Optimization of Operation Strategy of Multi-Islanding Microgrid Based on Double-Layer Objective

The shared energy storage device acts as an energy hub between multiple microgrids to better play the complementary characteristics of the microgrid power cycle. In this paper, the cooperative operation process of shared energy storage participating in multiple island microgrid systems is researched, and the two-stage research on multi-microgrid operation mode and shared energy storage optimization service cost is focused on. In the first stage, the output of each subject is determined with the goal of profit optimization and optimal energy storage capacity, and the modified grey wolf algorithm is used to solve the problem. In the second stage, the income distribution problem is transformed into a negotiation bargaining process. The island microgrid and the shared energy storage are the two sides of the game. Combined with the non-cooperative game theory, the alternating direction multiplier method is used to reduce the shared energy storage service cost. The simulation results show that shared energy storage can optimize the allocation of multi-party resources by flexibly adjusting the control mode, improving the efficiency of resource utilization while improving the consumption of renewable energy, meeting the power demand of all parties, and realizing the sharing of energy storage resources. Simulation results show that compared with the traditional PSO algorithm, the iterative times of the GWO algorithm proposed in this paper are reduced by 35.62%, and the calculation time is shortened by 34.34%. Compared with the common GWO algorithm, the number of iterations is reduced by 18.97%, and the calculation time is shortened by 22.31%.

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Publication Details

Journal
Energies
Published
2024-09-14
DOI
https://doi.org/10.3390/en17184614
Citations
9
Primary Topic
Islanding Detection in Power Systems
Type
article
Field-Weighted Citation Impact
1.88
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article

Optimization of Operation Strategy of Multi-Islanding Microgrid Based on Double-Layer Objective

Yingying Hu, Yongming Jing, Zheng Shi, Jiaojiao Deng et al.
9 citations
Energies
Islanding Detection in Power Systems
1.88
article

Optimization of Operation Strategy of Multi-Islanding Microgrid Based on Double-Layer Objective

Yingying Hu, Yongming Jing, Zheng Shi, Jiaojiao Deng, Zhi Zhang, Yan Lu, Haibo Zhao, Wenping Qin, Yan Liang, Yao Wang
article en
9 citations

Abstract

The shared energy storage device acts as an energy hub between multiple microgrids to better play the complementary characteristics of the microgrid power cycle. In this paper, the cooperative operation process of shared energy storage participating in multiple island microgrid systems is researched, and the two-stage research on multi-microgrid operation mode and shared energy storage optimization service cost is focused on. In the first stage, the output of each subject is determined with the goal of profit optimization and optimal energy storage capacity, and the modified grey wolf algorithm is used to solve the problem. In the second stage, the income distribution problem is transformed into a negotiation bargaining process. The island microgrid and the shared energy storage are the two sides of the game. Combined with the non-cooperative game theory, the alternating direction multiplier method is used to reduce the shared energy storage service cost. The simulation results show that shared energy storage can optimize the allocation of multi-party resources by flexibly adjusting the control mode, improving the efficiency of resource utilization while improving the consumption of renewable energy, meeting the power demand of all parties, and realizing the sharing of energy storage resources. Simulation results show that compared with the traditional PSO algorithm, the iterative times of the GWO algorithm proposed in this paper are reduced by 35.62%, and the calculation time is shortened by 34.34%. Compared with the common GWO algorithm, the number of iterations is reduced by 18.97%, and the calculation time is shortened by 22.31%.

EnergiesVol. 17(18)
North China Electric Power University (CN), State Grid Corporation of China (China) (CN), Taiyuan University of Technology (CN)
Openalex Percentile: Top 14%
Islanding Detection in Power Systems
1.88
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