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• W4387400379 startingPage "119414" @default.
• W4387400379 abstract "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 Itô 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." @default.
• W4387400379 created "2023-10-07" @default.
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• W4387400379 date "2023-12-01" @default.
• W4387400379 modified "2023-10-18" @default.
• W4387400379 title "Analysis and modeling of seasonal characteristics of renewable energy generation" @default.
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• W4387400379 doi "https://doi.org/10.1016/j.renene.2023.119414" @default.
• W4387400379 hasPublicationYear "2023" @default.
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