Short-term hydropower station scheduling under deregulated environment based on improved evolutionary programming

Shuai Li, Chuanwen Jiang

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

This paper proposes an efficient algorithm for short-term hydropower plant scheduling based on improved evolutionary programming (IEP). The water balance constraints, reservoir volume constraints, total water discharge constraints and the power constraints are taken into consideration. In common algorithm, the offspring is generated by adding a Gaussian random variable to the parent. In the improved evolutionary programming, a new chaotic mutation technique is used to generate the offspring. Numerical examples show that the improved evolutionary programming has quick convergence property and the desirable optimal solution can be fast and easily obtained through the proposed algorithm.
Original languageEnglish
Title of host publication2006 International Conference on Computational Intelligence and Security, ICCIAS 2006
Pages242-247
Number of pages6
Volume1
DOIs
Publication statusPublished - 1 Dec 2007
Externally publishedYes
Event2006 International Conference on Computational Intelligence and Security, ICCIAS 2006 - Guangzhou, China
Duration: 3 Oct 20066 Oct 2006

Conference

Conference2006 International Conference on Computational Intelligence and Security, ICCIAS 2006
Country/TerritoryChina
CityGuangzhou
Period3/10/066/10/06

ASJC Scopus subject areas

  • Computer Science(all)
  • Control and Systems Engineering

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