Programm Photovoltaik Ausgabe 2008 ... - Bundesamt für Energie BFE
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Programm Photovoltaik Ausgabe 2008 ... - Bundesamt für Energie BFE

Programm Photovoltaik Ausgabe 2008 ... - Bundesamt für Energie BFE Programm Photovoltaik Ausgabe 2008 ... - Bundesamt für Energie BFE

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29.09.2012 Views

7/9 c-Si reference cell for the measurement of the irradiance. Even better would be to have reference devices using the same technology. Pyranometer values lead to errors larger than 4%. (3) The characterisation approach with the sun-tracker requires a separate determination of NOST, due to the fact that a limited number of data at different irradiances and temperatures are available by tracking the sun. (4) Single day data of high resolution (1 minute intervals) are sufficient to determine the power matrix when applying the equations 1 and 2 of the matrix method. 1 year 0.19% Figure 5: Error in annual energy prediction by ex- jan 1.79% tracting the power matrix from annual and monthly feb mar apr -0.26% -0.72% -1.41% data. The irradiance is measured with a calibrated pyranometer. may jun jul aug sept -1.54% -0.38% 0.50% 0.77% 1.36% Figure 5 shows that the error of this specific module remains under 1% for all 3 approaches, when the test conditions described before are fulfilled. The intercomparison with power matrices and NOST values oct 2.26% determined from long term (monthly or annual) moni- nov 1.34% toring data confirms the possibility of also extracting dec 1.92% the module power matrix directly from monitoring data -3% -2% -1% 0% 1% Error in annual energy prediction 2% 3% with only pyranometer data available. The longer the period, the more accurate is the energy prediction. The winter months generally lead to higher errors than the other months. The disadvantage of this approach is the time required for a characterisation, reason for which the short term measurement approaches were here investigated. 3.4 Energy prediction with indoor data From the most accurate methods, the indoor approach has been selected for a final energy prediction inter-comparison between modules of different technologies (sc-Si, mc-Si, HIP, back-contact cells, CdTe, single junction a-Si and triple junc- tion a-Si). The indoor approach has the advantage of being the most reproducible and of being independent from weather conditions. The energy of the 14 different module types, 2 modules of each, were predicted by combining (1) the indoor measured power matrix of the reference module, (2) the outdoor determined NOST value (see Table I), and (3) the annual meteo matrix measured at Lugano. Since the stabilised power of the reference modules and the modules to be predicted are not the same due to different durations of outdoor exposure, the calculated kWh has to be corrected for this. The grey columns in Figure 3 show the original error and the blue the error after a proportional correction. Figure 6: Error in annual energy prediction of 28 modules before and after correction for differences in stabilised power. Vm beta Co C1 Im alpha MF01 19.3 -0.0857 -0.27 -0.36 6.8 -1.83E-04 NT01 35.3 -0.1675 -2.12 -1.96 4.8 -3.73E-05 FS01 68.8 -0.171 -2.66 -1.61 0.9 3.74E-04 BP01 35.6 -0.1657 -0.21 -0.58 4.7 -5.37E-05 STP01 34.2 -0.1569 -0.31 -0.80 4.3 -2.20E-05 HIP01 36.4 -0.1321 -1.29 -0.84 5.0 2.39E-04 KC01 17.4 -0.082 -0.16 -0.33 7.1 -1.05E-04 MHH01 28.4 -0.1321 -1.96 -1.48 6.9 -3.19E-04 IBC01 29.5 -0.1278 -0.22 -0.24 7.0 -1.48E-04 K01 77.5 -0.1967 -2.64 -2.46 1.1 1.19E-03 ES01 16.7 -0.0576 0.33 -0.23 3.9 1.08E-03 SW01 35.1 -0.1588 -0.57 -1.04 4.6 -1.26E-04 STM01 39.5 -0.1809 -1.52 -1.57 5.2 -1.21E-04 ASE01 35.6 -0.1486 0.11 -0.68 4.4 -5.09E-05 ASE03 ASE02 STM03 STM02 SW03 SW02 ES03 ES02 K03 K02 IBC03 IBC02 MHH03 MHH02 KC03 KC02 HIP03 HIP02 STP03 STP02 BP03 BP02 FS02 NT03 NT02 MF03 MF02 error with orginal STC power of module 01 error after correcting according to STC power of module 02 and 03 -5.0 -2.5 0.0 2.5 10 20 30 40 50 Error in energy prediction (%) After this correction for all tested modules the error remained in the range of ±3%, except for the Kaneka a-Si module technology, which had still not terminated its initial degradation. Table II shows the fit parameter of all modules. Table II: Indoor determined fit parameter of all modules describing their power matrix. Centrale di test ISAAC-TISO, D. Chianese, ISAAC-TISO Seite 165 von 288

