![Model Parameter True-Up (2 of 2)
Ex-post derivation of thermal parameters from:
Faiman, Prog. Photovolt: Res. Appl., 2008.
BOM-specific analytical modeling of IAM:
Fatehi & Sauer, Proc. 40th IEEE PVSC, 2014.
Orig. PF Ext. AB
UC [W/m2/°C] 20 19.9
UV [W/m2/°C/m/s] 0 2.4
13](https://image.slidesharecdn.com/sauertsetrueup2015pvscslidesamplify-170118005236/85/Revisiting-the-Model-Parameters-of-an-Existing-System-Using-the-Photovoltaic-System-Analysis-Toolbox-PVSAT-13-320.jpg)
![Results (1 of 2)
Orig. PF Typ. AB Ext. AB
PPI [%] 107.50 105.82 99.81
Power Capacity Test for 1st month (Target = 100%):
Degradation Test over 20 months (Target = 0.7 %/year):
Orig. PF Typ. AB Ext. AB
RDEG [%/year] 1.27 1.14 1.15
Energy Production Test over 20 months (Target = 100%):
Orig. PF Typ. AB Ext. AB
EPI [%] 106.07 104.12 99.43
RMSD [% of nameplate] 4.53 3.57 1.10
MBD [% of nameplate] 4.15 2.87 -0.41
14](https://image.slidesharecdn.com/sauertsetrueup2015pvscslidesamplify-170118005236/85/Revisiting-the-Model-Parameters-of-an-Existing-System-Using-the-Photovoltaic-System-Analysis-Toolbox-PVSAT-14-320.jpg)
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Revisiting the Model Parameters of an Existing System Using the Photovoltaic System Analysis Toolbox (PVSAT)
- 1. Revisiting the Model Parameters of an Existing System Using the Photovoltaic System Analysis Toolbox (PVSAT) Kenneth J. Sauer, Ian C. Tse, and Ryan A. Desharnais Originally Presented at the 42nd IEEE Photovoltaic Specialists Conference June 17th, 2015
- 2. Original design plans / drawings Manufacturer datasheets 3rd party test reports Industry rules of thumb Default parameters in software Pro forma Energy Production Forecasts 2 Pro forma parameters come from: How well do pro forma parameters represent a PV system as built? Pro forma Weather Data Pro forma Model Parameters Energy Simulation Software (PVsyst, PVWatts, SAM, etc.) Pro forma Energy Production Forecast Procurement Phase
- 3. Presentation Outline 3 Photovoltaic System Analysis Toolbox (PVSAT) Precision of PVSAT validated with PVsyst Accuracy of PVSAT checked against test array data Executing a modern performance guarantee Three levels of model parameter true-up Evaluating the impact of true-up on forecast accuracy
- 4. Photovoltaic System Analysis Toolbox (PVSAT) 4 Performance Metrics Calculation Energy Simulation Model Validation Data Import & Filtration PVSAT Sandia PV_LIB v1.2 Irradiance transposition Heat transfer (U values) Diode circuitry (.PAN files) Power loss mechanisms (e.g., IAM) Energy Sim submodels • PVSAT able to take sub-hourly data • Also can analyze periods > 1 year • Capable of degradation rate modeling
- 5. Measurement Data 5 Roof-mounted mc-Si 11 modules in series 1 inverter PV system specification 1-minute data September 2013 – April 2015 Global horizontal irradiance Diffuse horizontal irradiance Ambient temperature Wind speed DC current and voltage Clear sky filter applied Measurements collected on-site
- 6. Validation Test I: PVSAT vs. PVsyst 6 Measured weather + high-loss parameters PVSAT PVsyst Simulation results Simulation results Compare residuals solar position algorithm error PVSAT more precise and with less noise
- 7. Validation Test II: Model vs. Measurement 7 Measured weather + ext. as-built parameters Simulation results Simulation results Compare residuals Energy forecasts from PVSAT are as accurate as those from PVSyst Measured energy production PVSAT PVsyst PVSAT PVsyst RMSD 1.92% < 1.94% MBD -0.44% -0.47% Energy Production Deviation -0.67% -0.72%
