データマイニングに基づく毎日の太陽光発電の発電電力予測手法

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: 2014/10/01

タイトル(英語): A Prediction Method for Daily Photovoltaic Power Generation based on Datamining

著者名: 杉村　博（神奈川工科大学 創造工学部 ホームエレクトロニクス開発学科），林　敏（神奈川工科大学大学院 工学研究科 電気電子工学専攻），森　武昭（神奈川工科大学 創造工学部 ホームエレクトロニクス開発学科／神奈川工科大学大学院 工学研究科 電気電子工学専攻）

著者名(英語): Hiroshi Sugimura (Department of Home Electronics, Faculty of Creative Engineering, Kanagawa Institute of Technology), Bin Rin (Department of Electrical and Electronic Engineering, Graduate School of Engineering, Kanagawa Institute of Technology), Takeaki Mori (Department of Home Electronics, Faculty of Creative Engineering, Kanagawa Institute of Technology/Department of Electrical and Electronic Engineering, Graduate School of Engineering, Kanagawa Institute of Technology)

キーワード: 太陽光発電，予測システム，時系列データマイニング　　photovoltaic，prediction system，time-series datamining

要約(英語): This paper describes a method for predicts future behavior of generating power of photovoltaic power generation apparatus, PV for short, using time-series datamining technique. Introducing the renewable energy apparatus, such as PV, and then operating pieces of apparatus by renewable power are essential for reducing the total emission of carbon dioxide. The point here is harmonization among the whole pieces of apparatus, we thus are necessary making a plan to share the limited PV power. The generating power of PV varies depending on meteorological factors, which means the optimized harmonization plan must be dynamically changed in accordance with the generated power. For this reason, we need a method to predict the future generation power of PV in making a plan. In this paper, we develop a prediction method based on a combination of clustering, decision tree learning and dynamic time warping. The utilization data is time series from five sensors that are the temperature, the atmospheric pressure, humidity, the velocity of the wind, and the solar radiation. The output of the system as prediction is a sequence of daily generating power of PV at intervals of five minutes. We carry out to install and experiment with a PV of 25 [m2] and several sensors on a detached house. As a result of comparing measurements to prediction values, the mean absolute error per day is 0.34 [kW].

本誌: 電気学会論文誌B（電力・エネルギー部門誌） Vol.134 No.10 （2014）

本誌掲載ページ: 849-855 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/134/10/134_849/_article/-char/ja/