3.5 Energy Rating comparison services In 2007, four Energy Rating comparison in field were performed for third-parties. Some of them including: � Initial I-V measurement at STC; � exposure at Voc for first degradation (20kWh/m2); � second I-V at STC for reference; � exposure at MPPT for an insolation ranging from 100kWh/m2 to 400kW/m2; � final I-V measurement at STC. 3.6 MPPT3000 development During 2007 collaborations with 6 institutes (either Universities and manufactures) have been achieved for the installation of systems equipped with MPPT3K testing devices which were developed by ISAAC-TISO. The communications software "MPP3K Manager" has been improved. The firmware of the DSP has also been improved; an auto-range and new indicators of setup were added. 3.7 BIPV The introduction of photovoltaic plants into the building environment requires a sensitivity and nontechnical knowledge which installers often lack. Although BIPV (Building Integrated PV) makes up only a small part of the overall PV market, it is becoming increasingly important for the eventual acceptance of PV. The photovoltaic module is no longer a building accessory which disfigures, but it is becoming a building element which has a role in the creation of the entire envelope of a building. In the case of BiPV integration, due consideration at the beginning of a project will permit better integration from aesthetic, energetic and economic points of view. The architect must therefore have the knowledge and the tools to promote photovoltaic integration in a building. He must be aware of the possibilities, the obligations, the advantages and the disadvantages. In order to help them a new homepage dedicated to BIPV was created. 4 Evaluation 2007 Figure 7: Information homepage on BIPV for architect (www.bipv.ch). ISAAC-TISO participates also as external work partner at the subproject SP6 of the PERFORMANCE project in 6 th European Framework programme. The rule of ISAAC in this sub-project is to provide input on present regulations and building codes in Switzerland and to participate actively in the work-package dealing with the development of tests for novel BIPV technologies. � In April 2007 the seventh quality audit, for the ISO17025 accreditation maintenance of the sun simulator, supervised by the Swiss Accreditation Service, was successfully passed. � A total of 342 indoor I-V measurement were performed for third-parties. � In addition for several modules other measurements were executed: 22 determination of the temperature coefficients; 21 I-V characterization at different irradiances (200, 400, 600 and 800 W/m²); 47 outdoor initial degradation (20-40 kWh/m²); I-V determination with multiflash method; Visual inspection and insulation test according to IEC 61215; Electrical continuity test; By-pass diode test. Seite 166 von 288 Centrale di test ISAAC-TISO, D. Chianese, ISAAC-TISO 8/9

7/9<br />

c-Si reference cell for the measurement of the irradiance. Even better would be to have reference<br />

devices using the same technology. Pyranometer values lead to errors larger than 4%.<br />

(3) The characterisation approach with the sun-tracker requires a separate determination of<br />

NOST, due to the fact that a limited number of data at different irradiances and temperatures are available<br />

by tracking the sun.<br />

(4) Single day data of high resolution (1 minute intervals) are sufficient to determine the power<br />

matrix when applying the equations 1 and 2 of the matrix method.<br />

1 year<br />

0.19%<br />

Figure 5: Error in annual energy prediction by ex-<br />

jan<br />

1.79% tracting the power matrix from annual and monthly<br />

feb<br />

mar<br />

apr<br />

-0.26%<br />

-0.72%<br />

-1.41%<br />

data. The irradiance is measured with a calibrated<br />

pyranometer.<br />

may<br />

jun<br />

jul<br />

aug<br />

sept<br />

-1.54%<br />

-0.38%<br />

0.50%<br />

0.77%<br />

1.36%<br />

Figure 5 shows that the error of this specific module<br />

remains under 1% for all 3 approaches, when the test<br />

conditions described before are fulfilled. The intercomparison<br />

with power matrices and NOST values<br />

oct<br />

2.26% determined from long term (monthly or annual) moni-<br />

nov<br />

1.34% toring data confirms the possibility of also extracting<br />

dec<br />

1.92%<br />

the module power matrix directly from monitoring data<br />

-3% -2% -1% 0% 1%<br />

Error in annual energy prediction<br />

2% 3%<br />

with only pyranometer data available. The longer the<br />

period, the more accurate is the energy prediction.<br />

The winter months generally lead to higher errors than the other months. The disadvantage of this<br />

