Annexure I-B - AERA

MIAL submits that in its MYTP dated 11.10.2011 it has followed an asset by asset segregation
methodology wherein assets were identified as purely Aeronautical, purely Non-Aeronautical and
Common Assets. The Common Assets are mainly located in the Terminal buildings which are further
allocated between Aeronautical and Non-Aeronautical Assets based on the ratio of volume occupied by
the Aeronautical and Non-Aeronautical Assets.
In the entire approach the critical assumptions are:
• Assets defined as Aeronautical Assets in Of'JIDA and used for provision of Aeronautical services (as
listed in Schedule 5 of OMDA) are treated as aeronautical. For example, lifts, escalators and
passenger conveyors are specifically included under Schedule 5 of OMDA and hence, included under
Aeronautical Assets. Similarly, Assets used for provision of Non-Aeronautical Services (as listed in
Schedule 6 of OMDA) are treated as Non-Aeronautical.
• Assets that cannot be identified as purely Aeronautical or Non-Aeronautical are classified as common
assets.
As the approach adopted for identification and segregation of assets into Aeronautical, Non-Aeronautical
and Common Assets is in line with provisions of OMDA, MIAL has not changed its approach for the same.
The segregation of assets as on 31.03.2010 and 31.03.2011 is presented below:
T a bl e 3 : Segrega tl Ion 0 fA sse ts s mro l t AeronaufiN teat on-A eronautlrca andC ommon A sse t s
In Rs. Cr.
As on 31.03.2010
As on 31.03.2011
Aeronautical Assets
1062
1624
Non-Aeronautical Assets 130
141
Common Assets
Total*
*Excluding Upfront Fee and Retirement Compensation
281
1473
308
2073
For the purpose of allocation of Common Assets, although MIAL believes that ratio of volume represents
more appropriate basis for allocation, it has modified the basis of allocation from volume to area used by
Aeronautical and Non-Aeronautical Assets in line with the suggestion given by Hon'ble Authority. While
doing an allocation of Common Assets, MIAL has considered the area used by all Non-Aeronautical
Services, including seating areas for provision of Non-Aeronautical Services. In addition, it has allocated
the common seating areas in three proportions of Aeronautical: Non-Aeronautical (i) Common (50:50),
(ii) Predominantly Aeronautical (90:10) and (iii) Predominantly Non-Aeronautical (10:90). The revised
j 5

Based on the above approach, AeronaLitical and Non-Aeronautical Assets have been segregated for the
entire control period. The overall ratio of Aeronautical Assets to Total Assets (Le. Aeronautical plus Non­
Aeronautical Assets) has been computed for each year of the control period, which is summarized below:
Table 6: Overall Aeronautical Assets as a °/0 of Total Assets
Aeronautical Assets as
%age of Total Assets
FY 10 FY 11 FY 12 FY 13 FY14
89.92 91.87 91.18 92.78 93.11
Total Aeronautical Assets* 1,559 2,144 2,642 4,000 10,324
*Excludmg Upfront Fee and including Retirement compensation
5. Hypothetical Regulatory Base (HRB)
MIAL had earlier considered WACC based on actual gearing, cost of debt and cost of equity for FY 09
while computing the Hypothetical Regulatory Base (HRB). However, upon careful reading of the definition
of HRB given in the SSA it was noticed that actual values of only expenses and revenues, as specified
therein, for FY 09 is to be considered. Since HRB is dependent on the notional business value of the
airport leased to MIAL at the time of privatization during the year 2005-06, it would be appropriate if the
WACC is considered equivalent to what was indicated at the time of bidding l.e, 11.6%. Further, the HRB
once becomes part of the overall regulatory base, the same needs to be depreciated like any other
physical fixed assets. Accordingly, HRB calculation is being revised as follows with depreciation
considered at the weighted average rate of other assets:­
Table 7: Computation of Hvoothetlca . I Requ atorv Base
In Rs. Cr.
.I ..
r
FY09
Aeronautical Revenue (A)
375
Non-Aeronautical Revenue(B)
563
Operation and Maintenance Expenditure pertain ing to Aeronautical
Services(C)
311
Tax pertaininc to Aeronautical Services (D)
1.6
Weighted Averaue Cost of Capital - WACC (E)
11.6%
Hypothetical Regulatory Base((A+300/0*B-(C+OH/E) 1991
7
\
l

[C] Cost of Equity
6. Risk Free Rate (Rt)
Hon'ble Authority had desired to know the reasons for choosing Yield on 10 year Government Bonds as
Risk Free Rate and the source of data used. In this regard it is submitted that sovereign bonds are
considered to come closest to a risk-free investment. They satisfy two basic conditions to qualify as risk­
free:
a. Absence of default risk
b. No reinvestment risk - In order for an investment to fetch a return that is exactly equal to the
expected return for a given time horizon, the rate of return for that risk free investment needs to remain
unchanged throughout that period. For this reason, treasury bills which have a maturity period of less
than a year are not considered. The investment horizon of T bills is much shorter than the investment
horizon in case of an airport. So, although they are risk-free investments, they fail to eliminate the
reinvestment risk as yields of such instruments are unlikely to remain the same for the said period.
Accordingly, the yield on government bond securities with long-term maturity is a preferred option for
estimating the risk-free rate. MIAL has considered yield on 10-year GO! securities as at the valuation date
as the risk-free rate, over bonds with different maturity periods, as a benchmark risk-free rate for two
key reasons. First, the price of the 10 year bond is less sensitive to unexpected changes in inflation
compared to the 30-year bond. Second, the trading volumes of 10 year bond are higher compared to the
trading volumes of longer tenure bonds and hence the liquidity premium built into 10-year rates is
generally lower compared to that of 30-year bonds. Our methodology is in line with the ones followed by
major airports around the world, e.g. Dublin international airport uses yields on long-term deflated
German government bonds to estimate the risk-free rate.
The source of data is Bloomberg Website, which publishes such data and which is attached as Appendix
3.
7. Basis of computing Market Rate of Return (Rm)
Hon'ble Authority desired to know the basis for computing Market Rate of Return (Rm) and the reasons
for choosing that basis.
8
,

MIAL has used the 10 year CAGR on 90 days moving average of the BSE Sensex value as the market rate
of return (Rm). The 10 year time frame corresponds to the time period which is a decade after the onset
of liberalization ('91) of the Indian economy. Varma and Barua (IIM Ahmedabad) in their paper [Varma,
Jayanth R, Samir K Barua, "The First Cut Estimate of the Equity Risk Premia in India"] have also
emphasized the fact that structural changes have taken place in the Indian economy during the decades
of '80s and '90s and the characteristics of the economy are markedly different as compared to periods
preceding it. However, in order to provide for sufficient time period, for development and ripening of the
economy and the markets post the structural changes, the 10 year time frame (2001-11) has been used.
The 90-day moving average, instead of a daily average, is used so that day-to-day volatility of the
...; markets is eliminated while calculating the return. Further, as the half-yearly or yearly moving average
may have large deviations from the market trend due to averaging over larger period, they have not
been used. 10 year CAGR of 90 days moving average, rather than arithmetic or geometric mean of
annual growth rates in 90 days moving average has been used to eliminate the impact of cyclical
variations in economy over a long horizon of 10 years.
The BSE Sensex represents free-float market capitalization weighted index of 30 well established and
financially sound companies in India and thus is a good proxy for the Indian markets. While a broader
index (e.g. BSE-SOO, Nifty) may include a wider portfolio of stocks in the market, given the relative
instability of some of the smaller stocks in these broader indices, Sensex is chosen as a more robust
indicator of returns on a diversified matured market portfolio.
EqUity Risk Premium (ERP) has, therefore, been computed as Rm - Rf.
8. Reasons for choosing airports from emerging markets for computing Beta
In the absence of any pure play publicly listed airport in India that can be used to estimate the beta for
airport business in India, betas of listed airport operators in the emerging markets have been considered
as a proxy for the Indian airport operators. For selecting listed international airport operators only from
countries with emerging markets, their semblance to Indian airports on the followinq factors has been
considered:
• Economic profile
• Operating environment
• Opportunities and constraints
• Financial position
9

In 1980, a World Bank Economist, Antoine van Agtmael, brought forward this term to replace the then
exlstinq "less economic developed countries" (LEDC) tag that was given to countries who were less
developed than US, Japan and Western Europe. Emerging markets also represents such countries, which
are in transitional phase between developing and developed status. There have been various practical
definitions too given to Emerging markets over time, such as:
1. In 2008, Center for Knowledge Societies defined Emerging Economies as those "regions of
the world that are experiencing rapid informationalization under conditions of limited or partial
industrialization."
2. FTSE Group, a UK based provider of stock market indices, distinguishes between various
markets (Advanced EM and Secondary EIVI) based on a country's national income and
development of their market infrastructure
3. MSCI, a New York based advisory in investment decision support tools, provides a list of 21
countries around the world as emerging markets. The same list is supported by The Economist
as well. To select a country in EIVI group, MSCI compares the per capita income with respect
to that of the country with lowest per capita income in their World List (developed countries list).
4. S&P, based on the following factors: macroeconomic conditions; political stability; legal property
rights and procedures; trading and settlement processes and conditions; and feedback from
institutional investors, came up with segmentation of countries as.developed and emerging.
5. Dow Jones, considers 35 countries in the EM segment
6. Frontier Strategy Group, conducts surveys every month to find the top 10 EM, which are
tracked by the executives of various multinationals
7. BBVA Research, introduced a new concept to identify EM based on the 10 year GDP forecast
for a country and comparing it with the 10 yr forecast for G-7 countries (excluding US).
Here is a list of common names among these sources:
Country FTSE MSCI S&P Dow Jones Frontier-l0 BBVA
India Yes Yes Yes Yes Yes Yes
China Yes Yes Yes Yes Yes Yes
Malaysia Yes Yes Yes Yes No Yes
Thailand Yes Yes Yes Yes No Yes
Mexico Yes Yes Yes Yes Yes Yes
Honq Konq No No No No No No
Russia Yes Yes Yes Yes Yes Yes
slncaoore No No No No No No
Indonesia Yes Yes Yes Yes Yes Yes
Vietnam No No No No No Yes
UAE Yes No No Yes No No
Brazil Yes Yes Yes Yes Yes Yes

C .
Per anita Income Com aarlsom
Country Per Capita Income (USD, 2010, IMF)
India 3408
China 7544
Malaysia 14,744
Thailand 9221
Mexico 14,406
Hong Kong 45944
Russia 15612
Singapore 56694
Indonesia 4,347
Vietnam 4,143
UAE 47439
Brazil· 11273
US 46860
Japan 33885
UK 35,059
France 33,910
Germany 36,081
Spain 29,830
Quick observation of the above table shows stark difference between countries termed as EM and non­
EM countries. India is comparable to China, Thailand, Indonesia, etc. countries and hence airports in
these countries have been used to arrive at beta value for Indian scenario.
For sake of comparison MIAL gives herein below the equity beta for airports across the globe which
include developed countries having similar passenger traffic:
S.
N
0
Airport / Operator Passenger
Capacity in Mn
5 Years Beta
1 Kuala Lumpur International Airport / Malaysia
Airports Holdinqs
34.08
0.848
2 Shenzhen International Airport/ Shenzhen Airport
Company Ltd.
26.71 0.861
3 Auckland Airport 13.20 (Newzealand) 1.041 (Newzealand)
4 Australia 27.73 (Melbourne)
35.99(Sydney)
0.623
5 Flughafen Wien AG 19.7 0.822 (Vienna)
6 Flughafen MunchenAG 34.7 0.860 (Munich)
7 Japan Airport Terminal 64.07 0.779
8 Xiamen International Airport Co. Ltd, China
Operates 3 airports
13.2 (Gaoqui)
6.5(Shuzhou Chanqll)
0.742
9 Fraport, Germany 53.00 0.898
10 Flughafen Zuerich, Switzerland 21.92 0.763
11

