Research on the Operation of Complementary Microgrid System for Wind-Solar-Hydro-Storage Based on DEPSO

With the increasing demand for green energy transition, multi-energy complementary microgrid systems that integrate wind, solar, hydro, and storage have become a popular research focus due to their efficient, clean, and stable energy supply characteristics. This system combines wind power, photovoltaics, hydropower, and energy storage, effectively mitigating the output fluctuations of renewable energy sources, achieving self-sufficiency, and enabling flexible energy regulation. In response, this paper establishes a model aimed at minimizing system fluctuations and optimizing economic performance, taking into account various system constraints. The model is solved using the Differential Evolution Particle Swarm Optimization (DEPSO) algorithm. Through case analysis, both the Particle Swarm Optimization (PSO) algorithm and the DEPSO algorithm are applied to the multi-energy complementary microgrid system, allowing a comparative analysis of equipment output and total operating costs. The experimental results confirm the effectiveness of the proposed algorithm.

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Publication Details

Published
2024-11-29
DOI
https://doi.org/10.1109/ei264398.2024.10990606
Primary Topic
Power Systems and Renewable Energy
Type
article
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article

Research on the Operation of Complementary Microgrid System for Wind-Solar-Hydro-Storage Based on DEPSO

Ruicheng Feng, Di Liu, Fanhua Meng, Likui Yi
Power Systems and Renewable Energy
article

Research on the Operation of Complementary Microgrid System for Wind-Solar-Hydro-Storage Based on DEPSO

Ruicheng Feng, Di Liu, Fanhua Meng, Likui Yi
article en

Abstract

With the increasing demand for green energy transition, multi-energy complementary microgrid systems that integrate wind, solar, hydro, and storage have become a popular research focus due to their efficient, clean, and stable energy supply characteristics. This system combines wind power, photovoltaics, hydropower, and energy storage, effectively mitigating the output fluctuations of renewable energy sources, achieving self-sufficiency, and enabling flexible energy regulation. In response, this paper establishes a model aimed at minimizing system fluctuations and optimizing economic performance, taking into account various system constraints. The model is solved using the Differential Evolution Particle Swarm Optimization (DEPSO) algorithm. Through case analysis, both the Particle Swarm Optimization (PSO) algorithm and the DEPSO algorithm are applied to the multi-energy complementary microgrid system, allowing a comparative analysis of equipment output and total operating costs. The experimental results confirm the effectiveness of the proposed algorithm.

Shenyang Institute of Engineering (CN)
Affordable and clean energy
Openalex Percentile: Top 62%
Power Systems and Renewable Energy
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