Improved Parallel Differential Evolution Algorithm with Small Population for Multi-Period Optimal Dispatch Problem of Microgrids

Tianle Li, Yifei Li, Fang Wang, Cheng Gong, Jingrui Zhang () and Hao Ma
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Tianle Li: Beijing Dingcheng Hongan Technology Development Co., Ltd., Beijing 101399, China
Yifei Li: Beijing Dingcheng Hongan Technology Development Co., Ltd., Beijing 101399, China
Fang Wang: State Grid Beijing Electric Power Research Institute, Beijing 100031, China
Cheng Gong: Beijing Dingcheng Hongan Technology Development Co., Ltd., Beijing 101399, China
Jingrui Zhang: Department of Instrumental & Electrical Engineering, Xiamen University, Xiamen 361005, China
Hao Ma: Beijing Dingcheng Hongan Technology Development Co., Ltd., Beijing 101399, China

Energies, 2025, vol. 18, issue 14, 1-26

Abstract: Microgrids have drawn attention due to their helpfulness in the development of renewable energy. It is necessary to make an optimal power dispatch scheme for each micro-source in a microgrid in order to make the best use of fluctuating and unpredictable renewable energy. However, the computational time of solving the optimal dispatch problem increases greatly when the grid’s structure is more complex. An improved parallel differential evolution (PDE) approach based on a message-passing interface (MPI) is proposed, aiming at the solution of the optimal dispatch problem of a microgrid (MG), reducing the consumed time effectively but not destroying the quality of the obtained solution. In the new approach, the main population of the parallel algorithm is divided into several small populations, and each performs the original operators of a differential evolution algorithm, i.e., mutation, crossover, and selection, in different processes concurrently. The gather and scatter operations are employed after several iterations to enhance population diversity. Some improvements on mutation, adaptive parameters, and the introduction of migration operation are also proposed in the approach. Two test systems are employed to verify and evaluate the proposed approach, and the comparisons with traditional differential evolution are also reported. The results show that the proposed PDE algorithm can reduce the consumed time on the premise of obtaining no worse solutions.

Keywords: parallel DE; microgrid; optimal power dispatch; power flow constraint; small population (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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