A hybrid multi-agent based particle swarm optimization algorithm for economic power dispatch

Rajesh Kumar, Devendra Sharma, Abhinav Sadu

Research output: Contribution to journalArticlepeer-review

153 Citations (Scopus)

Abstract

This paper presents a new multi-agent based hybrid particle swarm optimization technique (HMAPSO) applied to the economic power dispatch. The earlier PSO suffers from tuning of variables, randomness and uniqueness of solution. The algorithm integrates the deterministic search, the Multi-agent system (MAS), the particle swarm optimization (PSO) algorithm and the bee decision-making process. Thus making use of deterministic search, multi-agent and bee PSO, the HMAPSO realizes the purpose of optimization. The economic power dispatch problem is a non-linear constrained optimization problem. Classical optimization techniques like direct search and gradient methods fails to give the global optimum solution. Other Evolutionary algorithms provide only a good enough solution. To show the capability, the proposed algorithm is applied to two cases 13 and 40 generators, respectively. The results show that this algorithm is more accurate and robust in finding the global optimum than its counterparts.

Original languageEnglish
Pages (from-to)115-123
Number of pages9
JournalInternational Journal of Electrical Power and Energy Systems
Volume33
Issue number1
DOIs
Publication statusPublished - Jan 2011
Externally publishedYes

Keywords

  • Economic power dispatch
  • Multi-agent system
  • PSO
  • Valve-point effect

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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