Optimal Operational Planning of Energy Plants by Modified Brain Storm Optimization

Kiyo Arai, Yoshikazu Fukuyama, Tatsuya Iizaka, Tetsuro Matsui

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

This paper proposes optimal operation planning of energy plants by modified brain storm optimization (MBSO) The problem can be formulated as a mixed integer nonlinear optimization problem and various evolutionary computation techniques such as particle swarm optimization (PSO), differential evolution (DE), and differential evolutionary PSO (DEEPSO) have been applied so far. This paper applies recently developed MBSO for optimal operational planning of energy plants in order to improve solution quality. The proposed MBSO based method is compared with the conventional PSO and DEEPSO based methods, and the original BSO based method. It is verified that total energy cost by the proposed method is lower than those by all the comparative methods for a typical energy plant.

Original languageEnglish
Pages (from-to)73-78
Number of pages6
JournalIFAC-PapersOnLine
Volume51
Issue number28
DOIs
Publication statusPublished - 2018

Keywords

  • Computational methods
  • Energy management systems
  • Factory automation
  • Heuristic searches
  • Optimization problem

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