Abstract

Introduction: With the development of the energy market and the gradual rise of emerging market players, the linkage of interests between energy sources and loads in the Integrated Energy System (IES) has become increasingly complex. Additionally, the reliability of the system has been impacted by the growing proportion of renewable energy output.Methods: To address the challenges posed by the above issues. This paper first proposes an operational strategy for an integrated energy system that incorporates the uncertainty of wind and solar output using a master-slave game approach. To enhance system robustness and cost-effectiveness, the paper introduces the information gap decision theory (IGDT). Second, building on this foundation, the system operator is considered as the leader, adding a tiered carbon trading mechanism and cloud energy storage system, and building a system revenue maximization model. Then, the user is regarded as the follower, and an optimization model is developed based on integrated demand response (IDR). Finally, the two-layer model is converted into a mixed-integer linear programming problem (MILP) to be solved by the Karush-Kuhn-Tucker conditions (KKT) combined with the big M method.Results: The analysis of the example shows that according to the difference of the decision maker’s attitude towards risk, different scheduling schemes can be obtained through the two perspectives of risk-seeking and risk-avoiding, which can provide guidance for the dynamic operation of the system, and at the same time, the users can be guided by the energy differentials to reasonably use the energy under this strategy.Discussion: Therefore, the proposed strategy in this paper can balance the economy and robustness of the system.

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