It may be seen that 5 year beta for these airports is close to the range of 0.89 to 1.12 for chosen
airports in emerging markets by MIAL. Even for developed countries the beta is not very low. It is,
however, pointed out that Traffic risk, while being a significant risk, is only one of many business risks
that an airport operator faces. While comparing airports with similar traffic profile is preferable, airports
with lower traffic levels can exhibit a similar risk profile (beta) as airports with higher traffic, if the
underlying business and economic environment are similar. Further, International traffic is not location
neutral. International air travel is influenced by factors such as business, leisure and personal needs as
well as the prevailing political, economic and security environment of the country. Even though airports
.
may have similar international traffic volumes and passenger profiles, volatility of demand is likely to be
different for different airports based on the strength of underlying demand drivers and risks. For
example, in a global recession, the impact on international air traffic will be different in different
economies. Comparing beta of airports with similar international traffic profile may, therefore, not be the
right approach. Further, this approach ignores the impact of volatility in domestic demand.
9. Reason for taking different Debt/Equity (D/E) ratios during un-levering and re-Ievering
The beta of a stock (or business) is determined by three factors -(1) business risk, (2) operating leverage
and (3) financial leverage. (1) Business risk means the more sensitive a business is to market conditions,
the higher the risk with respect to the market and hence higher is its beta. (2) Operating leverage refers
to the variability in earnings for an investor due to fixed cost vs. variable cost split of the cost structure of
the business. As for (3) financial leverage, all things remaining equal, an increase in financial leverage will
increase the beta as the variance in net earnings of investors increase with higher obligated payments to
the lenders. Since financial leverage impacts the beta, it becomes imperative to unlever the (equity) beta
determined for publicly traded stocks to arrive at the (asset) beta which reflects the risk only due to
business risk and operating leverage. Hence, by un-levering the equity beta with D/E ratio the normalized
asset beta is obtained which reflects the business and operating risk for that industry. To arrive at equity
beta of a particular stock in that industry, the asset beta (considered as proxy for business in a different
country) needs to be re-levered with financial leverage of that particular business to capture additional
riskiness due to financial leverage. Since unlevering and re-Ievering are done for similar stocks/businesses
but with different financials; the financial leverage and hence, equity beta for both is bound to be
different.
Further, the Indian private airport operators have a significantly high debt to equity ratio compared to the
listed airports in the emerging markets. The median debt equity ratio for the airports in emerging
markets is onIYIV0.15. Such a debt equity structure translates into further fixed cash outflows in the form
12

of huge interest and repayments, which translates to a longer gestation period to equity investors before
any dividends are paid. Further, CSIA faces unique risks as have been brought out by KPMG in their
Report on Cost of Equity submitted earlier with MYTP. Hence asset beta of 0.85, which is slightly higher
than median asset beta of 0.80, has been considered.
)
10. Reason for using Market Capitalisation while de-levering and Book Value of Equity while
re-Ievering
As CAPM is a prospective model as opposed to a retrospective model, it attempts to measure the return
on capital in the company going forward. Since the inception of a business, changes in capabilities, value
proposition, business environment, competitiveness, etc. of the underlying asset or business are likely to
happen. Consequently, the present valuation of the stock is a better indicator of the worth of the equity.
Therefore, the relative risk due to obligated payments to lenders may be more appropriately reflected
using the Debt-Equity Ratio (DER) based on market value than on book value. Hence, market
capitalization has been used for de-levering equity beta.
The market value of equlty is ideally the one based on the price of actively traded shares of a listed
entity. Since MIAL is a Private Limited Company its market value is not available. Clause of 2.5 of OMDA
prohibits transfer of eqoltv shares upto initialS years and puts restrictions on transfer of shares upto i h
year and hence no realistic market value of equity can be determined. Since these restrictions are within
the present control period starting from 4 th year, realistic estimation of market value of equity is not
possible, Hence, projected value of DER in books, which is the best available substitute for market value
of equity and debt, has been used to re-Iever the beta. This approach is also preferred since it is
important to be consistent in using the same DER both for re-Ievering the beta and for calculating the
costs of debt and equity for calculating the FRoR.
13

[C] Operation and Maintenance (O&M) Cost
11. Benchmarking of O&M Cost
•
MIAL has done Benchmarking of its O&M and Employee Costs with some other airports in India which is
presented below:
Table 8: Benchmarking of O&M Cost$
Name of Airport I
Company
Mumbai International Airport
Private Limited*
Delhi International Airport
Private Limited*
Airports Authority of India*
Trivandrum Airport#
Ahmedabad Airport#
Period Operating Cost
(in Rs. Million)
FY11
FY11
FY 10
FY11
FY11
$ Includes Employee Cost
* Taken from Annual Accounts of the respective Companies
Pax in Million Operating
Costs/Pax
2,559.00 29.07 88.03
5.474.60 29.94 182.85
26173.88 123.76 '211.50
881.00 2.53 348.65
779.00 4.04 192.66
# Taken from Order No. 01/2010-11 for Trivandrum Airport and 02/2010-11 for Ahmedabad Airport
issued by Hon'ble Authority
It can be seen from the data presented above that MIAL currently operates at a lowest operating cost per
passenger amongst the comparators, inspite of the fact that there are quite a few cost which are
significantly higher in Mumbai such as minimum wages payable to workers, salaries payable to staff and
per unit electricity cost etc. Further, few costs which are unique to CSIA / airports in Maharashtra which
may not be applicable to other airports such as Property Tax/ Municipal Tax and Non Agriculture Tax etc.
12. Reasons for substantial increase in Employee Cost
Main reasons for increase in employee cost during this control period is increase in Head count for
readiness and operationlisation of New Common User Terminal which is scheduled to be operational from
September 2013
14
l-Y

The Employee Cost is increasing for the following reasons:
(i) Annual Increments
Annual increments in salary have been assumed to be 15% p.a. which are also close to the
average increase in past 4 years. Further, net increase after accounting for inflation of 8.94% is
only 6.06%, which is nominal considering normal increments and increments due to promotion.
(ii) Head Count
The Head Count has been determined for each department separately depending upon
operational requlrernents for each year separately. MIAL has further revisited its assumption for
increase in manpower requirements as suggested by Hon'ble Authority and has reduced
projected requirements, The reasons for increase in headcount are given in Appendix 4. The
revised manpower cost is presented in the following Table:
Table 9: Revised Manpower Cost
FY 10 FY 11 FY 12 FY 13 FY14
Cost (in Rs. crs.) 79.8 83.8 96.5 29.3 148.7
A benchmarking of Employee Cost is given hereunder:
Table 10: Benchmarking of Employee Cost $
Name of Airport / Company Period Employee Cost
(in Rs. Million)
Pax in
Million
Employee
Cost/Pax
Mumbai International Airport Private Limited* FY 11 837.81 29.07 28.83
Delhi International Airport Private Limited* FY 11 1393.30 29.94 46.53
Airports Authority of India * FY 10 16,128.26 123.76 130.32
$ The Employee Cost/Pax given above may not be strictly comparable as it may vary depending upon
number of actlvlties outsourced, the cost of which may be captured in some other head.
* Taken from Annual Accounts of the respective Companies
13. Reasons for substantial increase in Electricity Cost
The Electricity Cost is increasing for the following reasons:
(i) Annual increase in electricity tariff
The increase in electricity tariff is beyond the control of MIAL as the same is set by Electricity
Regulator. MIAL has also represented before the regulator for considering lower than existing
15

- Jo/­
whereas some portion of the load (e.g. mechanical drives for conveyer belts, escalators, lifts, HVAC)
has variable load factor and hence, consumption increases/ decreases depending upon the number of
passengers using these facilities. However, consumption due to these facilities is not purely variable
but comprises of some fixed portion (which is small %age of full load consumption) and some
variable portion which is purely dependent on usage. With increase in number of passengers, the
usage of equipment and hence variable consumption increases. CSIA has about 26% lighting load,
58% HVAC load and 16% mechanical load while 26% lighting load has fixed load factor, balance
74% load is assumed to have 24% fixed load factor component and 50% variable load factor
component making total fixed and variable load factor components 50% each. Accordingly, the
increase in load factor by 50% of growth rate of passenger has been used. This is also validated by
the fact that CSIA has made about 5% savings in electricity in previous year by various energy
conservation measures, which otherwise would have resulted in 5% increase in electricity
consumption that has not happened as electricity consumption has almost remained same. 5%
increase in electricity consumption is almost 50% of 3 year CAGR of 11% p.a. increase in passenger
numbers and hence, the assumption of increase in load factor by 50% growth rate of passengers is
reasonable.
(iv) Regulatory Asset Recovery ordered by Hon'ble MERC
As mentioned in the MYTP, Hon'ble MERC has in principle decided to levy recovery of Regulatory
Asset in its recent tariff order of R-Infra-D (Erstwhile Electricity supplier to MIAL), which is to be
recovered in the coming years. Hence, MIAL has estimated its liability based on the said order to be
paid in a period of 3 years. The relevant extract of the Order and calculations are attached as
Appendix 5(B).
14. Basis for projecting Repairs and Maintenance (R&M) Cost
MIAL has considered 1.25% of the opening value of Gross Fixed Assets (GFA) for projecting the R&M
expenses. This ratio for last 5 years has been 6.1%, 7.2%, 2.5%, 1.56% and 1.1% respectively.
Although R&M cost has been increasing in absolute terms, this ratio has first increased and then shown a
declining trend R&M cost, other than that on comprehensive operations and maintenance contract, is
mostly contingent upon the unplanned repairs and maintenance activities required for various civil,
mechanical and electrical works in a particular year. For example, an old machinery may require huge
maintenance cost in particular year, but may not need it for next few years. Hence, R&M cost cannot be
correctly estimated based on past trend. The closest estimate for projecting R&M cost can be computed
by linking it to the driving factor for various R&M activities. As R&M activities are directly dependent upon
17 1.Jei­

the quantum of assets required to be maintained, the R&M cost is usually estimated on the basis of value
of assets maintained. For example, Delhi Electricity Regulatory Commission (DERC) has specified R&M
expenses to be fixed as proportion of GFA in its Multi Year Tariff Regulations (MYT). While determining
the R&M expenses in case of North Delhi Power Limited (NDPL), DERC observed that there was large
variation in the proportion of R&M expenses as a percentage of GFA over last five years and hence, has
taken average 2.82% for projecting the R&M expenses. Relevant extract of the MYT Order dated
23.02.2008 is enclosed as Appendix 6. Hence, R&IVI cost as 1.25% of opening GFA, which is much less
than average of 3.69 % for preceding 5 years is justified considering that new assets would require lesser
maintenance. It may also be noted that R&M cost as a proportion of GFA is increasing substantially due
to substantial addition of assets in this control period. R&M expenses are expected to be more stable
after commissioning of l\Iew Common User Terminal. The example of NDPL as an electricity distribution
utility is also from a business that has regular addition of assets for meeting the increasing demand of
electricity as is the case with MIAL. Additionally Rs. 26 Crore is the planned expenditure for repair of
taxiway N1 in FY 13.
15. Administrative Costs
Routine Administrative Costs have been projected based on inflationary increases of 8.94% p.a.
Additionally specific planned expenditure such as consultancy cost for Airport Operations Readiness and
Business Development, I T services outsourcing cost have been added wherever required.
16. Operating Contracts for cleaning services
The cost of Operating Contracts for cleaning services have been increased annually with rate of increase
in Minimum Wages (CAGR of 9.49% for last four years). Additional 10% increase in manpower has been
considered for FY 12. On commencement of operation from New Common User Terminal, cost has been
increased in proportion to increase in area and additional 100% increase due to requirement of
specialized cleaning manpower and equipment for the State-of-the-Art New Common User Terminal and
considering significant glasswork and intricate roof and jali work.
18

