特高系統における機械学習を活用した電圧・無効電力制御手法の提案
特高系統における機械学習を活用した電圧・無効電力制御手法の提案
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: 2024/09/01
タイトル(英語): The Voltage and Reactive Power Control Methodology for Sub-transmission Network using Machine Learning
著者名: 松島 史弥(名古屋工業大学),青木 睦(名古屋工業大学),上田 勝久(中部電力(株)技術開発本部 電力技術研究所),Suresh Chand Verma(中部電力(株)技術開発本部 電力技術研究所),中津井 紳司(中部電力(株)技術開発本部 電力技術研究所)
著者名(英語): Fumiya Matsushima (Nagoya Institute of Technology), Mutsumi Aoki (Nagoya Institute of Technology), Katsuhisa Ueda (Chubu Electric Power Co., Inc.), Suresh Chand Verma (Chubu Electric Power Co., Inc.), Shinji Nakatsui (Chubu Electric Power Co., Inc.)
キーワード: 電圧・無効電力制御,深層強化学習,太陽光発電システム,特別高圧系統,電圧推定 voltage and reactive power control,deep reinforcement learning,photovoltaic generation system,sub-transmission network,voltage estimation
要約(英語): A voltage and reactive power control method is used in substations to control transformer taps and shunt capacitors/reactors in order to maintain the voltage of a power system. It becomes difficult with the conventional method to ensure the voltage within stipulated band for a power system with a massive penetration of photovoltaic (PV) generation systems. In order to address this issue, the authors have first used machine learning to estimate the voltages at the consumer end and then proposed a voltage and reactive power control method using deep reinforcement learning that considers the voltage at all consumer ends. The effectiveness of the proposed method is studied through simulations performed on an example system with a massive PV and the results are found to be quite promising.
本誌: 電気学会論文誌B(電力・エネルギー部門誌) Vol.144 No.9 (2024)
本誌掲載ページ: 474-483 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/144/9/144_474/_article/-char/ja/
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