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Enhanced heap-based optimization algorithm for dynamic economic dispatch considering electric vehicle charging integration

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  • Chen, Xu
  • Zhang, Zhixiang

Abstract

With the integration of electric vehicles (EVs) into the power system, the uncoordinated charging behaviors of EVs significantly increase the complexity of the dynamic economic dispatch problem. In this paper, we establish a mathematical model for dynamic economic dispatch with EV charging (EVDED). To address the shortcomings of existing optimization algorithms, such as slow convergence and low accuracy in solving the EVDED problem, we propose an improved heap-based optimization algorithm called RDHBO. RDHBO incorporates an optimal member region search strategy and a dual population interaction strategy. The former helps guide the optimal member toward more promising regions, improving both convergence speed and accuracy. The latter makes full use of information from eliminated individuals, enriching population diversity and avoiding local optima. We apply the RDHBO algorithm to solve three EVDED problems involving 10, 30, and 100 units under four different charging scenarios. Experimental results show that RDHBO outperforms several representative optimization methods in generating low fuel costs.

Suggested Citation

  • Chen, Xu & Zhang, Zhixiang, 2025. "Enhanced heap-based optimization algorithm for dynamic economic dispatch considering electric vehicle charging integration," Energy, Elsevier, vol. 324(C).
    • Handle: RePEc:eee:energy:v:324:y:2025:i:c:s036054422501597x
    DOI: 10.1016/j.energy.2025.135955
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