太陽光発電出力予測における時間推移のパターン抽出を用いた誤差分析手法

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: 2023/02/01

タイトル(英語): An Error Analysis Method by Extracting Error Time Transition Patterns in Photovoltaic Power Forecasting

著者名: 石川　歩惟（（一財）電力中央研究所），比護　貴之（（一財）電力中央研究所）

著者名(英語): Ai Ishikawa (Central Research Institute of Electric Power Industry), Takayuki Higo (Central Research Institute of Electric Power Industry)

キーワード: 太陽光発電，予測誤差分析，クラスタリング，k-means法　　photovoltaic power generation，forecasting error analysis，clustering，the k-means method

要約(英語): Information about forecasting errors of photovoltaic power generation (PV) output is useful in daily supply and demand operation of power systems for large-scale integration of PV. In the conventional error analyses, average is generally used which implies the summary of errors in a certain period. It does not represent actual transitions of errors that occurred every day and hence likelihood of future transitions with time cannot be grasped in the forecasting error. In this paper, we propose an error analysis method for PV output forecasting to grasp characteristics of error transitions such as the shapes and their occurrence probabilities. We enable such an analysis by extracting representative patterns in shape of error transitions in the following way. All the days are classified to some clusters by using a clustering method based on a similarity of shape of the error transition in that day, and then representative patterns are obtained by averaging the error transitions for each cluster. The numerical result shows that the k-means method, which is one of the clustering methods, is suitable for helping understand annual trends of error transitions. We also clarify how we should estimate the appropriate number of patterns of error time transitions.

本誌: 電気学会論文誌B（電力・エネルギー部門誌） Vol.143 No.2 （2023） 特集：令和4年電力・エネルギー部門大会

本誌掲載ページ: 146-156 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/143/2/143_146/_article/-char/ja/