A hybrid quantum-behaved particle swarm optimization solution to non-convex economic load dispatch with multiple fuel types and valve-point effects

Qidong Chen, Sun Jun, Vasile Palade

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Abstract

Economic dispatch problems (EDPs) can be reduced to non-convex constrained optimization problems, and most of the population-based algorithms are prone to have problems of premature and falling into local optimum when solving EDPs. Therefore, this paper proposes a hybrid quantum-behaved particle swarm optimization (HQPSO) algorithm to alleviate the above problems. In the HQPSO, the Solis and Wets local search method is used to enhance the local search ability of the QPSO so that the algorithm can find solutions that is close to optimal when the constraints are met, and two evolution operators are proposed and incorporated for the purpose of making a better balance between local search and global search abilities at the later search stage. The performance comparison is made among the HQPSO and the other ten population-based random search methods under two different experimental configurations and four different power systems in terms of solution quality, robustness, and convergence property. The experimental results show that the HQPSO improves the convergence properties of the QPSO and finally obtains the best total generation cost without violating any constraints. In addition, the HQPSO outperforms all the other algorithms on 7 cases of all 8 experimental cases in terms of global best position and mean position, which verifies the effectiveness of the algorithm.
Original languageEnglish
Pages (from-to)1503-1522
Number of pages20
JournalIntelligent Data Analysis
Volume27
Issue number5
Early online date4 Aug 2023
DOIs
Publication statusPublished - 6 Oct 2023

Bibliographical note

This document is the author’s post-print version, incorporating any revisions agreed during the peer-review process. Some differences between the published version and this version may remain and you are advised to consult the published version if you wish to cite from it.

Keywords

  • Constrained nonlinear optimization
  • Hybrid quantum-behaved particle swarm optimization
  • Economic dispatch problems
  • Solis and wets local search

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