Cross-Park Dispatch Optimization Strategy for Hybrid Energy Storage Power Systems Considering Carbon–Green Certificate Trading

To alleviate renewable energy curtailment and the high operating costs arising from the temporal and spatial mismatch of distributed generation, this paper develops a cross-park dispatch optimization approach for power systems under the joint participation of carbon trading and green certificate trading (GCT). The proposed approach aims to improve system flexibility and economic performance in coordinated multi-park operation. Specifically, adjustable resources in different parks are dispatched in a coordinated manner, and the total comprehensive operating cost is taken as the optimization objective. In addition, the Alternating Direction Method of Multipliers (ADMM) is adopted to determine inter-park electricity trading prices and exchanged power in a distributed framework. Furthermore, an asymmetric bargaining model is introduced to distribute the cooperative benefits, ensuring a balance between fairness and incentive compatibility. Simulation results demonstrate that inter-park electricity interaction reduces generation costs by 5.29%. The integration of carbon and green certificate trading further reduces costs by 7.4%. After asymmetric bargaining-based benefit allocation, the operating costs of parks with higher contributions decrease by up to 10.34%. The results conclude that the proposed strategy effectively leverages the complementary advantages of multi-park resources and optimizes the synergy between carbon markets, green certificate markets, and physical dispatch.

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Publication Details

Journal
Energies
Published
2026-08-14
DOI
https://doi.org/10.3390/en19163827
Primary Topic
Electric Power System Optimization
Type
article
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article

Cross-Park Dispatch Optimization Strategy for Hybrid Energy Storage Power Systems Considering Carbon–Green Certificate Trading

Shuo Ren, Chunxian Feng, Heng Chen, Yifeng Wang et al.
Energies
Electric Power System Optimization
article

Cross-Park Dispatch Optimization Strategy for Hybrid Energy Storage Power Systems Considering Carbon–Green Certificate Trading

Shuo Ren, Chunxian Feng, Heng Chen, Yifeng Wang, Feifei Zhang, Long Yuan, Wenxue Wang
article en

Abstract

To alleviate renewable energy curtailment and the high operating costs arising from the temporal and spatial mismatch of distributed generation, this paper develops a cross-park dispatch optimization approach for power systems under the joint participation of carbon trading and green certificate trading (GCT). The proposed approach aims to improve system flexibility and economic performance in coordinated multi-park operation. Specifically, adjustable resources in different parks are dispatched in a coordinated manner, and the total comprehensive operating cost is taken as the optimization objective. In addition, the Alternating Direction Method of Multipliers (ADMM) is adopted to determine inter-park electricity trading prices and exchanged power in a distributed framework. Furthermore, an asymmetric bargaining model is introduced to distribute the cooperative benefits, ensuring a balance between fairness and incentive compatibility. Simulation results demonstrate that inter-park electricity interaction reduces generation costs by 5.29%. The integration of carbon and green certificate trading further reduces costs by 7.4%. After asymmetric bargaining-based benefit allocation, the operating costs of parks with higher contributions decrease by up to 10.34%. The results conclude that the proposed strategy effectively leverages the complementary advantages of multi-park resources and optimizes the synergy between carbon markets, green certificate markets, and physical dispatch.

EnergiesVol. 19(16)
North China Electric Power University (CN), State Grid Corporation of China (China) (CN)
Affordable and clean energy
Openalex Percentile: Top 18%
Electric Power System Optimization
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Cross-Park Dispatch Optimization Strategy for Hybrid Energy Storage Power Systems Considering Carbon–Green Certificate Trading — Shuo Ren, Chunxian Feng, et al. · Energies (2026) | TGRS Research Map | TGRS