In this regard, it is submitted that the computations given below are based on the changes discussed
above. However, in case Hon'ble Authority does not accept any of the above changes, it will have a
corresponding impact on tariff increase, internal accruals and DF requirement etc. For example, as the
project cost of Rs. 12380 Crore and funding from other sources (Rs. 6431 Crore) is fixed, the balance
funding of Rs. 5949 Crore has to come from internal accrual and DF. In case, internal accruals given here
are reduced, DF has to be increased by corresponding amount so that both add up to Rs. 5949 Crore for
meeting the funding requirement. As such, the computations and amounts given herein are required to
be considered together and not in isolation or selective basis. Hon'ble Authority is, therefore, requested
to consider the above submissions in entirety.
Table 12: Means of Finance
In Rs. Cr.
Equity
a. Paid Up Capital 1200
b. Internal Accruals (Reserves) 2473
c. Real Estate deposits (refundable) 1000
Development Fee 3476
Debt 4231
Total 12,380
T abl e 13.S . ummaryofT arge tRevenue . In Rs. Cr.
FY 10
Target Revenue Computation
FY 11 FY 12 FY 13 FY 14
Actual
Projections
Regulatory Base*
3090 3512 3877 4677 7128
WACC 16.66% 16.66% 16.66% 16.66% 16.66%
Return on Regulatory Base 515 585 646 779 1187
Operation & l'vlaintenance cost 256 213 350 441 643
Depreciation
152 194 212 251 370
Corporate Tax
211 226 247 300 331
Subtotal 1134 1218 1455 1771 2531
Less: 30% of Revenue from Revenue
Share Assets
---
175 229 242 219 207
Tarqet Revenue 960 988 1213 1552 2323
(*) Net ofUpfront Fees, DFfunded assets and Non-Aeronautical Assets.
20
.
'.ot

MU MBAI INTERNATIONAL AIRPORT PRIVATE LIMIT ED
Air Traffic Forecast for Chhatrapati
Shivaji International Airport, Mumbai
FY12-FY21
Department of Statistics, M IAL
si" October 2011
1

Executive Summary
1. Ghhatrapati Shivaji Intemational Airport (e SIA) was the busiest airport in India
until Delhi Airport overtook il in FY10. 11 handled 20.2% 01 India's passenger
traffic and 26.7% 01cargo traffic in FYl l .
2. GSIA handled 29.07 million passengers in FY 11, registering 13.5% growth in
passengers and 5.6% growth In Air Traltic Movements (ATMs) compared 10 FY
10.
3. A comparative study 01 GSIA passenger tratlic wiltl ' AIl India" traffic lor the last
ten years shows that CSIA's Compound Annual Growth Rate (GAGR) of 3. 5 and
t o-years respectively is always lower than the national GAGA. The 3, 5 and l Qyears
CAGR lor passengers at CSIA grew by 4.0%, 9,6% and 9.1% against the
national CAGR ot 7.1 %,14.4% and 13.1% respectively. The 3, 5 and t c-yee rs
CAGR lor ATMs at GSIA grew by 1.4%, 7.2% and 6.4% against the national
GAGR oj 2.1%, 10.7% and 11.0% In the corresponding years.
4. Further analysis 01 the recent traffic trend of GSIA with other major airports in
India also shows that the growth rate at GSIA is lower than the other major
airports. For exarnpte. 5-years GAGR for Delhi's passenger nettie was 13.0%
against 9.6% at CSIA.
5. The growth of GSIA tratlic was stifled in recent years mainly due to runway
capacily constraint which is capped at 36 ATMs per hour at present.
6. Air trallic lorecast is done for lwo scenarios, unconstrained growth scenario and
constrained growth scenario mainly due to runway capacity constraint.
7. Under the unconstrained growth scenario, passengers traffic are projected based
on the historical lQ-years GAGR at CSIA i.e. 11.1 % and 5.8% for domestic and
international passengers respactively. ATMs are estimated by dividing the
projected passengers per air traffic movements lor passenger flights
(PAX/PAlM). The hislorical 3-years GAGR on PAXlPATM Is used as it shows
some consistency in the growth and rellects lhe current situation. Under
unconstrained growth GSIA's capacity 0140 milliOn passengers would have been
reached in FY15.
8. Under the constrained growth scenario, the average passenger, ATMs and cargo
growth will be 6.0%, 3.7% and 6.5% respectively (as against 9.5%, 7% and 8.9%
in the unconstrained growth scenario) lor 3 years up to FY14.
a

AIR TRAFFIC FORECAST FOR CHHATRAPATI SHIVAJI
INTERNATIONAL AIRPORT, MUMBAI FOR THE PERIOO FY12-FY21
1. INTRODUCT..!Q!!
Chhatrapati Shivaji International Airport (CSIA), Mumbai was the busiest airport In India
until Delhi Airport overtook it in FY10. In FY11, CSIA handled a tolal 01 29.07 million
passengers, or 20,2% 01 India's total traffic (as against Delhi's share 01 20.6%).
Presently, 37 International airlines and 7 domestic airlines connect CSIA 10 44
international destinations and 43 domestic destinations. In addition, 5 inlemational
airlines and 1 domestic airline operate exclusive freighter flights from CSIA,
2. OBJECTIVES
This report provides a comprehensive air traffic torecast tor CSIA lor the period FY12­
FY21. Although air traffic toeecast depends on various lactors such as GOP,
populafion growth, worldwide economic oullook, tourism growth, Oil prices as well as
regulatory and policy framework. this in-house air traffic forecast for CSIA is derived
mainly based on historical air traffic data 01 CSIA. The main objectives 01 this Report
are:
i. To compare the growth 01 CSIA traffic with "All India" traNic and that of other
major airports in India;
ii. To evaluate the growth potential 01 CSIA based on historical Compound Annual
Growth Rate (CAGR); and
IIi. To analyse lhe fuM e traffic situation of CSIA in relatiOn to runway capacity
constraint.
3. DATA SOURCE
The data used lor the analysis include CSIA historical data and "All India" traffic data
taken Irom the 'Review of Traffic 2009- 10' published by the Airport Authority ct India
(AAI) and also lrom lhe AAI website,
,

5. AIR TRAFFIC FORECAST FOR CSIA
Air Traffic forecast for CS1A based on unconstrained growth whereby it is assumed that
the physical capacity 01 CSIA is able to match the demand of air traffic growth in the
catchment area of Mumbai. Second scenario assumes this traffic growth will be
restrained the runway capacity.
ABBREVIATIONS
The following abbreviations are used in the subsequent sections on air traffic forecast
CSIA = Chhatrapati Shivajl International Airport
PAX = Passengers (Embarking and Disembarking)
ATMs = Air Traffic Movements (landing and take-off are counted as 2 movements.)
PATM = ATM of passenger flights
FrAlM '" AlM ot freighter flights
SEAT", No. of seats in a particular flight
SEATI PAlM ", No. of seats per PATM
PAX/PAlM ", No, of PAX per PAlM
PAlMI hour", No. of passenger flights in a particular hour
FrATMf hour = No. of freighter flights in a particular hour
CAGR = Compound Annual Growth Rate
ASSUMPTIONS
The following assumptions are considered in the traffic torecast..
Unconst rained Growth Scenario
1. Historical 10-years CAGR is used for the forecast of passenger growth at CSIA
[i.e. 11.1 % annual growth in domestic passengers and 5.8% annual growth in
international passengers) as it reflects long term trend of almost unconstrained
growth.

- l lt­
2, HislOriCal 3-years CAGR on PAX/PATM (3.3% annual grO'Nlh in domesUc
PAx/PAlM and 0% growth in international PAX/PAl M) is used to forecast lhe
number 01 PAl Ms (passenger I lights) in future as it shows consistency in Ihe
growth and reuects the current trattlc situation. Ten-years and five years CAG R
of PAX/ATM show nega tive growlh for internation al traff ic and the refore is nol
conside red.
3. Historical a-years CAGR on SEATfPATM (0.48% annual growlh in domestic
SEAT/PAl M and 0% growlh in international SEATil"ATM (as 3 . 5 and 10-years
CAGR for international passengers was negative) is used to calculate the
fore cast SEAT/PAl M.
4. Historical 5-years CAGR on FrAnAs (freighler nights) is used to forecast the
future FrATMs and iI is assumed to grow at 8.7% and 2.0% per ann um for the
domestic and intemalional lraffic respectively.
5. Hourly trend of ATMs in each particular hour in FY l 1 is assumed to continue and
the growth of ATMs in each particular hour is equal to the corresponding annual
growth rate in PATMs and FrATM for me year.
6. Historical 10-years CAGA of tol al cargo handled at CS IA is used for the forecast
01 ca rgo lonoage growth at CSI A separately for in-line and freighter cargo in
domestic arc inlemational flights (i.e. an nual growth in dom estic cargo: 9.4% inline
and 12.4% freig hter and annual growth in internalional cargo : 8.34 % in-line
and 8.35% freighter) as it reflects long term trend of growth.
Co ns tr ained Growth Scena rio
·1. CS IA is cons trained by the runway capacity.
2. The hourly runway capacity is capped at 36 ATMs rna Jdmum (supporting
document at Ann exure - 2) , However, a maximum hou rly ATM of 34 .81 (instead
of 36) is conside red alter factoring in a cancellation ra te 01 3.3% of the scheduled
flights based on FY1l .
"

-1/7­
3. As in unconstrained growth scenario, the historical 3-years GAGR on PAXJATM
and SEAT/PAlM are used to calculate the forecast number of passengers in
future.
4. Seat load factors are capped at 90% for the projected period because practically
il is not feasible 10 achieve average load factor beyond 90%.
5. FrATM will be allotted slots above FY 11 level only during lean period as no
further growth is possible due to runway capacity limitation during peak hours.
Thus, FrATMs are assumed to be allotted additional slots only after meeting
PAlM demand subject 10 runway capacity constraint.
FORECAST METHODOLGY
The methodology adopted to project the future traffic is follows:­
Unconstrained Growth Scenario
1. The forecast for domestic and international air traffic is done separately and
added togethe r 10 arrive at total air traffic forecast for GSIA
2. Domestic and intemational passenger traffic are projected based on the historical
10-years GAGA of GSIA (11.1% and 5.8% annual growth for domestic and
international passengers respectively) which is achieved without major constraint
till dale ,
3. The future PAx/PATM is derived based on the historical 3-years GAGA for GSIA
(3.3% and 0% respectively for domestic and inte rnational traffic).
4. Seal load factor is calculated based on PAXlPATM over SEAT/PATM.
5. PATMs (passenger flights) projection, the forecast passenger numbers so
obtained above are divided by PAX! PATM for the corresponding years .
6. FrATMs (freighter flights) projection are assumed to grow at 6.7% and 2.0%
respectively for domestic and international traffic. This is based on 5 years
CAGA
n

