Research on microgrid cluster optimization method based on sparrow search algorithm

With the widespread application of renewable energy in microgrids, collaborative optimization scheduling of microgrid clusters has become a key issue in improving energy utilization efficiency and operational economy. To solve this problem, this paper proposes a microgrid cluster optimization scheduling method based on the sparrow search algorithm. Firstly, construct a microgrid cluster model that includes wind turbines, photovoltaics, energy storage batteries, diesel generators, and hydrogen fuel cells. Secondly, the economic optimum is defined as the objective function, and combined with the constraints of equipment and system operation, the sparrow search algorithm is proposed to solve the optimization model of the microgrid cluster. Finally, this method is used to simulate an IEEE 9-node system with 4 microgrids. The simulation results showed that this method has significant advantages over traditional particle swarm optimization algorithms in reducing total costs and new energy utilization efficiency, verifying the feasibility of this method in microgrid cluster optimization scheduling.

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Publication Details

Journal
Scientific Reports
Published
2026-04-14
DOI
https://doi.org/10.1038/s41598-026-48617-w
Primary Topic
Microgrid Control and Optimization
Type
article
Field-Weighted Citation Impact
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Research on microgrid cluster optimization method based on sparrow search algorithm

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Scientific Reports
Microgrid Control and Optimization
article

Research on microgrid cluster optimization method based on sparrow search algorithm

Lingrao Wang, Liying Yu, Hongzhi Su, Shuai Xu, Pengtao Mu, Bo Zhang
article en

Abstract

With the widespread application of renewable energy in microgrids, collaborative optimization scheduling of microgrid clusters has become a key issue in improving energy utilization efficiency and operational economy. To solve this problem, this paper proposes a microgrid cluster optimization scheduling method based on the sparrow search algorithm. Firstly, construct a microgrid cluster model that includes wind turbines, photovoltaics, energy storage batteries, diesel generators, and hydrogen fuel cells. Secondly, the economic optimum is defined as the objective function, and combined with the constraints of equipment and system operation, the sparrow search algorithm is proposed to solve the optimization model of the microgrid cluster. Finally, this method is used to simulate an IEEE 9-node system with 4 microgrids. The simulation results showed that this method has significant advantages over traditional particle swarm optimization algorithms in reducing total costs and new energy utilization efficiency, verifying the feasibility of this method in microgrid cluster optimization scheduling.

Scientific Reports
State Grid Corporation of China (China) (CN)
Affordable and clean energy
Openalex Percentile: Top 8%
Microgrid Control and Optimization
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