Optimization Method for Park Integrated Energy Systems Considering Carbon Reduction Value Transfer and Source-Load Mapping

To address the issue of value fragmentation among the electricity market, carbon market, and green certificate (GC) market in park integrated energy systems (IES), as well as the insufficient exploitation of low-carbon regulation potential on the user side, a multi-agent collaborative optimal scheduling method for park IES considering carbon asset value coupling and user low-carbon contribution incentives is proposed. Firstly, an electricity-carbon-GC multi-market coupling mechanism is constructed. By establishing the mapping relationship among renewable energy accommodation, GC revenue, and carbon reduction value, the unified quantification of the environmental value of renewable energy is achieved. Secondly, a user low-carbon demand response mechanism based on the renewable energy accommodation contribution index is proposed. This mechanism transforms user load adjustment behaviors into quantifiable carbon asset revenues, thereby guiding users to actively participate in renewable energy accommodation. Furthermore, a multi-agent Stackelberg collaborative optimization model is developed, with the IES operator acting as the leader, and the park, energy storage, and renewable energy entities acting as followers. This model achieves the coordinated optimization of economic benefits, carbon emissions, and renewable energy accommodation capacity. Case study results demonstrate that the proposed method can effectively enhance the system"s operational economy, improve the utilization rate of renewable energy, and reduce carbon emissions.