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Multi-objective optimization of PMSG controller parameters with multi-objective COLSHADE algorithm based on transformer model acceleration

Author

Listed:
  • Yin, Linfei
  • Li, Haomiao
  • Liu, Yuhan

Abstract

For the issue of the long optimization process of permanent magnet synchronous generator (PMSG), this study introduces the constrained optimization linear population reduction adaptive differential evolutionary algorithm (COLSHADE) algorithm to optimize parameters. This paper proposes a multi-objective COLSHADE (MOCOLSHADE) to tackle the multi-objective question of control parameter optimization by applying a crowding distance strategy to adapt non-dominated solutions. Finally, to reduce the optimization time, this study proposes the MOCOLSHADE algorithm accelerated by the Transformer model (AOT-MOCOLSHADE). Compared to the five algorithms, the AOT-MOCOLSHADE algorithm optimizes the PMSG controller parameters to get Pareto fronts with homogeneity and diversity, reduces the average computation time by 60 %–90 % relative to the comparison algorithms, and the optimized multi-objective controller has superior control performance and system stability.

Suggested Citation

  • Yin, Linfei & Li, Haomiao & Liu, Yuhan, 2025. "Multi-objective optimization of PMSG controller parameters with multi-objective COLSHADE algorithm based on transformer model acceleration," Energy, Elsevier, vol. 337(C).
    • Handle: RePEc:eee:energy:v:337:y:2025:i:c:s0360544225043580
    DOI: 10.1016/j.energy.2025.138716
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