Multi-Region Game-Optimized Scheduling of Small Modular Reactors Involved in Energy Supply in Multiple Scenarios

With the increasing penetration of renewable energy sources, there is a pressing need to improve multi-regional Integrated Energy Systems (IES) output flexibility with nuclear participation. However, uncertain information and competitive constraints among multiple interconnected Regional Integrated Energy Systems (RIES) pose challenges to conventional optimal scheduling methods. Therefore, a small modular reactor configured with multiple units is considered to supply electrical energy to the interconnected multi-regional integrated energy system, and a Bayesian game-optimized dispatch strategy is adopted based on the analysis of the incomplete information scenarios among the RIESs. First, the incomplete information scenarios existing between interconnected IESs are analyzed from the source-transfer-load multidimensional perspective, and the optimal scheduling model of the integrated energy system considering multiple uncertainties is constructed. The IES Bayesian game model is established by analyzing the constraints between IESs under the dynamic price mechanism. The existence and uniqueness of the Nash equilibrium solution are proved, and the decision-making game algorithm is used to optimize the scheduling of interconnected RIESs under the multiple uncertainty scenario. Finally, the simulation verification is carried out with the IES interconnected by three RIESs as an example. The results show that the optimal scheduling scheme of a regional interconnected IES constructed by the game model considering multiple uncertainties is reasonable and feasible to improve the system's economic efficiency while considering the environmental pollution problem.