The Effect of Inverter Loading Ratio on Energy Estimate Bias

Kevin S. Anderson, William B. Hobbs, William F. Holmgren, Kirsten R. Perry, Mark A. Mikofski, Rounak A. Kharait

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations


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 languageEnglish (US)
Title of host publication2022 IEEE 49th Photovoltaics Specialists Conference, PVSC 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages7
ISBN (Electronic)9781728161174
StatePublished - 2022
Externally publishedYes
Event49th IEEE Photovoltaics Specialists Conference, PVSC 2022 - Philadelphia, United States
Duration: Jun 5 2022Jun 10 2022

Publication series

NameConference Record of the IEEE Photovoltaic Specialists Conference
ISSN (Print)0160-8371


Conference49th IEEE Photovoltaics Specialists Conference, PVSC 2022
Country/TerritoryUnited States


  • clipping
  • high-frequency
  • inverter
  • irradiance
  • modeling
  • photovoltaic
  • subhourly
  • variability

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering
  • Electrical and Electronic Engineering


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