7. Hourly trend of ATMs in each particular hour in FY11 is assumed to continue and
the growth 01 ATMs in each particular hour is equal to the corresponding annual
growth rate in PATMs and FrATM for the year.
8. Domestic and intemational cargo trallic are projected from FY11 data based on
the historical 10-years CAGR 01 CSIA for inline and freighter cargo separately
(9.4% for Inline and 12.4% for freighter annual growth for domestic and 8.34% for
Inline and 8.35% for freighter for international cargo respectively). The
unconstrained cargo forecast details are given in Annexure 8.
FORECAST
Table·3 below shows the unconstrained passenger traffic and ATM growth for CSIA for
the period FY12-FY21. Details 01hourly traffic are as per Annexure - 4.
Table-3 ; Unconstrained Traffic Forecast for Ihe period FY12-FY21
Constrained Growth Scenario
The main constraint at CSfA is the runway capacily. currently capped at 36 ATMs per
hour , Under the current Ilighl schedule at CSIA. up to 36 ATMs have already been
scheduled almosl lhroughout the t e-nccrs period from 0600-2359hrs daity. In addition
10 the scheduled lIights. there are on an average 38 general aviation movements a day.
moslly during the day hours, which lurther cooseeuus the runway cepacw. A typical
houl1y runway movemenl chart for a week is given below (Table - 5) to illustrate the
current runway capacily constraint at CSIA.
"

'rabie-s : Hourly ATM s in winter schedule effective from October 20 11
HOURLYATM as per Winter SCh edu le 2011
"0' W, W OO '"0 >"'
0000-0100 ai az zz n "" '"'
0100-0200 is n
is ia re rs
"
" " az
0200-0300 " rs B " " is
0300-0400 rz rz U rz U B U
0400-0500 rs rs n " 0500-0600
ai as " za
0600-0700 " " ss
aa " ss
0700-0800 " " ae as
0800-0900 " as " se "
0900-1000 as as " as " as
1000-1100 as as as " se as
1100-1200 as as "
" 1200-1300 so ai ai " aa
"
zo is
"
" "
as as
as as az
" "
1300-1400
1400-1500
1500-1600
1600-1700
1700-1800
1800-1900
as
" as
ss
se
as
as
" sa
ss
" as
" as
as
ss
aa
as
" as
ss
as
" as
ae
" as
as
ss
se
se
ai " as
sa as
" as " aa
" as " as
ae as
"
1900-2000
2000-2100
2100-2200
2209-2 300
2300-2359
TOTAL
as
ss
" aa
az
ae
as
as
" az
ae
as
" as
az
as
ae
se
as
az
ae
as
as
as "
as
" as
aa
sa
as
se
as
as
ai
'" '"
m m va s rae no
The methodology adopted in the projection of future traffi c is as follows:­
1. The projection for future trattlc wil l start with the determination of total hourly
ATMs in future which is constrained by the hourly runway capacity of 36 ATM
maximum . A maximum hourly ATM of 34.81 (instead of 36) is considered after
B

To validate the soundness of fhe assumptions and methodol ogy edccted In the trentc
forecast. the forecast traffic in FYTD Septt t are compared with the actual traffic for the
period FYTD Septtt . It is noted that the overall growth rates lor Ihe passengers , ATMs
and cargo tonnage as derived by the forecast model are lower than the actual growth
registered during Ihe period April 11 -Septl1 as shown in Table ·7 below.
TBbl,.Z; Cemparallve a""lyo.ls el aClua ' Ir"fllc IOf !!It ponoel Aprll-Stp! 11 " , ••• ", 19",," 1 p....n9' "
fYTO seau
April11- Sept 11 % of variation
Actual Forecast
over forecast figur es
Total ATM 125,569 127,647 -1.63%
Total
Passe nge rs 14,92 5,910 15,634,703 -4.53%
Total Cargo
(MT) 339,243 360.358 -5.86%
It may be seen that the forecast is higher than lhe actual traffic. primarily beca use n is based on
past trend in growth, whereas due 10 global ec:ooomic recession In lhe recent past the Iraffic at
CSIA is witnessing a steep declining trend r terercre. it is eoncludect mat the traffic al CS IA will
no! only grow slower lhan the unconstrained scenario because of the runway capacity constraint
but also due 10 unforeseen changes in ecooornic 'actors, which have no! been captured In this
report The airpor1 capacity oI4tl million will be reach ed only In FY19. Instead 01 FY 15. based
on !his in-house traffic forecast A summary oIlhe projected IraffiC is presented in Annexure - 6.
"

ANNEXURE - 1
CAG R for last ten years

- 33/­
Annexure - 3
Data of flights cancellations in FY11
TOTAL
Year International Domestic Overall
zoi o­
11
No of
cancell
ed fIts
2402
Noot
Slots
approv
ed
76541
%of
cancellati
on
3.1%
Noof
cancell
ed flts
6394
No of
Slots
approv
ed
188145
25
% of
cancellati
on
3.4%
No of
cancell
ed flts
8796
No of
Slots
approv
ed
264686
% of
cancellati
on
3.3%

- 11\­
ANNEXURE· 6
10 years Histo rical data and forecast for the period FY12 - FY21
ae

UK Civil Aviation Authority Economic Regulation of Heathrow and Gatwlck Airports 2008 ·20 13
CM Decision
Economic Regulation of Heathrow and Gatwick Airports
2008-2013
CAA decision
11 March 2008
Civil Aviation Authority
CAA House, 45-59 Kingsway, London, WC2B GTE

UK CivilAviationAuthority Economic Ragulation of Heathrowand GatwickAirports 2008 -2013
eM Decision
Effect ofEU-US Open Skies - Heathrow
4.24 In, January 2008. ACL published its Heathrow Initial Coordination Report for
Summer 2008. This showed that Summer 2008 would see an increase in planned
seat capacity at Heathrow of 3.1 per cent over Summer 2007 mainly on North
American routes, due to the increase in services brought about by the EU-US Open
Skies agreement. As the transatlantic services that represent this growth tend to
be operated year-round, it can be reasonably assumed that Winter 2008/09 will see
a similar increase in capacity over Winter 2007/08.
4.25 Using country level data from the ACL report and the load factors above, the switch
from short haul to long haul services in2008/D9 can be estimaied to increase the
overall load factor by around 0.2 per cent. However, since many of the new long
haul services will be on only a few US routes, the load factors on these routes may
initially suffer as a result of the large increase in capacity'·. It therefore seems
unlikely that Heathrow will see an Increase in traffic for 2008/09 due to EU-US
Open Skies much above the increase in seat capacity.
Opening ofHeathrow Terminal 5
4.26 Any traffic growth above the 3.1 per cent capacity increase for 2008/09 would have
to arise from increased load factors. CAA estimates suggest.lhatthe load factor for
long haul at Heathrow is currently around 77 per cent, whereas short haul and
domestic load factors are around 70 per cent. These figures do not seem to have
fallen in recent 'years, so increases to load factors in 2008/09 cannotbe assumed to
arise simply from a return to historic levels because, say, security restrictions have
been eased.
4.27 The opening of Terminal 5 and the subsequent relocation of carriers around the
other terminals should in turn make flight connections easier and improve
passenger experience, each of which might be expected to raise average load
factors, other things being equal. However, there are also downside risks to load
factors, such as Terminal 5 not achieving its expected operational efficiencies in its
first year of operation. Also the relocation of airlines amongst the airport's
terminals, which is scheduled to take until October 2008and so might be expected
to have more positive impact on load factors in the later years of Q5, may have an
Initial negative effect on passenger perception.
27 They grew by 0.5 per cent in 2005, fell by 0.3 per cent in 2006, and grew by 0.8 per cent in 2007
28 For example, Table 3.4 of SA's respense to CAA November2007 propesals, estimates that of the 22 new
daily servicesbetween Heathrowand the US in Summer2008,five will serve NewYork, four will serve Houston
and three Dallas.
Chapter4 - Trafficforecasts 41

UKCivi AviationAuthority Economic Regulation of HeathrowandGatwickAirports2008 -2013
CAA Decision
December 2007 compared to the same month in 2006. Consequently, the airport
seems likely to see growth of over 2.5 per cent for the year 2007/08.
4.35 There is no published ACL report for Gatwick showing the effect on capacity of
airlines handing back, selling or leasing slots. However, the airlines and BAA were
near to agreement"" on their traffic forecasts in July 2007, which included the then
assumed effects of both Open Skies and charter consolidation. BAA's published
2007 CIP forecasts, identical to its July 2007 Constructive Engagement forecasts,
included an estimate of the effect of Open Skies and charter consolidation on
Gatwick traffic: a reduction of between 0.5 million and 1.0 million passengers for
each of the years of 05. For 2008/09, the reduction due to Open Skies and charter
consolidation is 0.5 million passengers.
4.36 BAA states" that the amendments to their forecasts made in November 2007 were
mainly due to changed assumptions over the likely passenger figures for 2008/09,
which were reduced by 1.1 million, with the growth rates for the other years of 05
being roughly in line with their July 2007 forecasts. Therefore the following sections
investigate whether the latest information on the effects of Open Skies and charter
consolidation support BAA's revision of their JUly 2007 forecasts for 2008109. An
effect of the order of 1.6 million passenqers" would support the current BAA
position, whereas a figure nearer the original 0.5 million would indicate that the
original constructive engagement forecasts are still suitable.
Effect ofEU-US Open Skies - Gatwick
4.37 Many of the Gatwick airlines have already announced changes to their US
schedules tor Summer 2008 indicating where services have switched to Heathrow
and where remaining services have reduced frequencies or changed aircraft size.
There have also been announcements of new transatlantic services at Gatwick,
with BA adding three services per week to Orlando and Zoom UK adding two per
week each to San Diego and Fort Lauderdale.
4.38 On the assumption that charter services and services to leisure destinations
(Orlando, Tampa, Las Vegas, Miami) will remain at Gatwick, it is possible to
formulate a high and low case for the net effect of Open Skies in terms of
transatlantic capacity lost. Table 4-3 summarises these effects.
30 They agreedon forecastsfor the first twoyears of Q5 and the differencebetweentheir forecastsoverthe
wholeQ5 periodwas only 0.5 per cent.
31 BAAlQ5/600 page74
32 Calculatedby combiningthe 0.5 miliionreduction fromthe 2007CIP and the further 1.1 million reduction from
the November2007amendedforecasls.
Chapter 4 - Traffic forecasls 44

