Optimization of the electric power leveling system by using superconducting magnetic energy storage with genetic algorithm

Shigeyuki Funabiki, Toshihiko Tanaka, Toshinori Fujii

Research output: Contribution to journalArticle

Abstract

A new optimization method of the electric power leveling system using an SMES is proposed. The SMES is parallelly connected with rolling mills in steel works. The leveling control is based on fuzzy reasoning. The SMES capacity and the scaling factors of the fuzzy controller will be optimized so that the power leveling control can be achieved and then the total cost of the added SMES cost and reduced contract electricity rate becomes lower. The optimization is carried out using a genetic algorithm and a cost reduction of 7.76 billion yen can be achieved. Power leveling simulation confirms that the proposed optimization method is very effective for designing the power leveling system.

Original languageEnglish
Pages (from-to)62-69
Number of pages8
JournalElectrical Engineering in Japan (English translation of Denki Gakkai Ronbunshi)
Volume150
Issue number3
DOIs
Publication statusPublished - Feb 1 2005
Externally publishedYes

Keywords

  • Genetic algorithm
  • Optimization
  • Power leveling
  • Superconducting magnetic energy storage

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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