Analysis and modeling of seasonal characteristics of renewable energy generation

The increasing penetration of renewable energy leads to seasonal fluctuation in the power system. This also results in continuous low-renewable-output events, which pose significant challenges for ensuring adequate renewable energy supply and arouse growing concern. To analyze the seasonal fluctuation characteristics of renewable in different timescales, this paper first decomposes the renewable time series into three components: climate, seasonal, and daily. Then an Ito process is introduced to model the climate and daily components considering the time series' stochastic characteristics and time correlations. Finally, the proposed model is first tested based on case studies on historical data from two selected weather stations in China. Moreover, the method is further applied to analyzing data from 253 weather stations across China at the provincial level. The results indicate that low-renewable-output events are more likely to have a longer duration in central China.