UK CivilAviationAuthority Economic Regulation of Heathrowand GatwickAirports2008 -2013
I eM Decision
Table 4-3 Open skies effect on Gatwlck
High case (000)
Movements Passengers
Services already announced andleisure services
Low case (000)
Movements Passengers
-3.7 -563 -3.7 _563
other services
Carrier Route
Delta JFK -1.0 -156 a a
Delta Others a a a a
Northwest Minneapolis -0.7 -176 a a
US All a -76 a a
BA Atlanta a a a a
Total Effect -5.5 -970 -3.7 -563
Source: CAA
Lostpassengers arecalculated ontheassumption thatcu"sntloadfactors forthe routes BrB maintained
Highcase assumptions:
DeltamovesJFK service to Heathrow, butmaintains others atGalwick
Northwest cancels Minneapolis service
US retains all services butreduced aircraft size
BAretsins Atlanta servIce
4.39 The high case demonstrates a reduction in passengers on transatlantic services
iess than 10 per cent greater than the 0.9 million that BAA has proposed".
However the reduction in movements is around 30 per cent greater than BAA's
assumption, supporting the airllnes view that the implied average passengers per
movement for displaced transatlantic services has been overestimated by BAA.
Gatwick charter consolidation
4.40 BAA has assumed that charter consolidation will result in a reduction of 1 million
passengers and 3,800 movements in 2008/09 over and above that assumed in July
2007 34 • BAA also assumes that some of the charter services that remain at
Gatwick will operate with smaller aircraft in 2008/09, which explains why it assumes
over 260 passengers lost for every movement lost.
4.41 Recent public statements from TUI and Thomas cook" show reductions in
capacity, although they are mainly in short haul services and the companies do not
specify the extent to which Gatwick services are affected. Gatwick airlines in their
response to the CAA's proposals (cf Gatwick LACC and AGC) have suggested that
there is no evidence of charter carriers cutting their Gatwick services, but rather
cuts are concentrated in the regions.
4.42 However, in confidential evidence detailing its conversations with airlines, BAA
claims that the bulk of reductions in charter capacity at Gatwick will be by the
independent operators. CAA estimates based on this evidence suggest that these
33 BAAl05/600, Annex B2.
34 BAAl05/600, Annex B2.
35 Investorday & interimmanagement statement, TUI travel pic, 29 January2008, and Annual results
presentation, ThomasCookgroup pic, 30 January2008.
Chapter4 - Trafficforecasts 45

UK CivilAviationAuthority EconomicRegulation of Heathrowand GatwickAirports 2008 -2013
. eAA Decision
changes could lead to a total fall of 0.75 million passengers and 4,180 movements
in 2008/09 compared to 2007/08.
Gatw/ck backfill
4.43
4.44 In addition, a number of the airlines (easyJet, Gatwick LACC and AOC) claimed
that the slots freed up by transatlantic and charter services at Gatwick will mainly
be used by short haul aircraft based at the airport, which will fly two or more
rotations a day. The implication is that there will be a net increase in passengers
as the single daily rotation of a larger aircraft is replaced by multiple daily rotations
of a smaller one. However, ACL scheduling reports for previous years indicate that
it would be difficult to find free slots at other parts of the day to provide for these
extra rotations, suggesting that the extra slots required would probably displace an
existing service. Therefore, it seems unlikely that many extra flights would be
operated at Gatwick simply due to long haul services being replaced by short haul
services.
4.45 Also, it is not necessary for aircraft using slots vacated by charter or transatlantic
services to fly multiple rotations at Gatwick. A Gatwick-based aircraft could operate
a single rotation to a short haul point and, between the outbound and return flight,
operate one or more rotations to a third airport. Alternatively, an aircraft based at
another airport could operate a single rotation into Gatwick and still be fully utilised
on other routes for the remainder of the day. The particular slots vacated by a
transatlantic service would not be suitable for these operations, but any airline
wishing to use such slots for a short haul service would probably need to exchange
them in order to obtain suitable take-off and landing times.
4.46
ee BAA/QS/600, page 76
Chapter4 - Traffic forecasts 46

Analysis report for Correlation between Passenger and ATM
Objective: To establish relationship between aircraft movements and passenger
Data: Data considered Is Pax ATM & Pax from 2001-02 to 2010-11
Method used : Statistical parameters used like Correlation, R sq
Definations:
Appendix 2
Correlation Coeff(R): It is a measure ofassociation between two variables. RangeofR Is -1 to +1.lfR
is close to -1 then we say that two variableshave negative correlatIon. IfR Is 0, there is no correlation
between two variables. And ifR is +1, the two variablesare highly correlated.
R square: Rsq is defined as the ratio ofExplained variation to Total variation in a data model. An Rsq
value close to 1 indicates that the modelis a goodfit.
SUMMARY STATISTICS
Variables
Domestic Domestic International International Total Pax • Total
Parameters PaxATM Passenger PaxATM Passenaer ATM Passenaer
N (No. of
. Years)
11 11 11 11 11 11
Mean 124,643 12,307,116 45,477 6,738,116 170,120 19,045,232
Std Dev 37,606 4,963,681 13,335 1,493,576 50,606 6,443,683
Correlation 0.98 0.99 0.99
Rsauare 0.96 0.98 0.97
Findings:
Domestic Operations:. Correlation coeff (R) is 0.98 which indicates that there is strong correlation
between ATM and pax.
R square is 0.96 which means that the 96% of variation is explained by the data which once again
indicates that there Is a high correlation between atm & pax.
International Operations :. Correlation coeff (R) is 0.99 which Indicates that there is strong
correlation between atm and pax.
R square is 0.98 which means that the 98% of variation is explained by the data which once again
Indicates that there Is a high correlation between atm & pax
Total:. Correlation coeff (R) is 0.99 which indicates that there is strong correlation between atm and
pax.
R square is 0.97 which means that the 97% of variation is explained by the data which once again
indicates that there 15 a high correlation between ATM & pax

Conclusion:
From above analysis and observations , we can conclude that for both international & domestic
operations, there is a strong correlation between ATMs and Passengers.
Domestic: A unit increase in ATM leads to 130units increase in pax
International: A unit increase in ATM leads to 111units increase in pax
Total: A unit increase in ATM leads to 126units increase in pax

Statement showing increase in Headcount over various years
Appendix 4
Additional Survey,
Inspection team to be
included to make
operational activities more
16 19 40 45 effective and efficient
2 4 5 5 To su ort increase ATMs
34 35 35 35 To su ort increase ATMs
40 49 50 50 Tosu ort increase ATMs
Head count increase as
per CAT 10 operations
Emer en Services 156 177 205 205 re uirement
To support effectively
increase in Airside
Airside & Ground Maint 12 13 15 15 o erations
Operation Area to be
increased to approx,
double in FY '13 and then
by another 20% in FY'14.
Hence proportional
increase in manpower is
En & Maint 106 113 140 150 envisa ed.
Operation Area to be
increased to approx.
double in FY '13 and then
by another 20% in FY'14.
Hence proportional
increase in manpower is
91 91 125 145 envisa ed.
13 13 16 16
Landside 0 erations 11 15 20 20
Operation Area to be
increased to approx.
double in FY '13 and then
by another 20% in FY '14.
Hence proportional
increase in manpower is
envisa ed.
GATerminal 22 32 33 33
Currently team only
managing ASQ. Additional
team to be build to carry
out surveys and research.
Design and Implement
Customer care 3 3 20 35 customer service ro ram.
car 0 114 137 8 8

Operation Area to be
increased to approx.
double in FY '13 and then
by another 20% in FY'14.
Hence proportional
increase in manpower is
20 22 40 40 envisa ed.
4 4 4 4
3 3 4 4
2 3 3 3
2 3 4 4
6 8 9 10
26 34 37 41
27 29 32 35
23 34 37 41
Additional Manpower will
be required to support
new technologies in T2.
Also, the IT support will
have to be increased to
mana e the new terminal
2 2 2 2
22 25 28 31
4 4 4 4
5 5 6 7
Commercial* 16 19 21 23
AT5* 5 5 6 7
Horticulture
4 4 4 4
Staff addition due to
addition in operational
area.
Airport Marketing & Aero
Business* 13 22 24 26
* A 10% increase in Head Count has been taken for Support functions due to increased activities for new
terminal.

Load Details of Additional Load for New Terminal T-2
6500 KVA load on Dec. 2012 for Chiller &.Testing
1) Loads
2) 31150 KVA Loads for New T-2 on Sept.2013
SUMMARY OF LOAD ESTIMATION - T2 BUILDING
SI.No. DESCRIPTION
Appendix 5(A)
C.L
M.D
D.F
{KW} {KW}
1 Lighting 4881 0.9 4393
2 Apron Lighting 503 0.6 318
3
Power sockets
Power sockets (Emeraencv)
3530
1335
0.2
0.9
1032
1202
4 UPS 1875 0.9 1687
5 HVAC
a.AHU.HRW 4751 0.8 3801
b. VENTILLATION 2390 0.8 1912
c. Life safety ventilation 1202 0.0 0
6 Plumbina 950 0.8 760
7 Fire Protection 334 0.0 0
8 MECHINAL EQUIPMENT
I) Travel
a. Lifts 1840 0.7 1288
b. Escalators & Travellators 970 0.8 776
IIlBHS 5633 0.7 4089
9 Tenant,M 9 Area 3484 0.7 2461
10 Retail 1528 0.7 1077
11 Food And Beverage 1661 0.7 1164
12 PCA 4923 0.6 3191
13 GPU(400 Hz) 5328 0.6 3454
14 PBB Gate Bridges 1560 0.5 780
15 CAR PARK, CONNECTORBRIDGE 378 0.8 302
16 GATE NO.5 &6 250 0.8 200
Total 49305 33886
Connected Load {KW} 49305 KW
Maximum Demand {KW} 33886 KW
Maximum Demand {KVA} 37651 KVA

Contract Demand for Surrender at New Terminal (T2) (7 MVA)
Load of existing T2 & CARGO
51 T-2 Connected Cargo Connected
no Details Loads Loads Total
1 Airconditioninq 7900.16 483.16 8383.32
2 Conveyors 411.56 0.00 411.56
3 Cold storaoes 0.00 229.74 229.74
4 DATA Centre 56.12 0.00 56.12
5 Elevators & escaltors 173.14 102.69 275.84
6 Lightings 2376.51 409.10 2785.61
7 Aerobrldqes 908.04 0.00 908.04
8 Pumps 529.18 529.91 1059.09
9 Misc. loads 390.80 113.41 504.21
10 X-rav 61.95 34.34 96.30
14709.8
Total 12807.45 1902.37 2
DF 55% 55% 55%
Max Demand 7044.10 1046.30 8090.40
Max Demand
T-2 7044.10 KVA
Carco 1046.30 KVA
Air India 400 KVA
IOC 950 KVA
Total 9440.40 KVA
Contracted Demand
Max Demand will be remained after Sept.2013
9500 KVA
Carqo 1046 KVA
Air India 400 KVA
IOC 950 KVA
Total 2396 KVA
Say Max Demand to be
retained 2500 KVA
Contract Demand for surrender 7000KVA on April 2013

Regulatory Asset Recovery ordered by Hon'ble MERe
Appendix 5(8)
FY08 FY09 FY 10 (Upto
October
2010)
Incremental Revenue GAP . 95.6 1015.41
Requlatorv Assets (aonroved) . 178 554
Imoact of ATE Order 90.7 - -
Impact of Adjustment of Consumer 23.15 - -
Contribution and Additional Capitalisation
Total Rs. Crs. 113.85 273.6 1569.41
Prooortionate RA 915.49
% shareof MIALconsumotion 1.09% 1.04% 1.00%
MIALConsumotion 86.32 85.93 49.71
R-infra D consumotion 7912 8270 4,975
1.24 . 2.84 9.15
(in Rs. Crs.) FY08 FY09 FY 10 FY 11 FY 12 FY 13 FY 14 FY 15
Opening
Balance (a) - 1.32 4.51 14.77 16.51 16.82 11.47 5.28
Add:
Additions in
RA (b) 1.24 2.84 9.15 - - - - -
I nterest
Rate (5BI
PLR) (c) 12.25% 12.75% 12.25% 11.75% 13.00% 14.75% 14.75% 14.75%
Add:
Interest
{(a+b/2)*c} 0.08 0.35 1.11 1.74 2.1B 2.13 1.28 0.33
Less:
Repayment
with
Interest - - - - 1.87 7.4B 7.48 5.61

