Coordinated optimal operation of multi-microgrids and distribution network considering shared energy storage multi-package leasing

To further explore the cooperation potential of each subject within a distribution network (DN) with multi-microgrids (MMGs), and to improve the utilization rate of energy storage, a cooperative optimal operation strategy of DN and MMGs that considers the shared energy storage system (SESS) multi-package leasing is proposed. Firstly, the DN and MMGs operate as a cooperative alliance. The DN ensures security and optimizes its operation by utilizing the reactive power provided by the MMGs. Secondly, considering the leasing of the SESS by the MMGs to promote the local consumption of renewable energy, a master-slave game model is established between the SESS and the MMGs-DN alliance. The SESS acts as the master and designs two types of packages. The MMGs act as slaves and choose the packages as well as the amount of energy storage usage. Afterward, on the basis of Nash bargaining theory, a two-stage cooperative revenue allocation model is constructed for the DN and MMGs to determine the incentive price of reactive power for MGs to participate in optimizing the DN and peer to peer (P2P) trading price between the MMGs, thereby achieving a win-win situation for the alliance participants. Finally, a simulation is conducted based on the modified IEEE 33-node system, and the results demonstrate the effectiveness of the proposed method. • Two shared energy storage leasing packages are designed. • A master-slave game model of SESS and MMGs-DN alliance is established. • An optimal model based on the cooperation game is established between MMGs and DN. • Distributed solution using the ADMM with an adaptive penalty factor.

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Publication Details

Journal
Journal of Energy Storage
Published
2026-02-18
DOI
https://doi.org/10.1016/j.est.2026.121064
Citations
2
Primary Topic
Microgrid Control and Optimization
Type
article
Field-Weighted Citation Impact
50.09
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article

Coordinated optimal operation of multi-microgrids and distribution network considering shared energy storage multi-package leasing

Meijia Wei, Jian Chen, Da Lin, Wen Zhang et al.
2 citations
Journal of Energy Storage
Microgrid Control and Optimization
50.09
article

Coordinated optimal operation of multi-microgrids and distribution network considering shared energy storage multi-package leasing

Meijia Wei, Jian Chen, Da Lin, Wen Zhang, Keyu Zhang
article en
2 citations

Abstract

To further explore the cooperation potential of each subject within a distribution network (DN) with multi-microgrids (MMGs), and to improve the utilization rate of energy storage, a cooperative optimal operation strategy of DN and MMGs that considers the shared energy storage system (SESS) multi-package leasing is proposed. Firstly, the DN and MMGs operate as a cooperative alliance. The DN ensures security and optimizes its operation by utilizing the reactive power provided by the MMGs. Secondly, considering the leasing of the SESS by the MMGs to promote the local consumption of renewable energy, a master-slave game model is established between the SESS and the MMGs-DN alliance. The SESS acts as the master and designs two types of packages. The MMGs act as slaves and choose the packages as well as the amount of energy storage usage. Afterward, on the basis of Nash bargaining theory, a two-stage cooperative revenue allocation model is constructed for the DN and MMGs to determine the incentive price of reactive power for MGs to participate in optimizing the DN and peer to peer (P2P) trading price between the MMGs, thereby achieving a win-win situation for the alliance participants. Finally, a simulation is conducted based on the modified IEEE 33-node system, and the results demonstrate the effectiveness of the proposed method. • Two shared energy storage leasing packages are designed. • A master-slave game model of SESS and MMGs-DN alliance is established. • An optimal model based on the cooperation game is established between MMGs and DN. • Distributed solution using the ADMM with an adaptive penalty factor.

Journal of Energy StorageVol. 153
Electric Power Research Institute (US), Shandong University (CN), State Grid Corporation of China (China) (CN), Shanghai Electric (China) (CN)
Affordable and clean energy
Openalex Percentile: Top 0%
Microgrid Control and Optimization
50.09
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