@inproceedings{79e0a7428cbe44b78b710f139294b166,
title = "The Effect of Inverter Loading Ratio on Energy Estimate Bias",
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.",
keywords = "clipping, high-frequency, inverter, irradiance, modeling, photovoltaic, subhourly, variability",
author = "Anderson, {Kevin S.} and Hobbs, {William B.} and Holmgren, {William F.} and Perry, {Kirsten R.} and Mikofski, {Mark A.} and Kharait, {Rounak A.}",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 49th IEEE Photovoltaics Specialists Conference, PVSC 2022 ; Conference date: 05-06-2022 Through 10-06-2022",
year = "2022",
doi = "10.1109/PVSC48317.2022.9938632",
language = "English (US)",
series = "Conference Record of the IEEE Photovoltaic Specialists Conference",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "714--720",
booktitle = "2022 IEEE 49th Photovoltaics Specialists Conference, PVSC 2022",
}