Considering that the traditional centralized optimized scheduling methods cannot comprehensively reflect the interests of different agents in the integrated energy microgrid and the application of artificial intelligence techniques in integrated energy scheduling is deepened

the coordinated scheduling model and method for grid-connected integrated energy microgrid based on multi-agent game and reinforcement learning are proposed in this paper. Firstly

the multiple investment and operation agents are divided from the perspectives of electrical/heating/cooling subsystems and source/grid/load/storage links

respectively. Secondly

the decision-making models for renewable energy provider

microgrid energy provider and electric vehicle owner are constructed

and the joint game based decision-making model is established with the objective of balancing the multi-agent interests. Thirdly

the artificial intelligence techniques are introduced to solve the highly-dimensional multi-agent game decision-making problem

and the coordinated scheduling method for integrated energy microgrid based on Nash game and Q learning algorithm is proposed. Finally

the effectiveness and applicability of the model and method proposed are verified by case study.