Research on collaborative optimization of the electric-carbon joint market based on renewable energy subsidies - Xia, Peng; Yuan, Bo; Lu, Gang; Zhao, Qiuli; Zhang, Fuqiang; Zhou, Suyang (Frontiers in Physics, 2025)
This paper addresses the current challenges in coordinating interactions between the power market and the carbon market, particularly the shortcomings arising from the insufficient consideration of renewable energy subsidies. To tackle these issues, we propose a collaborative optimization approach for an integrated electric–carbon market that incorporates a renewable subsidy mechanism. The aim is to foster deeper integration between the power and carbon markets, enhance the share of clean energy in the overall mix, and drive low-carbon transitions. A joint market clearing model is constructed that explicitly includes renewable subsidy costs in the objective function, thereby capturing the true cost-benefit dynamics of renewable projects. A case study based on a regional power system demonstrates the model’s effectiveness and feasibility, with the Particle Swarm Optimization (PSO) algorithm successfully converging to a near-optimal solution. This research not only provides theoretical support for the real-world application of coordinated electric–carbon market operations but also offers significant practical value by incorporating renewable energy incentives into the market design.