文章基本信息

标题：Forecasting Research on Long-term Solar Irradiance with An Improved Prophet Algorithm
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作者：Yang Xinpei ; Li Yiguo ; Shen Jiong 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2022
卷号：55
期号：9
页码：491-494
DOI：10.1016/j.ifacol.2022.07.085
语种：English
出版社：Elsevier
摘要：AbstractTo solve the problem of predicting solar irradiance in integrated energy systems (IES), this paper improves the Prophet algorithm by removing the trend and holidays terms, changing to the multiplicative form, and adding the monthly regressors. The improved Prophet algorithm is compared with the original and autoregressive integrated moving average (ARIMA) algorithms respectively, and the forecast accuracy is significantly improved, and the RMSE of the long-term forecast is 108.30% lower than that of ARIMA. The improved algorithm can be applied to forecast solar irradiance on long time scales with single information, providing a solution to the problem of PV array planning for IES. At the same time, the forecast data obtained by the algorithm can also be used as a reference value to optimize the day-ahead dispatch.
关键词：Keywordsintegrated energy systems (IES)solar irradiancePlanning, Prophet AlgorithmLong-term forecasting