance of equalizer. The simulation result shows that 

CMA has better MSE convergence as comparison to RLS. Since CMA is blind equalization algorithm and RLS 

is trained equalization algorithm so we can conclude that performance of blind equalization algorithm is better 

as compare to trained equalization algorithm in presence of noisy audio signal. 

V. Conclusion 

Thus using MATLAB simulation performance parameters of the LMS, RLS and CMA are optimized 

and analyzed in the presence of the noisy audio source. It is analyzed that the step size (µ) is the important 

parameter of these algorithms and the convergence characteristics decidedly depends on the µ. So the value of µ 

can affects the convergence rate and mean square error. Also it is examine that in the presence of noisy audio 


73 | Page


source, trained equalization algorithm RLS gives faster convergence rate as compare to the LMS, although 

needing higher computational capability. The obtained results show that the CMA equalizer is very promising in 

presence of noisy audio source. However CMA equalizer gives low convergence rate, comparable to that of the 

RLS equalizer but has better performance and requires no much computing power. 

References 

[1] John G. Proakis, “Digital Communications” McGraw-Hill International Edition, Fourth Edition 2001. 

[2] Theodore S. Rappaport, “Wireles Communications principles & practice Article”, Second Edition.2002 

[3] Shahid U.H.Qureshi, “Adaptive Equalization”, Vol-73, Issue-9, IEEE Proceedings-Sep 1985 

[4] S. Haykin, Adaptive Filter Theory, Prentice Hall, Englewood Cliffs, NJ, 4th edition, 2002. 

[5] C. R. Johnson et al., “Blind equalization using the constant modulus criterion: A review,” Proc. IEEE, vol. 86, no. 10, pp.1927– 

1950, Oct. 1998. 

[6] Domnique N. Godard, “Self-Recovering Equalization and carrier tracking in Two-Dimensional Data Communication Systems”, 

IEEE transactions on Communications, vol. COM-28, No.11, Nov.1980 

[7] E. Kalpana, O. Uma Maheswari, “Architecture Design for an Adaptive Equalizer”, National Conference, Pune.. 

[8] O. Dabeer, “Convergence analysis of the LMS and the constant modulus algorithms,” Ph.D. dissertation, Univ. Calif., San Diego, 

La Jolla, 2002. 

[9] G. UNGERBOECK, "Theory on the speed of Convergence in adaptive Equalizers for digital Communications." IBM J. Res. 

Develop., Vol. 11, pp 546-555, 1972. 

[10] V. WEERACKODY, S. A. KASSAM, and K. R. LAKER, "Convergence Analysis of an Algorithm for Blind Equalization, " IEEE 

TRANS. COMMUN., Vol. 39, pp. 856-865, June 1991. 

[11] R. CUSANI and A. LAURENTI, "Convergence Analysis of CMA Blind Equalizer," IEEE Transac. Commun., Vol. 43, pp. 1304- 

1307, 1995. 

[12] J. Yaun, K. Tsai, “Analyisis of the Multimodulus Blind Equalization Algorithm in QAM Communication Systems”, IEEE 

Transactions on Communications, Vol. 53, No. 9, pp. 1427-1431, Sept. 2005. 

[13] A. Beasley, A. Cole-Rhodes, “Performance of an Adaptive Blind Equalizer for QAM Signals”, MILCOM 2005, Atlantic City, NJ, 

Oct. 2005. 

[14] L. He, M. G. Amin, C. Reed, Jr., R. C. Malkemes, “A Hybrid Adaptive Blind Equalization Algorithm for QAM Signals in Wireless 

Communications”, IEEE Trans. on Signal Proc., Vol. 52, No. 7, pp. 2058-2069, July 2004. 

[15] Onkar Dabeer and Elias Masry “Convergence Analysis of the Constant Modulus Algorithm” IEEE TRANSACTIONS ON 

INFORMATION THEORY, VOL. 49, NO. 6, JUNE 2003 


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