UK Civil Aviation Authority Economic Regulallon of Heathrow and Gatwick Airports 2008 ·2013
CM Decision
Economic Regulation of Heathrow and Gatwick Airports
2008-2013
eAA decision
11 March 2008
Civil Aviation Authority
CAA House, 45 59 Kingsway, London, WC28 GTE

UK Civil AviationAuthority Economic Regulation of Heathrow and Galwick Airports 2008 -2013
eM Decision
4.28 Such factors and risks are difficult to quantify in terms of their effect on load factors.
However, the CAA believes that, for 2008/09, the potential for increases in load
factor due to Terminal S only just outweighs the potential for decreases.
4.29 Therefore, taking into account the latest passenger traffic at Heathrow, which
suggests a slightly higher outtum for 2007/08 than the CAA expected in lts
November 2007 proposals, and the Increase in planned seat capacity for Summer
2008 of 3.1 per cent over Summer 2007, as recently reported by ACL, the CAA
considers that BAA's forecast for 2008/09 of 70.4 million passengers, a 3.6 per cent
increase on 2007/08 , now represents a more likely outcome than either its own
November 2007 forecast or the airlines' proposed forecast. As a consequence of
the increased traffic In 2008109, the CM also considers that its forecast for 2009/10
should be increased to 72.5 million passenqers" .
Longer term outlook - Heathrow
4.30 The effect of the Open Skies agreement is unlikely to be restricted solely to
2008/09. bmi has previously stated its intention to begin transatlantic operations
from Heathrow after Summer 2009, and it is likely that there will be further
increases in frequency from the other network carriers throughout 05.
4.31 It is also reasonable to assume that the average aircraft size and mix of long haul
and short haul services will change, and the longer term effects of the opening of
Terminal 5 and the subsequent re-Iocation of carriers should increase average load
factors at Heathrow. However, no new evidence on the magnitude of these effects
has arisen to justify moving away from the CAA's November 2007 forecasts in the
later years of 0 5.
4.32 However, as noted in footnote 22, the CAN s November forecasts for Heathrow
were expressed to the nearest 0,5 million passengers. Since the effect of this
rounding was to reduce the traffic forecast in the latter two years of Q5, the CAA
does not consider such rounding accurately reflects the likely annual growth rates
between 2010/11 and 2012/13. Consequently, the forecasts for 2011/12 and
2012/13 have been increased slightly.
Gatwick - current trends in passenger numbers
4.33 In contrast to Heathrow, passenqer numbers at Gatwick have been grOWing
steadily since the middle of 2004, although the airport is becoming increasingly slot
constrained. Figure 4-3 and Figure 4-4, respectively, show the twefve-month roiling
average for terminal passengers at Gatwick and the year-an-year growth rates that
they represent. The figures also show the BAA and airline forecasts and the growth
rates required to achieve them.
29 If the 2009/1 0 forecasl remained as 72.0 million passengers, this would imply a growth rate of only 2,3 per
cent compared 103.6 per cent in 2008109 and 3.5 per cent In 2010/1 1.
Chapter" - Traffic forecasts 42

UK Civil Aviation Authority Economic Regulation of Heathrow and GatwickAirports 2008 -2013
eM Decision
December 2007 compared to the same month in 2006. Consequently, the airport
seems likely to see growth of over 2.5 per cent for the year 2007/08.
4.35 There is no published ACL report for Gatwfck showing the effect on capacity of
airlines handing back, selling or leasing slots. However, the airlines and BAA were
near to agreemene o on their traffic forecasts in July 2007, which included the then
assumed effects of both Open Skies and charter consolidation. BAA's published
2007 CIP forecasts, identical to Its July 2007 Constructive Engagement forecasts,
included an estimate of the effect of Open Skies and charter consolidation on
Gatwick traffic: a reduction of between 0.5 million and 1.0 million passengers for
each of the years of 0 5. For 2008/09, the reduction due to Open Skies and charter
consolidation is 0.5 million passengers.
4.36 BAA states" that the amendments to their forecasts made in November 2007 were
mainly due to changed assumptions over the likely passenger figures for 2008/09,
which were reduced by 1.1 million, with the growth rates for the other years of 0 5
being roughly in line with their July 2007 forecasts. Therefore the following sections
investigate whether the latest infonnation on the effects of Open Skies and charter
consolldatlon support BAA's revision of their July 2007 forecasts for 2008/09. An
effect of the order of 1.6 million passenqers" would support the current BAA
position, whereas a figure nearer the original 0.5 million would indicate that the
original constructive engagement forecasts are still suitable.
Effect ofEU-US Open Skies - Gatwick
4.37 Many of the Gatwick airlines have already announced changes to their US
schedules for Summer 2008 indicating where services have switched to Heathrow
and where remaining services have reduced frequencies or changed aircraft size.
There have also been announcements of new transatlantic services at Gatwick,
with BA adding three services per week to Orlando and Zoom UK adding two per
week each to San Diego and Fort Lauderdale.
4.38 On the assumption that charter services and services to leisure destinations
(Orlando, Tampa, Las Vegas, Miami) will remain at Gatwick, it is possible to
formulate a high and low case for the net effect of Open Skies in terms of
transatlantic capacity lost. Table 4-3 summarises these effects.
30 They agreed on forecasts for the first two years of Q5 and t e difference between their forecasts over the
Whole 0 5 period was only 0.5 par cent.
31 BAAlQ51600 page 74
32 Calculated by combining the 0.5 million reduction from the 2007 CIP and the further 1.1 million reduction from
the November 2007 amended forecasts.
Chapter 4 - Traffic forecasts 44

Analys is report fo r Correlation between Passenger and ATM
Objective : To establish relationship between aircraft movements and passenger
Data : Data considered is Pax ATM & Pax from 2001-02 to 2010-11
Metho d ysed : Statistical parameters used likeCorrelation, R sq
Detinations:
Appendix 2
Correlation Coeff(R): I t is a measure ofassociation between two variables. Range of R Is -1 to +1.lfR
Is close to -1 then we say that two variables have negative correlation. IfR is 0/ there is no correlation
between two variables. AndIfR Is +1/ the two variables are highly correlated.
R square: Rsq Is defined as the ratio ofExplained variation to Total variation in a data model. An Rsq
value close to 1 Indicates that the model is a good fit.
SUMMARY STATISTICS
Variables
Dom estic Domestic Int ernational I nternational Tota l Pax , Tota l
Parameters PaxATM Passenger PaxATM Passenger ATM Passenger
N (N o. of
Years)
11 11 11 11 11 11
Mean 124,643 12,307,116 45,477 6/738,116 170,120 19,045,232
5td Dev 37/606 4/963/681 13/335 1,493,576 50,606 6,443/683
Correlation 0.98 0.99 0.99
Rsquare 0.96 0.98 0.97
Findings:
Domestic Operations:. Correlation coeff (R) is 0.98 which indicates that there is strong correlation
between ATM and pax.
R square is 0.96 which means that the 96% of variation is explained by the data which once again
Indicates that there is a high correlation between atm & pax.
International Operations :. Correlation coeff ( R) is 0.99 which indicates that there is strong
correlation between atm and pax.
R square is 0 .98 which means that the 98% of variation is explained by the data which once again
IndIcates that there is a high correlation between atm & pax
Total :. Correlation coeff (R) Is 0.99 which indicates that there is strong correlation between atm and
pax.
R square is 0.97 which means that the 97% of variation is explained by the data which once again
indicates that there is a high correlation between ATM & pax

Conclusion:
From above analysis and observations , we can condude that for both international & domestic
operations, there is a strong correlation between All4s and Passengers.
Domestic: A unit increase in ATM leads to 130 units increase in pax
International: A unit increase in ATM leads to 111 units increase In pax
Total: A unit Increase in All4 leads to 126 units increase in pax

Security 20 22 40 40
Operation Area to be
Increased to approx.
double in FY '13 and then
by another 20% in FY '14.
Hence proportional
increase in manpower is
envisaged.
MD's Office 4 4 4 4 -
President's Office
Strateov DIvision
Reouletorvt
3
2
2
3
3
3
4
3
4
4
3
4
-
-
-
leqal*
Finance & Accounts*
6
26
8
34
9
37
10
41
-
-
Human Resources* 27 29 32 35 -
Information Technology
l and Manaaement
Corporate Relatlon*
Environment
COrporate Communrcatron*
Commercial
23
2
22
4
5
16
34
2
25
4
5
19
37
2
28
4
6
21
I
41
2
31
4
7
23
Additional Manpower will
be required to support
new technologies in n .
Also, the IT support will
have to be Increased to
menace the new terminal
-
-
-
-
-
ATS* 5 5 6 7 -
Horticulture 4 4 4 4
Staff addition due to
addition in operational
area.
Airport Marketing & Aero
Business* 13 22 24 26 -
..lIU,,.,. em 0Ml HOUJ rnTII!I
$Does not include outsourced headcount
'" A 10% increase in Head Count has been taken for Support functions due to increased activities for new
terminal.

Contract Demand for Surrender at New Terminal (T2) (7 MVA)
Load of existing T2 & CARGO
51
no Details
T-2 Connected
Loads
Cargo Connected
Loads Total
I
1 Alrconditioninq 7900.16 483.16 8383.32
2 Conveyors 411.56 0.00 411.56
3 Cold Storages 0.00 229.74 229.74
4 DATA Centre 56.12 0.00 56.12
5 Elevators & escaltors 173.14 102.69 275.84
6 Lightinqs 2376.51 409.10 2785.61
7 I Aerobridces 908.04 0.00 908.04
8 Pumps 529.18 529.91 1059.09
9 Misc. loads 390.80 113.41 504.21
10 X-ray 61.95 34.34 96.30
14709.8
Total 12807.45 1902.37 2
OF 55% 55% 55%
Max Demand 7044.10 1046.30 8090040
Max Demand
T-2 7044.10 KVA
Cargo 1046.30 KVA
Air India 400 KVA
I OC 950 KVA
Total 9440.40 KVA
Contracted Demand 9500 KVA
Max Demand will be remained after Sept.2013
Carqo 1046 !

