Abstract: With the development of distributed energy resources, there is an increasing trend for traditional users to become production and consumption users (PCUs) with generation capacity, and this paper focuses on the cooperative operation of many production and consumption users under the same micro-energy network. The tariff uncertainty and the response of production and consumption users bring difficulties in scheduling between PCUs with different interests in micro energy networks. In this context, a hybrid game optimization strategy between the micro energy network and the consumers is proposed to consider the response of the consumers and the tariff uncertainty. First, the consumer response model and the tariff uncertainty model are constructed, the utility function is introduced to describe the satisfaction degree of PCU, and the robust optimization and opportunity constraint methods are used to describe the tariff uncertainty and the uncertainty of new energy output. Second, a hybrid game model is constructed, i.e., a master-slave game model between the upper-layer Integrated Energy Operator (IEO) and the lower-layer PCUs and a cooperative game model between the lower-layer PCU alliances. As the leader of the master-slave game, the upper-level IEO aims to minimize the operation cost and guide the energy demand of the consumers and producers by setting the electricity and heat prices for them. In contrast, the lower-level consumers, and producers, as the followers, aim to maximize revenues by cooperating and responding to the decisions made by the IEOs. The cooperative game between the PCUs is carried out in a Nash bargaining manner, which makes the PCU model equivalent to two sub-problems: maximizing the union's revenues and cooperative allocation subproblems. Based on the KKT condition, the two-layer problem is converted into a single-layer mixed-integer linear programming problem by using the Big-M method and McCormick's envelope method to solve the master-slave game, and the lower cooperative game is solved by combining the alternating direction multiplier method (ADMM). The results show that the strategy proposed in this paper effectively coordinates the scheduling of the micro energy network and PCUs and ensures the fairness of the cooperative union of PCUs.