ベータ回帰を用いた確率的日射量予測―大外れの予見可能性の検討―

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: 2014/06/01

タイトル(英語): Probabilistic Solar Irradiation Forecast using Beta Regression―A Study on Capability of Predicting Large Forecast Error―

著者名: 志賀　孝広（名古屋大学大学院工学研究科電子情報システム専攻／（株）豊田中央研究所BR社会システム研究部），加藤　丈佳（名古屋大学大学院工学研究科電子情報システム専攻），鈴置　保雄（名古屋大学大学院工学研究科電子情報システム専攻）

著者名(英語): Takahiro Shiga (Dept. of Electrical Eng. and Comp. Sci., Grad. Schoolof Eng., Nagoya University/Social Systems Research Div., Toyota Central R&D Labs., Inc.), Takeyoshi Kato (Dept. of Electrical Eng. and Comp. Sci., Grad. Schoolof Eng., Nagoya University), Yasuo Suzuoki (Dept. of Electrical Eng. and Comp. Sci., Grad. Schoolof Eng., Nagoya University)

キーワード: 日射量，確率的予測，大外れ，メソ数値予報モデル格子点値，ベータ回帰，スレットスコア　　solar irradiation，probabilistic forecast，large forecast error，meso-scale model grid point value (MSM-GPV)，beta regression，threat score

要約(英語): Although renewable energies such as solar and wind power are penetrating rapidly, they require reserve powers for sudden change of output and sometimes cause serious incident in electricity grid because of their unpredictability. On the other hand home energy management systems also need efficient operation of energy storage devices to maximize the utility of facilities including photovoltaics. Therefore to know the uncertainty of their output is crucially important to utilize such unstable power sources effectively. As the solar irradiation has upper and lower bound, beta distribution which has finite interval of [0,1] is suitable to represent the uncertainty of the irradiation. Thus we applied beta regression, which is a kind of generalized linear models using beta distribution, to probabilistic forecast of solar irradiation. As a result of assessment of estimated models by using threat score, precision, and recall, the model employing variable dispersion beta regression showed the best performance in terms of predicting occurrences of large forecast errors. Moreover the precision parameter φ(x) of the variable dispersion beta regression was found to be an excellent indicator to alert possibility of large forecast errors.

本誌: 電気学会論文誌B（電力・エネルギー部門誌） Vol.134 No.6 （2014） 特集：再生可能エネルギーの発電予測とシステム技術

本誌掲載ページ: 527-536 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/134/6/134_527/_article/-char/ja/