A two-layer game optimization strategy for an integrated energy system considering multiple responses and renewable energy uncertainty

Abstract

The integrated energy system (IES) is one of the most important developments in the field of multi-energy coupling, where the conflict of interests between different market players poses significant challenges to the economic, stable and efficient operation. To address this problem, this study proposes a two-layer game optimization strategy for an IES considering multiple responses and renewable energy uncertainty. First, on the energy supply side, a flexible response model for the heat and electricity output of a combined heat and power unit is constructed by introducing the Kalina cycle and an electric boiler. Based on the principle of electricity-heat-cooling calorific value equivalence, an integrated demand response model containing energy use conversion is established on the energy demand side. Second, the uncertainty in renewable energy output is addressed by constructing a robust model based on a polyhedral uncertainty set. Then, using the energy retailer (ER) as the leader and the energy producer (EP) and user agent (UA) as the followers, a one-master-multiple-slaves Stackelberg game model is established. Finally, the model is simulated and analyzed using the distributed method of the improved Dual-Mutation Differential Evolution (DMDE) algorithm nested CPLEX solver. The results indicate that the proposed optimal strategy can optimize the multiple parties' conflict of interests, which makes the benefits of EP, ER, and UA increase by 19.68 %, 38.63 %, and 9.36 %, respectively, and effectively balances the robustness and economy of the system. Compared with the traditional algorithms, the DMDE algorithm has significant advantages in terms of solution time and iteration number.