Abstract:

With the development of the energy market, many emerging market agents participate in competition. The increasingly complex coupling of interests between the operators and users of the regional integrated energy system (RIES) make it difficult to formulate effective collaborative optimization strategies. Therefore, this paper proposes an operator-user collaborative optimization strategy based on the distributionally robust game model for RIES. Regarding RIES operators as leaders and users as followers, a Stackelberg game model accounting the uncertainty of wind power on the energy supply side is established. In this model, the leader aims to maximize revenue and establishes a data-driven distributionally robust decision model of the combined heat and power RIES, which takes into account the uncertainty of wind power. Followers establish a comprehensive benefit optimization that considering energy substitution behavior according to time-of-use energy prices. In order to simplify the solution of the proposed distributionally robust game model, the follower model is equivalent to an equilibrium constraint and added to the leader’s decision-making model applying KKT condition, and the two-level game model is transformed into a single-level sub-Brue-bar optimization model. Then, the McCormick method is used to linearize the bilinear term in the leader’s objective function. Finally, the problem is solved by the C&CG algorithm. The experimental results show that, the strategy can satisfy the interests of users and guide them to use energy reasonably through energy price difference, and effectively deal with the uncertain risk of wind power output.

Key words: regional integrated energy system, distributionally robust, Stackelberg game, uncertainty