Error Estimation of Solar Insolation Forecasts

カテゴリ: 論文誌(論文単位)

グループ名: 【B】電力・エネルギー部門

発行日: 2014/04/01

タイトル(英語): Error Estimation of Solar Insolation Forecasts

著者名: Peng Zhang (Graduate School of Information Science and Electrical Engineering, Kyushu University), Hirotaka Takano (Faculty of Information Science and Electrical Engineering, Kyushu University), Junichi Murata (Faculty of Information Science and Electrica

著者名(英語): Peng Zhang (Graduate School of Information Science and Electrical Engineering, Kyushu University), Hirotaka Takano (Faculty of Information Science and Electrical Engineering, Kyushu University), Junichi Murata (Faculty of Information Science and Electrical Engineering, Kyushu University)

キーワード: solar insolation forecasts，error estimation，data mining，forecast error

要約(英語): The prediction of solar insolation is needed to predict the photovoltaic (PV) generation output connected to power systems. This paper proposes a method for estimating the errors of solar insolation forecasts, which are unavoidable, using only the input variables employed in solar insolation prediction and the predicted solar insolation. Given that some big errors of solar insolation forecasts concentrate in the certain intervals of some variables, we use the statistics method to find those variables and the proper boundaries of the intervals and combine them as the rules to judge the categories of errors. The error estimation technique can inform the PV/power system operators what kind of error the predicted value of solar insolation is likely to have and how much the confidence of the correct estimation is. Since the big errors cause either large over expectation or under expectation of PV outputs, the results of error estimation are useful for operators to identify the extreme situations which cause the large deviation of power. From the simulation of two study cases, error estimation results of our proposed method are acceptable.

本誌: 電気学会論文誌B（電力・エネルギー部門誌） Vol.134 No.4 （2014） 特集：電力システムの時系列データおよびその解析技術

本誌掲載ページ: 367-373 p

原稿種別: 論文／英語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejpes/134/4/134_367/_article/-char/ja/