Multi-Market Coupling Mechanism of Offshore Wind Power with Energy Storage Participating in Electricity, Carbon, and Green Certificates

Wenchuan Meng (), Zaimin Yang, Jingyi Yu, Xin Lin, Ming Yu and Yankun Zhu
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Wenchuan Meng: Energy Development Research Institute, China Southern Power Grid, Guangzhou 510663, China
Zaimin Yang: School of Electrical Engineering, Zhejiang University, Hangzhou 310027, China
Jingyi Yu: Energy Development Research Institute, China Southern Power Grid, Guangzhou 510663, China
Xin Lin: Power Grid Planning Research Center, Guangxi Power Grid, Nanning 530013, China
Ming Yu: Power Grid Planning Research Center, Guangxi Power Grid, Nanning 530013, China
Yankun Zhu: School of Automation, Wuhan University of Technology, Wuhan 430070, China

Energies, 2025, vol. 18, issue 15, 1-22

Abstract: With the support of the dual-carbon strategy and related policies, China’s offshore wind power has experienced rapid development. However, constrained by the inherent intermittency and volatility of wind power, large-scale expansion poses significant challenges to grid integration and exacerbates government fiscal burdens. To address these critical issues, this paper proposes a multi-market coupling trading model integrating energy storage-equipped offshore wind power into electricity–carbon–green certificate markets for large-scale grid networks. Firstly, a day-ahead electricity market optimization model that incorporates energy storage is established to maximize power revenue by coordinating offshore wind power generation, thermal power dispatch, and energy storage charging/discharging strategies. Subsequently, carbon market and green certificate market optimization models are developed to quantify Chinese Certified Emission Reduction (CCER) volume, carbon quotas, carbon emissions, market revenues, green certificate quantities, pricing mechanisms, and associated economic benefits. To validate the model’s effectiveness, a gradient ascent-optimized game-theoretic model and a double auction mechanism are introduced as benchmark comparisons. The simulation results demonstrate that the proposed model increases market revenues by 17.13% and 36.18%, respectively, compared to the two benchmark models. It not only improves wind power penetration and comprehensive profitability but also effectively alleviates government subsidy pressures through coordinated carbon–green certificate trading mechanisms.

Keywords: offshore wind power; energy storage; multi-market coupling; optimization scheduling (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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