Forecasting degradation rates of different photovoltaic systems using robust principal component analysis and ARIMA

摘要

Degradation rates based on forecasting of performance ratio, R, time series are computed and compared with actual degradation rates. A 3-year forecasting of monthly R, measured from photovoltaic (PV) connected systems of various technologies is performed using the seasonal auto-regressive integrating moving average (ARIMA) time series model. The seasonal ARIMA model is estimated using monthly R measured over a 5-year period and based on this model forecasting is implemented for the subsequent 3 years. The degradation rate at the end of the forecasting period, eighth year, is computed using a robust principal component analysis based methodology. The degradation rates obtained for various (PV) systems are then compared with the ones obtained using the actual 8-year data.