Integrated energy multi-objective optimization based on PARETO-GWO considering demand response

Under the background of “double carbon”, in order to effectively improve the energy utilization of regional integrated energy system (RIES), reduce carbon emissions, and improve the flexibility of system operation, this paper proposes a multi-objective optimization model based on PARETO-GWO and considering demand response RIES. Firstly, the modeling is carried out for RIES containing cooling, heating and electricity. Then a demand response model containing transferable, curtailable and replaceable thermal and electric loads is established. Finally, by intro-ducing external population Archive library and Pareto-based non-dominated solution GWO algorithm to obtain mul-ti-scenario operation strategies, the impact of demand response on RIES multi-objective optimization and power bias of units with different operation strategies are analyzed and demonstrated, and it is verified that multi-objective opti-mization can achieve more effective unification of system operation cost and carbon emission than single-objective scheduling.