Unit Commitment by Adaptive Particle Swarm Optimization

カテゴリ: 部門大会

論文No: 66

グループ名: 【B】平成18年電気学会電力・エネルギー部門大会講演論文集

発行日: 2006/09/13

タイトル(英語): Unit Commitment by Adaptive Particle Swarm Optimization

著者名: Ahmed Yousuf Saber (University of the Ryukyus),千住 智信(University of the Ryukyus),宮城 吏(University of the Ryukyus),浦崎 直光(University of the Ryukyus),舟橋 俊久(Meidensha Corporation)

著者名(英語): Ahmed Yousuf Saber (University of the Ryukyus),Tomonobu Senjyu(University of the Ryukyus),Tsukasa Miyagi(University of the Ryukyus),Naomitsu Urasaki(University of the Ryukyus),Toshihisa Funabashi(Meidensha Corporation)

キーワード: Adaptive Particle Swarm Optimization|economic load dispatch|unit commitment|Gaussian distribution

要約(日本語): This paper presents an Adaptive Particle Swarm Optimization (APSO) for Unit Commitment (UC) problem. APSO reliably and accurately tracks a continuously changing solution. By analyzing the social model of standard PSO for the UC problem of variable size and load demand, adaptive criteria are applied on PSO parameters and the global best particle (knowledge) based on the diversity of fitness. In this method, PSO parameters are automatically adjusted using Gaussian modification. To increase the knowledge, the global best particle is updated instead of a fixed one in each generation. To avoid the method to be frozen, idle particles are reset. The real velocity is digitized (0/1) by a logistic function for binary UC.

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