遺伝的アルゴリズムによる日射量予測手法の開発

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: 2015/02/01

タイトル(英語): Development of Insolation Forecasting Method by Genetic Algorithm

著者名: 川崎　章司（明治大学理工学部電気電子生命学科），田岡　久雄（福井大学大学院工学研究科電気・電子工学専攻），長尾　泰気（福井大学大学院工学研究科電気・電子工学専攻），大中　奎佑（福井大学大学院工学研究科電気・電子工学専攻）

著者名(英語): Shoji Kawasaki (Department of Electronics and Bioinformatics School of Science and Technology, Meiji University), Hisao Taoka (Graduate School of Electrical and Electronics Engineering, University of Fukui), Taiki Nagao (Graduate School of Electrical and Electronics Engineering, University of Fukui), Keisuke Onaka (Graduate School of Electrical and Electronics Engineering, University of Fukui)

キーワード: 太陽光発電，日射量予測，遺伝的アルゴリズム，相関係数，再生可能エネルギー　　photovoltaic generation，insolation forecasting，genetic algorithm，correlation coefficient，renewable energy sources

要約(英語): Renewable energy sources such as photovoltaic generation (PV) have been promoted to be innovated. However, the output of PV is influenced by the weather condition and cause a steep fluctuation. So it is important to forecast the output of PV when an electric power company makes the power supply schedule for demand. In this paper, the authors proposed a forecasting method for amount of insolation closely related to the output of PV. In the proposed method, the amount of insolation is forecasted through the application of Genetic Algorithm which is one of the optimization method by using the past measured data. In addition, the correlation coefficients are analyzed with the weather data and measured insolation data. And, the correlation coefficients are used as the weight of observe value. The authors verify the validity and prediction accuracy of the proposed method. Moreover, we tried to improve the forecasting error by using the latest measured weather data and weather data of the other point.

本誌: 電気学会論文誌B（電力・エネルギー部門誌） Vol.135 No.2 （2015）

本誌掲載ページ: 89-96 p

原稿種別: 論文／日本語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejpes/135/2/135_89/_article/-char/ja/