Regulatory Asset Recovery ordered by Hon'ble MERC
Appendix S{B)
FY08 FY09 FY 10 (Upto
October
2010)
I ncremental Revenue GAP - 95.6 1015.41
Reoulatorv Assets (approved) - 178 554
Impact of ATE Order 90.7 - -
Impact of Adjustment of Consumer 23.15 - -
Contribution and Additional Capltallsation
Total Rs. crs, 113.85 273.6 1569.4 1
Proportionate RA 915.49
% share of MIAL consumption 1.09% 1.04% 1.00%
MIAL Consumption 86.32 85.93 49.71
R-infra D consumption 7912 8270 4, 975
1.24 2.84 9.15
(in Rs. Crs.) FY08 FY09 FY 10 FY 11 FY 12 FY 13 FY 14 FY 15
Opening
Balance (a) - 1.32 4.51 14.77 16.51 16.82 11.47 5.28
Add:
Additrons In
RA (b) 1.24 2.8 4 9.15 - - . - -
Interest
Rate (581
PLR) (c) 12.25% 12.75% 12.25% 11.75% 13.00% 14.75% 14.75% 14.75%
Add:
Interest
{(a+ b/2)*c} 0.08 0.35 1.11 1.74 2.18 2. 13 1.28 0.33
Less:
Repayment
with
Interest - - - - 1.87 7.48 7.48 5.61

MAHARASHTRA ELECTRIClTY REGULATORY COMMISSION
World Trade Centre, Centre So.I, 13th Floor, CuITe Parade, !\lumbai 400 005.
1'01. )1;0. 022 22163964/65/69 - Fu 022 22163976
E-mail: merc in.l;a(.;

- Jb7­
Total Energy - billed to change-over and sales to
own consumers (MU)
Wheeling charges for use of Rlnfra-D System for
FY20 10-11
1046.92 8188.76
0.62 1.19
Rlnfra-D requested the Commission to consider separate truing-up of Wires cost and Retail
Supply costs ofthe distrib ution licensee.
RIn fra-D submitted that the un der-recovery in Wires cost cou ld be determined using the ' per unit
allocated wires cost' and actual sales of each category and comparing the sum -product of these
with the actual Wires cost, represented mat hematically as under:
(Actual Distribut ion Wires costs) - (WH *SHT + WLT*SLT),
where, WBT is the allocated per unit wires cost at HT level (or wheeling charges at HT level);
SHT is the energy in MU at HT level, which is the sum of actual doorstep sales of own
consumers and actual energy billed to change-over consumers; WLT is the allocated pe r unit
w ires cost at LT level (or wheeling charges at LT level); and SLT is the energy in MU at L
level.
he Commission will bear this suggestion of Rlnfra-D in mind, at the time of truing up for FY
20 I0- 11. However, the Commission has not re-determined the Wheeling Charges for FY 20 IO­
11, since the year has been co mpleted.
6.2.2 Cost and arif" unbundling
Rlnfra-D submitted that change-over consumers use Wires Distribution Licen see ' s network and
Supply Distribution Licen see ' s supply, while own consumers usc both network and supply of the
same DistributionLicensee. Hence, cost of netwo rk and losses, which are different for different
networks, needs to be identified separately for o,,,'n consumers and change-over con sumers.
Rlnfra-D added that when cost elements are identified separately, cost allocated to own
consumers and change- ve l' consumers wo uld be different due to different network cost and
different loss es o f the two licensees. Consequently, the tariffs of the two types of con sumers
would also be different to the exten t ofdifference in allocate d cost.
Rlnfra-D proposed that going forward for parallel licence areas, such cost and tariff unbundling
may be considered by the Commission to ensure fair allocation of cos ts and tariffs representing
actual cost incidence.
172

These issues are being addressed separately under parallel licensing framework, and are not
relevant for the present exercise of determining the ARR for FY 2010-I 1.
6.3 RCOVERY OF REGULATORY ASSETS AND PAST REVENUE GAPS
RInfra-D submitted that large numb ers of consumers have migrated to TPC-D in FY 2010-1 I
itself, and Rlnfra-D would be left with a smaller consumer base to recover the regulatory assets
shown above, which include the un-recovered power purchase cost of the previous years . Rlnfra­
D added that as more and more consumers migrate, the impact of these regulatory assets and past
revenue gaps in Rs. per kWh terms would keep on leap-fragging. Rlnfra-D added that these
regulatory assets have been created mainly on account of power purchased to meet the demand
ofits customers, including all those customers who have migrated and would migrate to TPC-D.
Also, due to the stay on tariffs, Rlnfra-D could not recover the cost, which ought to have been
recovered from the consumers. Rlnfra-D added that unless the Commission appropriately
allocates the cost on existing and migrated consumers, migrating consumers will not see the
impact of these regulatory assets, even though these costs have been incurred to provide supply
to such consumers also. Rlnfra-D fu rther submitted that recovering these costs from a smaller set
of consumers would increase the tariff impact on the remaining consumers. Rlnfra-D requested
the Commission to prescribe a charge leviable on all consumers connected to Rlnfra-D system ­
whether own or migrated - so that migrating consumers bear their fair share of past costs of
Rlnlra-D. Rlnfra-D submitted that it would propose recovery of the above past regulatory assets
spread over a period of 3 to 5 years starti ng FY 20 11 -12 in, the subsequent MYT Petition.
In this regard, Rlnfra-D had filed Appeal No. 200 of 2010 before the Hon'b le -Appcllate Tribunal
for Electricity CA PTEL), seeking directions upon the Commission to consider the two important
issues relating to the cross-subsidy surcharge and regulatory assets from change over consumers in
the tariff pro ceedings. In its Ord er dated March I, 20 I I, the APTEL he ld as follows:
"The learned counselfor the Commission would submit that in respect of(he reg ulatory
assets, subject to the availability ofthe material on record, the Commission will decide
the same ill the tariffproceedings. In respect ofcross-subsidy surcharge, it is submitted
that there is some proposal to frame Open Access Regulations, 2011 and therefore, this
issue may be decided subsequent to F uming ojthe Regulations. Be that as it may, now it
is submitted that the petition fo r ARR 2011 has been admitted and the same is pending
before the Commission.
173

In the circumstances of the case, we deem it appropriate to direct the Commission to
consider the smile in the light of the statement made by the learned counsel for the
Commission within J20 days either fro m the date ofadmission orfrom today , whichever
is earlier.
The Commission may decide the same after hearing all the parties concerned including
the other respondents. I I
From the above, it is see n that Rlnfra-D has not actually proposed the detailed rationale and
method for recovery of the regulatory assets from consum ers who have migrated/would be
migrating, and has only sought recovery of the regu latory assets [rom all the consume rs who are
connected to Rlnfra-D system. Also, Rlnfra-D has not prop osed the exact manner in which the
regulatory assets will be recovered ov er a period of3 to 5 years. All these aspects would become
clear only when RInfTa-D actually proposes the charges in its Mr"T Petition. As a result, the
consumers have also found it difficult to assess the impact of Rlnfra-D's request to recover the
regulatory assets from consumers who have migrated/would be migrating . However, in response
to Rlnfra-D's proposal, several consumers have put forth their comments and suggestions on the
same, as captured in Section 2. 18 ofthis Order, and as summarised below:
a) Several stakeholders objected to the recovery ofpast regulatory assets from already migrated
consumers, based on the followi ng premise
i) There is 110 provision in the EA 2003, which entitles a distribution license to claim its
past revenue gaps from someone who is no longe r its consumer for supply of
electricity.
ii) If a new consume r can be charged towards recove ry of past revenue gap by reason of
being a consumer of the distribution licensee at the time of recovery, then by the
same logic a person who is no longer the consumer of the licensee at the time of
recovery, cannot be called upon to pay towards past revenue gaps.
iii) The deterred revenue gap is the outcome of inefficient operations of Rlnfra- D inspite
of directives by the Commission to execute long term PPA, and hence, the
consumers should not be asked to pay for the distribution licensee's co nsistent
failure,
b) On the other hand, quite a few consumers submitted thal migrat ing consumers should also
bear their share ofpast cos ts as proposed by Rln fra-D, while other consumers submitted that
the Commission may issue a methodology in the interest of the sma ll consumers and not
burden them by recovery of the huge regulator y asset of Rlnfra-D .
174

- :17'1 ­
ii) Group II: will have to pay the charges for recovery of regulatory assets, since they
conti nue to be consume rs of Rlnfra-D for Wires
iii) Group IH: will not have to pay the charg es for recovery of regulatory assets, since
they are no longer consumers of Rlnfra-D, either for Wires or Supply, and
charges can be levied by a licensee onl y on a 'consumer'.
Accordi ngly, Rlnfra-D should propose recovery of the regulatory asset from Group I and Group
II consumers, in the subsequent years.
6.4 LOSS OF CROSS-SUBSIDY
Rlnfra-D submitted that in FY 2009-10, there has been about 208 MU of reduction in sales due
to consumer chan ge-over to TPC-D. This number will increase to 1278 MU in FY 2010-11,
which is also an estimate as already approved by the Commission and the actual number is
expected to be larger. Rlnfra-D observed that the majority of this migrated sale comes from
subsidising industrial and commercial consumers, with sales to subsidized domestic category
forming only about 13% of total change-over sales.
Rlnfra-D added that the actual migration till date as well as that approved and recognized by the
Commission make s it apparent that the consumer base of Rlnfra-D will constitute increa singly of
low-end subsidized consumers. This class of consumers forms the most price-sensitive category
with the lowest paying capacity and these consumers will bear the burden of loss of cross­
subsidy on account of migration of subsidizing consumers of Rlnfra-D. Rlnfra-D submitted that
such an eve ntuality can, however, be averted if the Comm ission prescribes a Cross-Subsidy
Surcharge to recover loss ofcross-subsidy from migrating consumers.
Rlnfra-D added that it had filed a Petition (Case o. 7 of 2010) before the Commission to
prescribe a Cross-Subsidy Surcharge to recoup the loss of cross-subsi dy from migrating
consumers. Rln fra-D had requested for an in-principle approval of the Surcharge, with actua l
numbers being decided after submissio n of the ARR Petition. The Commission, while disposing
off the Petition, stated in its Order that it shall consider the issue of cross-subsidy toss at the time
of filing ofARR Petition by Rlnfra-D, and did not provide in-p rincip le approval to application of
Surcharge.
Rlnfra-D requested the Commission to prescribe a Cross -Subsidy Surcharge (eSS) on migrating
consumers, and proposed the methodology for dctennination ofCSS as under:
177

orth Delhi Power Limited Mu lti Year Tariff Order (FY08 - FYll)
4. 139 The capitalisation of A&G Exp enses has been discussed la ter in the Order in
section "Capitalisation of Expen ses and Intere st charges".
4. 140 The summa ry of A&G Expenses as approved by the Com mission is given in the tab le
below.
TableS: Approved A&G Expenses for the Control Period (Rs Cr)
Pnrtlculurs Base Year FYUS FYU9 FY10 rvu
Index{n)1 Index (n-l) 1.0415 1.041 5 1.0415 1.0415
Toeal ..... &0 Expenses 29.69 30.92 32.21 33.54 34.94
Less: Cupltalisation 0.00 0.00 0.00 0.00 0.00
Net A&G Expenses 29.69 30.92 32.21 33.54 34.94
Allo cation illto Wheeling and Retail Supply
4.141 For the purpose of allocating the A&G cost approved above, the Commission has
considered the follow ing approach:
(a) The Commission has rust allocated the A&G expenses approved into differe nt
heads, in the same proportion of value under the respective head to the total
A&G expenses submitted by the Petitioner the respective year (Table 78).
(b) Therea fter, the Commission has allocated the expenses of each component
into Wheelin g and Retail Supply business bused on the allocation statement
submitted by the Petitioner (Table 79).
4. I42 The Summary of the A&G cos t approved by the Com mission for Wheelin g and Retail
Supply business is sho wn below.
Table 82: Approved Allocation of A&G Cost (Rs, Cr)
Repairs and Maintenance (R&l\1) Expenses
Petitioner's Submission
4. 143 The Petitioner has submitted the R&M expenses for the Control Period as Rs. 67.02
Cr. Rs. 68.96 o . Rs. 7 1.99 Cr and Rs. 75.99 Cr for FY08. FY09, FY 10 and FY I I
respectively. The Pet itioner has projected the R&M expense at 2.5% of Openin g
GFA plus 1.5% to 2% of the incremental capital expenditure duri ng the year.
4.1 44 The Petitioner has also submitted the allocu tion of total R&M expenses in differe nt
head and [he alloca tion of these respective heads into Wheeling and Retail Supply
Delhi Electricity Regulatory Commission Page 140
•
the
February 2008

