A Coordinated Operation Optimization Model for Multiple Microgrids and Shared Energy Storage Based on Asymmetric Bargaining Negotiations

The promotion of local renewable energy consumption and stable power gird (the latter is referred to as PG) operation have emerged as the primary objectives of power system reform. The integration of multiple microgrids with distinct characteristics through the utilization of shared energy storage (the following is referred to as SES) facilitates coordinated operation. This approach enables the balancing of energy across temporal and spatial domains, contributing to the overall reliability and security of the energy network. The proposed model outlines a methodology for the coordinated operation of multiple microgrids and SES, with a focus on asymmetric price negotiation. Initially, cost and revenue models for microgrids and SES power plants are established. Secondly, an asymmetric pricing method based on the magnitude of each entity’s energy contribution is proposed. A profit optimization model is also established. The model can be decomposed into two distinct subproblems: the maximization of overall profit and the negotiation of transaction prices. The model can be solved by employing the alternating direction method of multipliers (ADMM). Finally, a series of case studies were conducted for the purpose of validating the operation optimization model that was previously constructed. These studies demonstrate that the model enhances collective operational efficiency by 44.69%, with each entity’s efficiency increasing by at least 12%. At the same time, cooperative benefits are distributed fairly according to each entity’s energy contribution.

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Publication Details

Journal
Processes
Published
2025-08-09
DOI
https://doi.org/10.3390/pr13082514
Primary Topic
Microgrid Control and Optimization
Type
article
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0.00
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article

A Coordinated Operation Optimization Model for Multiple Microgrids and Shared Energy Storage Based on Asymmetric Bargaining Negotiations

Huimin Wu, Xiaotong Zhou, Yao Wang, Jia Li et al.
Processes
Microgrid Control and Optimization
article

A Coordinated Operation Optimization Model for Multiple Microgrids and Shared Energy Storage Based on Asymmetric Bargaining Negotiations

Huimin Wu, Xiaotong Zhou, Yao Wang, Jia Li, Zhongfu Tan, Yingying Hu, Liwei Ju
article en

Abstract

The promotion of local renewable energy consumption and stable power gird (the latter is referred to as PG) operation have emerged as the primary objectives of power system reform. The integration of multiple microgrids with distinct characteristics through the utilization of shared energy storage (the following is referred to as SES) facilitates coordinated operation. This approach enables the balancing of energy across temporal and spatial domains, contributing to the overall reliability and security of the energy network. The proposed model outlines a methodology for the coordinated operation of multiple microgrids and SES, with a focus on asymmetric price negotiation. Initially, cost and revenue models for microgrids and SES power plants are established. Secondly, an asymmetric pricing method based on the magnitude of each entity’s energy contribution is proposed. A profit optimization model is also established. The model can be decomposed into two distinct subproblems: the maximization of overall profit and the negotiation of transaction prices. The model can be solved by employing the alternating direction method of multipliers (ADMM). Finally, a series of case studies were conducted for the purpose of validating the operation optimization model that was previously constructed. These studies demonstrate that the model enhances collective operational efficiency by 44.69%, with each entity’s efficiency increasing by at least 12%. At the same time, cooperative benefits are distributed fairly according to each entity’s energy contribution.

ProcessesVol. 13(8)
North China Electric Power University (CN), State Grid Corporation of China (China) (CN)
Affordable and clean energy
Openalex Percentile: Top 75%
Microgrid Control and Optimization
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