Energy Management of V2G‐Containing Multiource Microgrid Cluster Based on Two‐Layer Hybrid Game

With the large‐scale entry of electric vehicles into the grid, the impact on the new power system with new energy as the main status is gradually expanding. Utilizing V2G technology to make vehicle–network interaction, a two‐layer hybrid game energy management transaction method for multisource microgrid clusters is proposed. The upper layer constructs a microgrid group transaction model containing an energy management system based on a cooperative game; the lower layer constructs a master–slave game model with each microgrid as the leader and its interest as the objective function, and the follower EV aggregator adjusts the charging and discharging time according to the net power to strive for its maximum interest. The model is optimally solved by the CPLEX solver through simulation cases, and the results verify the effectiveness and superiority of the proposed two‐layer hybrid game model.

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Publication Details

Journal
International Transactions on Electrical Energy Systems
Published
2025-01-01
DOI
https://doi.org/10.1155/etep/6795794
Citations
1
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
0.73

Funders

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article

Energy Management of V2G‐Containing Multiource Microgrid Cluster Based on Two‐Layer Hybrid Game

Mei Li, Z. Yu
1 citations
International Transactions on Electrical Energy Systems
Electric Vehicles and Infrastructure
0.73
article

Energy Management of V2G‐Containing Multiource Microgrid Cluster Based on Two‐Layer Hybrid Game

Mei Li, Z. Yu
article en
1 citations

Abstract

With the large‐scale entry of electric vehicles into the grid, the impact on the new power system with new energy as the main status is gradually expanding. Utilizing V2G technology to make vehicle–network interaction, a two‐layer hybrid game energy management transaction method for multisource microgrid clusters is proposed. The upper layer constructs a microgrid group transaction model containing an energy management system based on a cooperative game; the lower layer constructs a master–slave game model with each microgrid as the leader and its interest as the objective function, and the follower EV aggregator adjusts the charging and discharging time according to the net power to strive for its maximum interest. The model is optimally solved by the CPLEX solver through simulation cases, and the results verify the effectiveness and superiority of the proposed two‐layer hybrid game model.

International Transactions on Electrical Energy SystemsVol. 2025(1)
Anhui University of Science and Technology (CN)
University Natural Science Research Project of Anhui Province
Openalex Percentile: Top 30%
Electric Vehicles and Infrastructure
0.73
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