翌日需要曲線予測手法と精度向上の検討

カテゴリ: 部門大会

論文No: 8

グループ名: 【B】平成25年電気学会電力・エネルギー部門大会

発行日: 2013/08/27

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),宮下 和稔(中部電力),遠藤 隆幸(中部電力),島崎 祐一(富士電機),飯坂 達也(富士電機),勝野 徹(富士電機)

著者名(英語): Hisatomo Miyata(CHUBU Electric Power),Kazutoshi Miyashita(CHUBU Electric Power),Takayuki Endo(CHUBU Electric Power),Yuichi Shimasaki(Fuji Electric),Tatsuya Iizaka(Fuji Electric),Toru Katsuno(Fuji Electric)

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ニューラルネットワーク|load forecasting|load curve|neural networks

要約(日本語): 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.

PDFファイルサイズ: 5,318 Kバイト