This document presents a unified characterization model for photovoltaic (PV) system performance. The model aims to accurately represent both expected and observed system performance using a single model structure. The model separates losses into two types - operational losses impacting all intervals (e.g. inverter efficiency) and event-based losses impacting discrete intervals (e.g. shading). The model development involves 6 steps: 1) determining nominal power, 2) removing event-based losses, 3) characterizing operational performance, 4) applying the operational model to all intervals, 5) determining final modeled performance, and 6) comparing modeled to observed performance. The unified model allows direct comparison of predictive modeling and operational performance, with applications for

1. Panasonic Eco Solutions
O&M Service – Steve Voss – 5/9/16

2. PV System Loss Factor Characterization
• Introduction / Background
• Unified Characterization Model
• Conclusion
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3. Current State
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• A priori models predict the distribution of Performance Ratio very
well.
• Note: This is a “typical” representation.

4. Current State
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• Our capability to predict specific system-month’s performance is
low.
• Note: This is a “typical” representation.

5. A Solution
• A single model that can:
• Accurately represent Expected performance;
• Accurately characterize Observed performance;
• Enable direct comparison between Expected and
Observed.
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6. Single Model Structure and Requirements
• Two loss types:
• Operational: impacting all intervals
• E.g. inverter efficiency or thermal losses
• Event Based: impacting discrete intervals
• E.g. shading or outage
• All losses categories must be discernable from
measured data.
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7. Acknowledgements
• Thank you to Josh Stein and Sarah Kurtz
• Data provided by:
• Sandia National Laboratories
• DOE PV Regional Test Centers
• National Renewable Energy Lab and DOE:
• Terry Sanford Federal Building
• http://www.nrel.gov/pv/engineering_performance_data.html
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8. Step 1: Nominal Power
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Nominal Power = (DC Capacity) * (Irradiance)

9. Step 2: Remove “Events”
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Nominal Power = (DC Capacity) * (Irradiance)

10. Step 3: Characterize operational performance
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Example: DC Voltage Characterization – Part 1

11. Step 3: Continued
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Example: DC Voltage Characterization – Part 2

12. Step 3: Continued
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Example: DC Voltage Characterization – Combined

13. Step 4: Operational model for all intervals
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Operational model applied to all intervals, accounts for: DC current,
DC voltage, Thermal, Inverter and AC losses.

14. Step 5: Final model – All Intervals
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Event based losses are quantified as the difference between the
Operational Model and Measured values.

15. Step 6: Compare
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Line by line comparison shows where observation and prediction disagree

16. Conclusion
• Direct correlation of predictive modeling and
operational performance is a small but critical step in
the on-going maturation of the PV industry.
• Applications of single model characterization:
• Troubleshooting;
• Acceptance testing;
• Performance reporting;
• Virtuous feedback loop between Design,
Modeling and Operations.
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17. Thank you
Steve Voss – Stephen.Voss@us.Panasonic.com