Quantification of the interannual variability of the nationwide electric power supply from photovoltaic systems in Japan

Abstract

Information on the variation in photovoltaic (PV) power generation is essential for resource assessment. This work investigated the interannual variability of the nationwide electric power supply from PV systems in Japan. Objectives of this study were twofold: one was the quantification of the annual variability of the nationwide PV power supply. The other was identifying the causes of the variability. However, the time span of available observation data on the PV power supply is inadequate to evaluate its variability, as PV systems have been rapidly installed in recent years. We used simulation to bypass this limitation. Due to the lack of available information for modeling, a hybrid modeling approach, combining a parametric model, and estimating parameters by fitting the model to observations, was employed. Nationwide PV power supply simulations were performed using historical weather data for 30 years, from 1991–2020. The long-term simulation data enabled us to quantify the interannual variability of the nationwide PV power generation. The annual variability measured with the range from the minimum to the maximum was approximately 9% of the mean. The variability for each month was less than 30% of the monthly mean for every month except for July when it was approximately 40%. An increasing trend in the annual mean PV power supply was observed over the 30 years, with an increase of 0.16% per year of the mean over the whole period. We found that the variations in sea surface temperature (SST) in the Tropics are factors contributing to the variability of nationwide PV power supply. Specifically, the variation in SST in the tropical Indian Ocean is one of the possible driving factors of the annual variability. The framework proposed in this study can provide valuable information for assessing solar energy resources on an interannual scale.

Keywords

• solar energy
• variability
• resource assessment
• climate
• photovoltaics
• simulation