Predator-Prey Brain Storm Optimizationを用いたロバスト配電系統状態推定法

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: 2023/02/01

タイトル(英語): A Robust Method for Distribution System State Estimation with Predator-Prey Brain Storm Optimization

著者名: 伊藤　亮朗（明治大学総合数理学部ネットワークデザイン学科），森　啓之（明治大学総合数理学部ネットワークデザイン学科）

著者名(英語): Akio Ito (Dept. of Network Design, Meiji University), Hiroyuki Mori (Dept. of Network Design, Meiji University)

キーワード: 配電系統状態推定，DistFlow，進化的計算，Predator Prey Brain Storm Optimization，L1ノルム　　distribution systems state estimation，DistFlow，evolutionary computation，Predator Prey Brain Storm Optimization，L1 norm

要約(英語): In this paper, a new method is proposed for distribution system static state estimation with low redundant measurements. It is different from transmission system static state estimation because the distribution system static state estimation has low redundancy of measurements while the transmission system static state estimation has enough redundancy. This paper makes use of the nest structure of DistFlow of the distribution system power flow calculation to transform the formulation into evaluating the state variable vector at distribution substations. In other words, the distribution state estimation problem may be expressed as an optimization problem. As the optimization method, PPBSO (Predator-Prey Brain Storm Optimization) of evolutionary computation is proposed to solve the problem. The proposed method is successfully applied to a sample system.

本誌: 電気学会論文誌B（電力・エネルギー部門誌） Vol.143 No.2 （2023） 特集：令和4年電力・エネルギー部門大会

本誌掲載ページ: 78-85 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/143/2/143_78/_article/-char/ja/