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Determining the causes and rates of PV degradation using the Loss Factors Model (LFM)with high quality IV measurements
Steve Ransome1 & Juergen Sutterlueti2
1Steve Ransome Consulting Limited, London UK2Gantner Instruments, Germany
PVPMC #6 – Freiburg Germany
25th Oct 2016
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Introduction to degradation analysis
• Most reported PV degradation are STC corrected efficiency only (1kW/m2, 25C, AM1.5, AOI=0, direct only)
• ISC variability dominates performance uncertainty (due to soiling, spectral effects, irradiance sensor calibration …)
Can we analyse other parameters independently of ISC ?
• The cause of degradation (e.g. RSHUNT, RSERIES, VOC )gives site dependent energy yield degradation rates (due to differing proportions of insolation vs. irradiance, TMOD etc.)
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Smooth IV curves are needed for good RSC and ROC calculations“Rn = Apparent resistance between adjacent data points”
Typical GI measured IV curve (CdTe) GI raw measured (smooth data) vs.
synthesised “poor” data
truncated accuracy and added noise
𝑹𝒏= −∆𝑽∆𝑰
= −𝑽𝒏− 𝑽𝒏−𝟏𝑰𝒏− 𝑰𝒏−𝟏
Worse RSC accuracy from synthesised data (e.g. truncated or noisy)
ISC, RSC
VOC, ROC
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Checking IV data quality with Log Resistance-Voltage (RV) curves GI data much smoother than NREL’s Daystar and therefore easier to fit.
Can ignore a few “bad end points” with V~0 or V > VOC
GI CdTe
NRELCdTe
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SRCL/Gantner “Loss Factors Model” [LFM]GI data
Measure raw IV curves = f(G,T)
Fit lines to RSC and ROC
Normalise data to datasheet
6 normalised losses LFM
PRDC = nISC*nRSC*nIMP * nVMP*nROC*nVOC
Cell mismatch, shading
Cell rollover
Curvature for better understanding
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Comparing “Loss Factors Model” with standard models
LFM
1-diode (and similar models)
Fit to IV curves Exact values for 8 parameters around every IV curve
“Best fit to whole curve” depends on data point distribution/weighting “imperfect traces” e.g. cell mismatch, roll over
Normalised values for module variability
Yes. e.g. “nRsc = 98.0 ± 2.0%”
No. Specific module data only e.g. “RSHUNT = 1234Ohms”.
IndependentParameters ?
Almost independent(nVOC depends a little on nRSC and nISC)
No. Parameters are often interdependent e.g. nF and Io
Dependence onIrradiance and temperature
Simple optimum fits giveexact coefficient behaviour for low light,temp coeffs etc. each module
Try to fit pre-defined equations (even if they don’t fit data) e.g. RSHUNT (GI), I0(TCELL) etc. low light and temp coeffs. may be wrong.
Separation of all inputs e.g. ISC ~ AOI, SR
Not needed. Can just measure outdoor params(for ISC separate clear from cloudy skies)
Need to separate all parameters ISC = ISC0 * f(AOI) * f(SR) …
Fault finding and quantification of loss
Yes. Can easily identify quantify Cell mismatch, shading, R and VOC changes etc.
Some are possible (e.g. RSHUNT, RSERIES) but not mismatch, rollover etc.
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Yearly IV traces by irradiance Sept. 2010-16 GI data
Discrepancies seen at very low light levels ?
Changes in LFM parametersΔnISC ΔnRSC
ΔPRDC
ΔnROC
ΔnVOC
For each module and Irradiance (e.g. ~0.8kW/m²)
ISC variability e.g. soiling, sensor calibration etc.
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Yearly IV traces by irradiance Sept. 2010-16 GI data
Discrepancies in ISC seen at very low light levels0.04kW/m²Why ?
Year Deg
%/y
If module is degrading it’s worse at low light 1.0 0.3 kW/m2
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GI Tempe OTF from North to South East Low horizon shading for morning sun
GI hut position redPower lines green
Sensors CyanModules Magenta
Google Street view from south east
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Shading from powerlines affect the sensors and modules at different times of morning (5 distinct dips)
Efficiency Isc / Gi
Approx. shade times
modules (07:35-08:05) sensors (07:10-07:40)
Sensors higher than modules so are shaded earlier in morning
(Late afternoons are affected by 2D tracker)
Low light performance measurements vs. irradiance must be properly corrected for shading
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SRCL/Gantner “Loss Factors Model” vs. Irradiance detailed information at www.steveransome.com, GI data
•A drop in any LFMparameter limitsoverall PRDC
•Any LFM parameterchanging over timeaffects PRDC
PRDC = nISC*nRSC*nIMP * nVMP*nROC*nVOC
Low light limiting
High light limiting
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Analysis method for frequent IV curves outdoorsGI Data
Sudden change –damaged or failed module
Steady declinemodule
Stable performance module
PRDC from 6 years of hourly measurements 2010-2016
modules chosen to analyse differing behaviour
PRDC at Low light may be seasonally dependent (longer day length, sun behind module)
PRDC at High Irradiance tends not to be seasonally dependent
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LFM vs. irradiance
GI data
It’s hard to see any changes in nISC
unless corrected for shading, soiling, aoi, sr and direct:diffuse
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LFM vs. irradiance
GI data
Irradiance dependentdegradation
dnRSC
Irradiance independentdegradation
dnROC
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nRsc vs. DateTime and Log(Irradiance)Low light levels performance degrades much faster than high light levels
High light levels(0.5–1.0kW/m²) dnRSC -0.5%/y
Low light levels(0.1–0.2kW/m²) dnRSC -2.0%/y
Very Low light levels(0.001–0.02kW/m²) dnRSC -5%/y
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Measurement Conclusions
NOTES:
• Atypical devices analysed vs. a stable module
• Smooth IV curves needed for degradation analysis (check if “Rn = –V/I” is good on your measurement system)
GANTNER INSTRUMENTS dataset in AZ (6 years) - SRCL/GI Loss Factors Model
• LFM separates degradation components from nISC
• Good Gantner Instruments IV trace quality allows study of RSC and ROC
• Modules may degrade differently at high or low light levels
• LFM allows a fast independent check of degradation rates
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Predictions : Site Dependent Energy Yield DegradationEnergy Yield Gi,Tmod [Insolation(Gi,Tmod) * Efficiency(Gi,Tmod)]
Irradiance distribution is
site dependent (cumulative Hi kWh/m² % > Gi kW/m²)
nRSC (related to RSHUNT) degradation/y vs. Irradiance
-2.0%/yearlow light
-0.5%/yearhigh light
*
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Predictions : Energy yield degradation rate at sites (from measured dnRSC )
High Insolation site = Lower Energy Yield degradation-0.7%/y
Lower Insolation site =Higher Energy Yield degradation-1.3%/y
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Predictions : Conclusions
LFM gives
• Degradation rates for various parameters vs. irradiance etc.
• Predicted Energy Yield (kWh/y) degradation vs. site
• Low light drops in nRsc (~ RSHUNT) cause worse falls at low than high insolation sites
• Analysis methodology is being integrated into
• www.gantner-webportal.com(see separate poster)
Thank you for your attention!