Distributed Low-Carbon Economic Dispatching for Multiple Park-level Integrated Energy Systems Based on Improved Shapley Value

Multiple park-level integrated energy systems (PIESs) energy sharing can fully exploit the synergies of complementary PIESs to realize the efficient utilization of flexible resources, while it also faces challenges of privacy protection and benefits allocation. Therefore, a distributed low-carbon scheduling model considering game-theoretical energy sharing among PIESs is proposed, and the benefits allocation method is improved. First, the integrated demand response and carbon trading mechanism are combined to motivate the demand-side flexibility potential and promote the low-carbon development. Second, a decentralized energy sharing framework is established based on the cooperative game theory and distributed optimization algorithm. Furthermore, considering the output uncertainties of renewable energy, the accuracy of the renewable energy forecasting results is quantified into the benefits allocation process to improve the traditional Shapley value, thus achieving a more fair and reasonable profits coordination. Finally, case studies verify the effectiveness of the proposed model in reducing carbon emissions, improving the economic performance and coordinating the complex stakeholders.