Hierarchical Optimization Strategy Of Park Integrated Energy System With Multiple Agents

Under the trend of high energy efficiency and clean emission,the integrated energy system comes into being.In view of the characteristics of the comprehensive energy system,which supports multi-terminal energy access and accepts the participation of multi-bodies,China also conforms to the trend of gradually opening up the energy market represented by electricity.Under the increasingly open market environment,the current research focus is how to carry out competition-cooperation interaction among different stakeholders in the integrated energy system so as to achieve the maximum benefit.In this paper,for the park-level comprehensive energy system with multiple stakeholders,a hierarchical and distributed scheduling strategy is constructed for its economic scheduling,and the trading mode between multiple stakeholders in the system is optimized by game theory.The advantages and disadvantages of different optimization strategies and their application situations are compared and analyzed through theoretical research and calculation examples.The main research work of this paper is as follows:(1)Aiming at the establish of the park-level comprehensive energy system model with multiple agents,the energy hub theory was first introduced to conduct standardized modeling of the output characteristics and operation constraints of the equipment in the park under this framework.Then a demand response model is constructed for the flexible load,and the user satisfaction is quantified by the energy difference before and after the response.At the same time,the uncertainty of landscape output is dealt with by the scene reduction method,which lays the model foundation for the subsequent research.(2)Aiming at the optimization scheduling problem of the park-level comprehensive energy system with multiple agents,a hierarchical distributed scheduling architecture is constructed.Under this architecture,a park system optimization strategy is proposed with economy as the goal and electricity price optimization as the core,and the park system scheduling problem under this strategy is solved through the objective cascade analysis method.(3)On the basis of distributed scheduling strategy,game theory is introduced to further explore the multi-agent interaction economy.Firstly,the cooperative game based on Nash bargaining theory is introduced to form a cooperative alliance among multiple players in the park,and the economic optimization problem of the park is decoupled into two sub-problems which are solved by objective cascade analysis.Then,non-cooperative game based on Stackelberg theory is introduced to layer the park system.The leader-follower model of the park system is constructed,and the existence of the equilibrium solution of the two-layer master-slave game is proved.The upper and lower levels are solved by genetic algorithm and quadratic programming respectively.(5)The feasibility and effectiveness of the three economic optimization strategies proposed above are verified by numerical examples,and the solution results are analyzed in various aspects to compare the advantages and disadvantages of each strategy and their respective application occasions.The conclusion shows that the three strategies in this paper can achieve the optimal energy of the park system,but because of the different structure and emphasis,the economy is different.Compared with the traditional centralized scheduling strategy,the operation cost of the three strategies proposed in this paper is reduced,which verifies the effectiveness of the model and scheduling strategy established in this paper.