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所要蓄電池容量の最適設計のためのベータ分布に基づく風力発電予測誤差時系列モデル

所要蓄電池容量の最適設計のためのベータ分布に基づく風力発電予測誤差時系列モデル

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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: 2019/03/01

タイトル(英語): Time Series Model of Wind Power Forecasting Error by using Beta Distribution for Optimal Sizing of Battery Storage

著者名: 兌 瀟偉(清華大学中国北京市海淀区清華大学),伊藤 雅一(早稲田大学),藤本 悠(早稲田大学),林 泰弘(早稲田大学),朱 桂萍(清華大学中国北京市海淀区清華大学),姚 良忠(中国電力科学研究院中国北京市海淀区中国電力科学研究院)

著者名(英語): Xiaowei Dui (Tsinghua University), Masakazu Ito (Waseda University), Yu Fujimoto (Waseda University), Yasuhiro Hayashi (Waseda University), Guiping Zhu (Tsinghua University), Liangzhong Yao (China Electric Power Research Institute)

キーワード: 風力発電,予測誤差,ベータ分布,時系列,蓄電池  wind power,forecast error,beta distribution,time series,battery storage

要約(英語): With the increase of wind power penetration in power system, the uncertainty caused by wind farm forecast error is enlarged which results in deterioration of wind power curtailment. In order to optimize the capacity of battery storage for mitigating forecast error, firstly it is necessary to improve the accuracy of forecast error model. This paper proposed a modeling method of forecast error time series in usage of beta distribution. Varying with forecast output, parameters of the beta distribution are estimated by maximum likelihood estimation. Autocorrelated forecast error obeying beta distribution is generated by correlated Monto-Carlo simulation. Based on the forecast error model, an optimization method is proposed to determine the optimum size of battery storage for mitigating forecast error. Through maximizing the total profit composed of electricity sales revenue, penalty and battery cost, the optimum size of battery storage is calculated. The results show that the forecast error model proposed in this paper is able to simulate both probability density function and autocorrelation correctly, which is beneficial to improving the accuracy and economy of battery storage sizing.

本誌: 電気学会論文誌B(電力・エネルギー部門誌) Vol.139 No.3 (2019)

本誌掲載ページ: 212-224 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/139/3/139_212/_article/-char/ja/

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