The accurate prediction of yields from photovoltaic systems (PV) is critical for their proper operation and financing, and in northern latitudes the effects of snowfall on yield can become significant. This work provides methods for identifying snowfall effects from commonly collected performance data, and recommends a model to allow for prediction of these effects based solely on meteorological time series. The model was validated with data from two large-scale (>8MW) operational PV plants. For the low tilt angles most affected by snowfall, this analysis was able to accurately predict both daily and mean values of snow effects. This methodology will enable system operators to utilize performance data to accurately identify and predict snowfall losses, and will assist system designers to optimize for the effects of snowfall on new system designs.
Pearce, J. (2019). Prediction of Energy Effects on Photovoltaic Systems due to Snowfall Events. Afribary. Retrieved from https://afribary.com/works/prediction-of-energy-effects-on-photovoltaic-systems-due-to-snowfall-events
Pearce, Joshua "Prediction of Energy Effects on Photovoltaic Systems due to Snowfall Events" Afribary. Afribary, 22 Apr. 2019, https://afribary.com/works/prediction-of-energy-effects-on-photovoltaic-systems-due-to-snowfall-events. Accessed 26 Apr. 2024.
Pearce, Joshua . "Prediction of Energy Effects on Photovoltaic Systems due to Snowfall Events". Afribary, Afribary, 22 Apr. 2019. Web. 26 Apr. 2024. < https://afribary.com/works/prediction-of-energy-effects-on-photovoltaic-systems-due-to-snowfall-events >.
Pearce, Joshua . "Prediction of Energy Effects on Photovoltaic Systems due to Snowfall Events" Afribary (2019). Accessed April 26, 2024. https://afribary.com/works/prediction-of-energy-effects-on-photovoltaic-systems-due-to-snowfall-events