Author
Listed:
- Chao Zheng
(Yunnan Power Dispatching Control Center, Yunnan Power Grid Co., Ltd., Kunming 650011, China)
- Wei Huang
(Kunming Power Dispatching Control Center, Kunming Power Supply Bureau, Yunnan Power Grid Co., Ltd., Kunming 650010, China)
- Suwei Zhai
(Yunnan Power Dispatching Control Center, Yunnan Power Grid Co., Ltd., Kunming 650011, China)
- Guobiao Lin
(Dongfang Electronics Cooperation, Yantai 264010, China)
- Xuehao He
(Electric Power Research Institute of China Southern Power Grid Yunnan Power Grid Co., Ltd., Kunming 650217, China)
- Guanzheng Fang
(Dongfang Electronics Cooperation, Yantai 264010, China)
- Shi Su
(Electric Power Research Institute of China Southern Power Grid Yunnan Power Grid Co., Ltd., Kunming 650217, China)
- Di Wang
(School of Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China)
- Qian Ai
(School of Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China)
Abstract
Against the backdrop of global low-carbon transition, the integrated development of electricity and carbon markets demands higher efficiency in the optimal operation of virtual power plants (VPPs) and distribution networks, yet conventional trading mechanisms face limitations such as inadequate recognition of differentiated contributions and inequitable benefit allocation. To address these challenges, this paper proposes a collaborative optimal trading mechanism for VPP clusters and distribution networks in an electricity–carbon coupled market environment by first establishing a joint operation framework to systematically coordinate multi-agent interactions, then developing a bi-level optimization model where the upper level formulates peer-to-peer (P2P) trading plans for electrical energy and carbon allowances through cooperative gaming among VPPs while the lower level optimizes distribution network power flow and feeds back the electro-carbon comprehensive price (EACP). By introducing an asymmetric Nash bargaining model for fair benefit distribution and employing the Alternating Direction Method of Multipliers (ADMM) for efficient computation, case studies demonstrate that the proposed method overcomes traditional models’ shortcomings in contribution evaluation and profit allocation, achieving 2794.8 units in cost savings for VPP clusters while enhancing cooperation stability and ensuring secure, economical distribution network operation, thereby providing a universal technical pathway for the synergistic advancement of global electricity and carbon markets.
Suggested Citation
Chao Zheng & Wei Huang & Suwei Zhai & Guobiao Lin & Xuehao He & Guanzheng Fang & Shi Su & Di Wang & Qian Ai, 2025.
"Collaborative Operation Strategy of Virtual Power Plant Clusters and Distribution Networks Based on Cooperative Game Theory in the Electric–Carbon Coupling Market,"
Energies, MDPI, vol. 18(16), pages 1-25, August.
Handle:
RePEc:gam:jeners:v:18:y:2025:i:16:p:4395-:d:1726950
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