- 8. Power Capacity Test 8 PPI > 100% = PASS subset for regression GpoaEff_RC Month GpoaEff_RC Tcell_RC PmpDC_RC Jan 519 26 1312 Feb 610 30 1518 Mar 762 37 1839 Apr 870 38 2084 May 895 38 2139 Jun 924 40 2186 Jul 918 39 2181 Aug 891 41 2105 Sept 860 40 2044 Oct 703 37 1700 Nov 534 31 1324 Dec 534 28 1342 Monthly Guarantee Table (Ext. As-Built)
- 9. Degradation Test 9 from the Guarantee Table execution GpoaEff_RC Tcell_RC PmpDC_RC PmpDC’ Sept 860 40 2044 2040 Oct 703 37 1700 1686 Nov 534 31 1324 1340 Dec 534 28 1342 1321 Jan 519 26 1312 1305 Feb 610 30 1518 1523 Mar 762 37 1839 1828 Apr 870 38 2084 2072 May 895 38 2139 2127 Jun 924 40 2186 2170 Jul 918 39 2181 2166 Aug 891 41 2105 2084 TimeinOperation Power Capacity Test (1st month) PPI time RDEG < 0.7 %/yr : PASS 0.7% annual degradation rate per module manufacturer’s warranty
- 10. Energy Yield Test 10 EPI > 100% : PASS Modeled RDEG = 0.7 %/yr Typically run over one year period; here all 20 months is used weather-adjusted
- 11. Three Models 11 Model Sources and Attributes Original Pro Forma Original system design plans • Tilt: 12° • Azimuth: 190° Datasheet • Power tolerances • γPmp Default .PAN, IAM, and U values taken from PVsyst v6.38 Typical As-Built On-site survey • Tilt: 13.87° • Azimuth: 190.8° Manufacturer flash test data • Power tolerances Extended As-Built Custom .PAN, IAM, U values Levelofparametertrue-up
- 12. Model Parameter True-Up (1 of 2) One-diode model optimization method from: Sauer et al., IEEE J. Photovoltaics, 2015. 12
- 13. Model Parameter True-Up (2 of 2) Ex-post derivation of thermal parameters from: Faiman, Prog. Photovolt: Res. Appl., 2008. BOM-specific analytical modeling of IAM: Fatehi & Sauer, Proc. 40th IEEE PVSC, 2014. Orig. PF Ext. AB UC [W/m2/°C] 20 19.9 UV [W/m2/°C/m/s] 0 2.4 13
- 14. Results (1 of 2) Orig. PF Typ. AB Ext. AB PPI [%] 107.50 105.82 99.81 Power Capacity Test for 1st month (Target = 100%): Degradation Test over 20 months (Target = 0.7 %/year): Orig. PF Typ. AB Ext. AB RDEG [%/year] 1.27 1.14 1.15 Energy Production Test over 20 months (Target = 100%): Orig. PF Typ. AB Ext. AB EPI [%] 106.07 104.12 99.43 RMSD [% of nameplate] 4.53 3.57 1.10 MBD [% of nameplate] 4.15 2.87 -0.41 14
- 15. Results (2 of 2) 15
- 16. Presentation Summary 16 Fidelity of model parameters influences test results Degradation test can detect long-term durability issues Seasonal errors introduced or masked by inaccurate parameters Possible to de-risk with efforts to true-up model parameters Setting the right bar for performance is also useful for O&M
- 18. Our mission is to quantify and maximize the operating performance and value of installed photovoltaic (PV) systems We provide services to owners, buyers, and developers of large commercial, industrial, and utility-scale systems Customers choose us because our advanced diagnostics and experience enable us to efficiently see things others cannot An engineering services company focused on the evaluation and improvement of PV systems 7/2/2015 18 Company at a Glance Inspection & Testing - Field / On-Site Testing - In-House Laboratory Performance Analysis - System Rating - Degradation Analysis - As-Built Parameters Consulting Services - Forensic Engineering - Repair and Warranty Administration - Optimization and Repowering Primary Services