approach is the time required for a characterisation, reason for which the short term measurement<br />

approaches were here investigated.<br />

3.4 Energy prediction with indoor data<br />

From the most accurate methods, the indoor approach has been selected for a final energy prediction<br />

inter-comparison between modules of different technologies (sc-Si, mc-Si, HIP, back-contact cells,<br />

CdTe, single junction a-Si and triple junc-<br />

tion a-Si). The indoor approach has the<br />

advantage of being the most reproducible<br />

and of being independent from weather<br />

conditions.<br />

The energy of the 14 different module<br />

types, 2 modules of each, were predicted<br />

by combining (1) the indoor measured<br />

power matrix of the reference module, (2)<br />

the outdoor determined NOST value (see<br />

Table I), and (3) the annual meteo matrix<br />

measured at Lugano. Since the stabilised<br />

power of the reference modules and the<br />

modules to be predicted are not the<br />

same due to different durations of outdoor<br />

exposure, the calculated kWh has to<br />

be corrected for this. The grey columns in<br />

Figure 3 show the original error and the<br />

blue the error after a proportional correction.<br />

Figure 6: Error in annual energy prediction<br />

of 28 modules before and after correction<br />

for differences in stabilised power.<br />

Vm beta Co C1 Im alpha<br />

MF01 19.3 -0.0857 -0.27 -0.36 6.8 -1.83E-04<br />

NT01 35.3 -0.1675 -2.12 -1.96 4.8 -3.73E-05<br />

FS01 68.8 -0.171 -2.66 -1.61 0.9 3.74E-04<br />

BP01 35.6 -0.1657 -0.21 -0.58 4.7 -5.37E-05<br />

STP01 34.2 -0.1569 -0.31 -0.80 4.3 -2.20E-05<br />

HIP01 36.4 -0.1321 -1.29 -0.84 5.0 2.39E-04<br />

KC01 17.4 -0.082 -0.16 -0.33 7.1 -1.05E-04<br />

MHH01 28.4 -0.1321 -1.96 -1.48 6.9 -3.19E-04<br />

IBC01 29.5 -0.1278 -0.22 -0.24 7.0 -1.48E-04<br />

K01 77.5 -0.1967 -2.64 -2.46 1.1 1.19E-03<br />

ES01 16.7 -0.0576 0.33 -0.23 3.9 1.08E-03<br />

SW01 35.1 -0.1588 -0.57 -1.04 4.6 -1.26E-04<br />

STM01 39.5 -0.1809 -1.52 -1.57 5.2 -1.21E-04<br />

ASE01 35.6 -0.1486 0.11 -0.68 4.4 -5.09E-05<br />

ASE03<br />

ASE02<br />

STM03<br />

STM02<br />

SW03<br />

SW02<br />

ES03<br />

ES02<br />

K03<br />

K02<br />

IBC03<br />

IBC02<br />

MHH03<br />

MHH02<br />

KC03<br />

KC02<br />

HIP03<br />

HIP02<br />

STP03<br />

STP02<br />

BP03<br />

BP02<br />

FS02<br />

NT03<br />

NT02<br />

MF03<br />

MF02<br />

error with orginal STC power of module 01<br />

error after correcting according to STC power of module 02 and 03<br />

-5.0 -2.5 0.0 2.5 10 20 30 40 50<br />

Error in energy prediction (%)<br />

After this correction for all tested modules the error remained<br />

in the range of ±3%, except for the Kaneka a-Si<br />

module technology, which had still not terminated its initial<br />

degradation. Table II shows the fit parameter of all modules.<br />

Table II: Indoor determined fit parameter of all modules<br />

describing their power matrix.<br />

Centrale di test ISAAC-TISO, D. Chianese, ISAAC-TISO Seite 165 von 288

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