1. 77­
North Delhi Power Limited Multi Year TarilT Order (FY08 - FYll)
business. The allocation statement pro posed by the Petitioner is give n In the table
below.
Table 83: Alloca tion of R&i\'1 ixpeuses into diffe rent R&M hea ds
Purl leuIIIrs Allocution (% )
Stores & Spares
Street Light
0
19,11%
2 45%
Building 2.61%
Computer/Off Equip/Other 17.52%
Meter/Street Light 2.72%
Automatic MeterRending Bxpenses 4.74%
Meter Rending Ex.penses 6.81%
Cull Centre charges
2.63%
Others 41.42%
abl e 84: Stateme nt of Allocation of R&M Exp enses be tween Wheeling & Retai l Supply Busin ss
I'm·ticulm-s Whl'Cling Retail Supply
Stores & Spares 100% 0%
Street Li ght 0% 100%
Building 60% 40%
Computer/Off Equip/Other 60% 40%
Meter/Street Light 0% 100%
Automutic Meter Reading Expenses 0% 100%
Meter Reading Expenses 0% 100%
Call Centre charges 0% 100%
Others 60% 40%
4.145 The table be low summarises the proposed R&M Expenses submitted by the Petitio ner
for the Control Period,
Ta ble 85: Proposed R&M Expenses for the Control Peri od (Rs Cr)
Part leulnrs FY08 FY1I9 F'Y 10 rv u
R&MTol ul 67.02 68.96 71.99 75.99
R&M - Wheeti ng 51.33 5 1.10 52.79 53.40
R&M - Retall SUPI)I)' 15.69 17.86 19.20 22.59
Commission's Analysis
4.146 The Co mmission observe. thai the Pet ition er has not followed the met hodology
specified in the MYT Distribution regula tions for calc ulation of R&M expenses for
the Con trol Period. The Co mmission has, however, determined the R& I expen e for
the Contro l Period using the same methodology as specified in the M YT Regulat ions,
2007.
Delhi Electricity Regulatory Commission Page 141
February 2008

ComputatIon of OF Peri od at Allowed Rate
Appendix 7
Dec Jan Feb Ma r FY12 Apr M ay Jun Jul Aug Sep Oct Nov Dec Jan Feb M ar FY13
No. of Days 31 31 28 31 30 31 30 31 31 30 30 30 31 31 28 31
No. of Departing Passengers
Domestic (Mn) 0.9 0.9 0.9 0.9 10.9 0.9 0,9 0.9 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 11.6
Internationa l (M nl 0.4 0.4 0.4 0.4 4.7 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 4.8
Total (M n) 1.3 1.3 1.3 1.3 15.6 1.3 1.3 1.3 1.4 1.4 1.4 1.4 1.4 1.4 1.4 1.4 1.4 16.4
Growth Rat e 0.0 16.4
Domest ic (%) 0.53 0.53 0.53 0.53 0.53 0.53 0.53 0.53 0.53 0.53 0.53 0.53 6.50
Int em atlo nal (%} 0.28 0,28 0.28 0.28 0.28 0.28 0.28 0.28 0.28 0.28 0.28 0.28 3.42
Coll ection Charge
Domestic (Rs./pax) 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5
Intern ational (Rs./pax) 5 5 5 5 5 5 5 5 S 5 S 5 5 5 5 5 5 5 5
Collection %age {%} 90% 90% 90% 90% 90% 90% 90% 90% 90% 90% 90% 90% 90% 90% 90% 90% 90% 90% 90%
Required Rate of DF
Dome stic {Rs./paxl 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200
Intern ational (Rs./pClX) 1860 1860 1860 1860 1860 1860.1 1860 1860 186 0 1860 1860 1860 1860 1860 1860 1860 1860 1860 1860
Net DF Collect ion {Rs. Cr.} 2834.6 81.2 81.2 81.2 81.2 324.9 83.0 83.2 835 83.8 84.1 84.3 84.6 84.9 85.2 85.5 85.7 86.0 1013.8
All owed Rate of OF
Domestic (Rs./p
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Apr M ay Jun lui Aug Sep Oct Nov Dec lran Feb M ar FY14
No. of Days 30 31 30 31 31 30 30 30 311 31 28 31
No. of Departi ng Passengers I
Domesti c (Mn) 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1 1.0 1.0 1.1 12.3
Internatio nal (M n)
0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 1 0.4 0.4 0.4 5.0
TOlal (M n) 1.4 1.4 1,4 1.4 1.4 1.4 1.4 1.4 1.51 1.5 1.5 1.5 17.3
Growth Rate I
17.3
Domestic (%)
0.48 0048 0.48 0.48 0.48 0.48 0.48 0.48 0.48 1 0,48 0.48 0.48 5.91
Interna tional (%) 0.24 0.24 0.24 0.24 0.24 0.24 0.24 0.24 0.24 0.24 0.24 0.24 2.92
Collection Charge
Domestic (Rs';pax) 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5
Int ernat ional (Rs./pax) 5 5 5 5 5 5 5 5 5 5 5 5 5 5
Collecti on %age
(%) 90% 90% 90% 90% 90% 90% 90% 90% 90% 90% 90% 90% 90% 90%
Requi red Rate of OF
Dom estic (Rs./pax) 200 200 200 200 200 200 200 200 200 200 200 200 200 200
International (Rs./pax) 1860 1860 1860 1860 1860 1860 1860 1860.1 1860.1 1860.1 1860.1 1860.1 1860.1 1860.102
Net OFCollection
(Rs. Cr.) 2834.6 86.1 86.3 86.6 86.8 87.1 87.3 87.6 87.8 88.1 88.4 88.6 88.9 1049.6
Allow ed Rate of OF
Domestic
Intern atio nal
Net OF Collection
Defi dt required as Loan
(Rs./pax) 200 200 200 200 200 200 200 200 200 200 200 200 200 200
(Rs./pax) 1300 1300 1300 1300 1300 1300 1300 1300 1300 1300 1300 1300 1300 1300
(Rs. Cr.) 3016.2 65.4 65.6 65.8 66.0 66.2 66.5 66.7 66.9 67.1 67.3 67.5 67.7 798.7
(Rs. Cr.)
20.6 20.7 20.7 20.8 20.8 20.9 20.9 21.0 21.0 21.1 21.1 21.2 250.9
Computation of Interest on Securltised loan
Opening Loan 350.8 375.1 399.8 424.7 450 .0 475.7 SOl.4 527.5 553.9 580.8 608.0 635.0 350.8
Addl tions to l oan
20.6 20.7 .20.7 20.8 .20.8 20.9 20.9 21.0 21.0 21.1 21.1 21.2 250.9
Total Lo an
371.4 395.8 420.6 445.5 470.9 496.5 522.4 548.5 575.0 601.9 629.2 656.2 601.7
Add : Interest on Loan
12% 3.7 4.0 4.1 45 4.8 4.9 5.2 5,4 5.9 6.1 5.8 6.7 61.1
Less: Repayment
Closing Loan aft er Interest
No. of Day for interest/OF
375.1 399.8
424.7 450.0 475.7 501,4 527.5 553.9 580.8 608.0
635.0 662.8
662.8
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Apr May Jun Jul Aug Sep Oct Nov Dec Ja n Feb Ma r FYlS Apr May Jun
No. of Days 30 31 30 31 31 30 30 30 31 31 28 31 30 31 30
No. of Departing Passengers
Domestic (Mn] 1.1 1.1 1.1 1.1 1.1 1.1 1.1 1.1 1.1 1.1 1.1 1.1 12.9 1.1 1.1 1.1
Int ern ational (Mn) 0.4 0.4 0.4 0.'1 0.4 004 0.4 0.4 0.4 0.4 0.4 0.4 5.1 0.4 0.4 0.4
Total (M n) 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5 18.0 1.5 1.5 1.5
Growth Rate 18.0
Domestic (%) 0.40 0.40 0.40 0.40 0.4 0 DAD DAD 0.40 DAD 0040 DAD 0.40 4.92 0.34 0.34 0.34
Inter nat ional (%) 0.20 0.20 0.20 0.20 0.20 0.20 0.20 0.20 0.20 0.20 1 0.20 0,20 2.37 0.16 0.161 0.16
Collection Chi!rge
Dome stic (Rs./pax) 2.5 2.S 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2..5 2.5 25 2.5 2.5
Inte rnation a l (Rs./pax) 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5
Collect ion %age (%) 90% 90% 90% 90% 90% 90% 90% 90% 90% 90% 90% 90% 90% 90% 90% 90% 90%
Required Rate of OF
Domestic (Rs./pax) 2.00 200 200 200 200 200
Int e rnational (Rs./pax) 1860 1860.1 186 0.1 1860 1860.1 1860.1
Net OF Collection
Allowed Rate of OF
(Rs. Cr.) 2834.6 88 .8 89.0 89.3 89.5 89.7
Do mestic (Rs./ pax) 2.00 200 2.00 200 2.00 200 ZOO ZOO 200 200 20 0 200 200 200 l aO 200 200
Int e rna tiona l (Rs./ pax) 1300 1300 1300 1300 1300 1300 1300 1300 1300 1300 1300 1300 1300 1300 1300 1300 1300
Net OFCollectio n (Rs. Cr.) 3016.2 67.7 67.8 68.0 68 .2. 68.3 68.5 68.7 68.9 69.0 69.21 69,4 69.6 823. 2 69.5 69.7 69.8
Deficit re quired as Loan (Rs. Cr.) 21.2 21.2 21.3 21.3 21.3
Comp utation of Inte rest on Securitlse d Loa n 1
Ope ning Loan 662 .8 690,8 719.2 747.8 776.9 806,4 745.9 684.5 622.4 559.7 496.2 431.4 662.8 366.3 30 0.3 233.7
Additions to Loan
21.2 21.2 21.3 21.3 21.3 0.0 0.0 0.0 0.0 0.01 0.0 0.0 106.3 0.0 0.0 0.0
Total Loan
684 .0 712 .0 740.5 769.1 798.3 806.4 745.9 684.5 622 .4 559 .71 496. 2 431.4 76 9.1 366.3 300.3 233.7
Add: Interest on Loan
12% 6.7 7.3 7.3 7.8 8.1 8.0 7.4 6.8 6.3 5.71 4.6 4.4 80.4 3.6 3.1 2.3
Less: Re payment
68.5 68.7 68.9 69.0 69.21 69,4 69.6 483.2 69.5 69.7 69.8
d osing Loan aft e r Interest
690.8 719.2 747.8 776.9 806,4 745.9 684.5 622.4 559.7 496.2 431.4 366.3 366.3 300.3 233.7 166.2
No. of Day fo r Interest/ DF
30 30 30 31 31 28 31
30 31 3D
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