Research On Multi-Agent Game Strategy Of Integrated Energy System

At present,the world is facing the problems of energy shortage and environmental pollution.The integrated energy system with multi-energy coupling can realize the coordinated operation of different energy sources,effectively improve the energy utilization efficiency and reduce the operating cost of the system.It plays an important role in realizing the goal of "dual carbon" and promoting the sustainable development of energy.With the opening of the energy market,the coupling relationship between different market entities in the comprehensive energy system is becoming more and more complex.It is difficult to describe the pricing mechanism and operation strategy of each subject in the system,because the optimization of the system as a whole can no longer meet the interest demands of each market subject.Therefore,the introduction of game theory into the multi-agent operation optimization of the integrated energy system can take into account the interests of all parties and optimize the operation strategy of each agent.The main research contents of this thesis are as follows:(1)Establish an integrated energy system infrastructure framework including energy operators and user clusters,and analyze the characteristics and functions of each subject.Modeling the internal equipment of energy operators,including wind turbine,gas turbine,gas boiler,waste heat boiler,P2G(Power to Gas),gas storage equipment and other models.Analyze the user’s energy consumption reduction,transfer and transformation behavior,and establish the user cluster energy consumption behavior model.It lays a foundation for building the multi-agent game model of integrated energy system.(2)The stackelberg game strategy of integrated energy system considering electric vehicle access is proposed.The interactive framework between the integrated energy operator and the user cluster is established.The bus exchange station and electric Vehicle are introduced into the operator and the user side respectively,and the bus exchange station is used as the power storage equipment of the operator.Meanwhile,the electric vehicle is divided into electric exchange bus and electric private car with V2G(Vehicle to Grid)function,and the Monte Carlo method is used to simulate the user behavior.On this basis,an optimization model is established for operators and user clusters to maximize their own interests,in which operators determine the energy purchase strategy from the superior energy network,the operation strategy of internal equipment and the energy sale strategy to user clusters,and user clusters determine the energy purchase strategy from operators,forming a stackelberg game pattern of supply and demand side.The example analysis shows that the integrated energy system with the participation of electric vehicles and bus exchange stations can effectively improve the wind power consumption capacity and protect the interests of operators and user clusters.(3)The game strategy of the three market players in the integrated energy system is proposed.Multiple energy suppliers form a non-cooperative game pattern,and energy suppliers,energy operators and user clusters form a tripartite market stackelberg game pattern.The game is divided into two stages.In the first stage,the operator formulates the energy purchase power,dynamic energy sale price and adjusts the operating status of internal equipment according to the historical energy sale price of the supplier and the load forecast data of the user cluster.The second stage is the supplydemand side game.On the supply side,the supplier sets the energy sale price by adjusting the power-price curve according to the purchase power of the operator.On the demand side,user clusters adjust energy consumption strategies according to the dynamic energy selling price of operators.The example analysis shows that the participation of energy suppliers in the energy market competition can improve their own profits,prevent the monopoly behavior in the market,and the operators can coordinate the competition among energy suppliers to ensure their own profits.User clustering can reduce energy costs.There are 31 figures,7 tables and 83 references in this thesis.