Quantum Predator Prey Brain Storm Optimizationを用いた新しい発電機起動停止法の開発

カテゴリ: 部門大会

論文No: 22

グループ名: 【B】令和6年電気学会電力・エネルギー部門大会

発行日: 2024/08/23

タイトル(英語): Development of a New Unit Commitment Method with Quantum Predator Prey Brain Storm Optimization.

著者名: 河内勇裕（明治大学），森啓之（明治大学）

著者名(英語): Yusuke Kawauchi (Meiji University), Hiroyuki Mori (Meiji University)

キーワード: 発電機起動停止問題|進化的計算|量子コンピューティング|Quantum BSO|Predator Prey BSO|Unit commitment|Evolutionary computation|Quantum computing|Quantum BSO|Predator Prey BSO

要約(日本語): This paper proposes a new method for unit commitment (UC) with Quantum Predator Prey Brain Storm Optimization (QPPBSO). The UC problems may be expressed as a mixed integer nonlinear programing problem in which binary variables means on/off conditions of units and continuous ones implies their output. Recently, Evolutionary Computation (EC) has been applied to the UC problems due to the existence of indifferentiable cost functions such as large-scale steam turbine units etc. However, there is still room for improvement in EC because the UC problems have high nonlinear features. This paper focuses on the integration of EC with Quantum Computing (QC) that is promising in power systems. Specifically, this paper combines QC with Predator Prey Brain Storm Optimization (PPBSO) of high performance EC. The effectiveness of the proposed method is demonstrated in the New England 39-node system.

PDFファイルサイズ: 732 Kバイト