Abstract
Subhourly effects, particularly variability in solar irradiance, can lead to underestimation of inverter clipping losses and overestimation of energy in hourly photovoltaic system performance models, particularly for systems with high inverter loading ratios. Direct simulation of this error can be complicated by factors such as the representation of spatial and temporal variability in hourly weather data and transient system conditions. In this work we take an alternative approach using real system power measurements to show that energy predictions from typical industry models suffer from a bias that increases with inverter loading ratio. We also show that this loading ratio-dependent bias is strongly correlated with an empirical subhourly inverter clipping bias derived from real power plant data. Finally, we show that this bias is not necessarily specific to any one model or weather dataset by recreating similar biases with alternatives of each.
Original language | American English |
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Number of pages | 10 |
State | Published - 2022 |
Event | 49th IEEE Photovoltaic Specialists Conference (PVSC 49) - Philadelphia, Pennsylvania Duration: 5 Jun 2022 → 10 Jun 2022 |
Conference
Conference | 49th IEEE Photovoltaic Specialists Conference (PVSC 49) |
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City | Philadelphia, Pennsylvania |
Period | 5/06/22 → 10/06/22 |
NREL Publication Number
- NREL/CP-5K00-82812
Keywords
- clipping
- high-frequency
- inverter
- irradiance
- modeling
- photovoltaic
- subhourly
- variability