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翌日需要曲線予測手法と精度向上の検討

翌日需要曲線予測手法と精度向上の検討

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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: 2014/01/01

タイトル(英語): A Study of a Next Day Electric Load Curve Forecasting Method and its Accuracy Improvement

著者名: 宮田 尚朋(中部電力(株)),宮下 和稔(中部電力(株)),遠藤 隆幸(中部電力(株)),島崎 祐一(富士電機(株)技術開発本部),飯坂 達也(富士電機(株)技術開発本部),勝野 徹(富士電機(株)技術開発本部)

著者名(英語): Hisatomo Miyata (CHUBU Electric Power Co., Inc.), Kazutoshi Miyashita (CHUBU Electric Power Co., Inc.), Takayuki Endo (CHUBU Electric Power Co., Inc.), Yuichi Shimasaki (Corporate Technology Development Office, Fuji Electric Co., Ltd.), Tatsuya Iizaka (Corporate Technology Development Office, Fuji Electric Co., Ltd.), Toru Katsuno (Corporate Technology Development Office, Fuji Electric Co., Ltd.)

キーワード: 電力需要予測,需要曲線,ニューラルネットワーク  load forecasting,load curve,neural networks

要約(英語): This paper presents a result of study for a next day electric load curve forecasting method and its accuracy improvement. Electric load curve forecasting is one of the most important tasks for insuring reliability and economic electric power supply. Because start-stop time of generators is decided using the load curve forecasting. This paper proposes three methods. First one is a new structure of forecasting models. It consists of single-output neural networks and a multi-output neural network. Second one corrects load curve using the operation information of commercial-scale utility customers. Last one selects the accuracy forecasting models adaptively using recent forecasting error. Input data of each forecasting model is different type of weather information. The simulation results reveal the effectiveness of the proposed methods for a next day electric load curve forecasting.

本誌: 電気学会論文誌B(電力・エネルギー部門誌) Vol.134 No.1 (2014) 特集:平成25年電力・エネルギー部門大会

本誌掲載ページ: 2023/09/15 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/134/1/134_9/_article/-char/ja/

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