Research On Optimal Scheduling Of Community Integrated Energy System Considering Source-load Interaction

With the progress of the energy revolution,promoting the transformation of energy use and the development of energy Internet has become an important way to solve the current world energy crisis and environmental degradation.As a typical terminal application form of energy Internet,Community Integrated Energy system(CIES)is a multi-energy network flow system with power system as the core,Internet and communication technology as the foundation,distributed renewable energy as the main primary energy,and closely coupled with natural gas network,transportation network and other systems.On this basis,the mutual coupling and substitution of multiple energy sources also provide a new interactive way for both sides of supply and demand,and the integrated demand response(IDR)strategy arises at the historic moment.Relying on the marketization of energy sources such as electric power and natural gas,it is considered to be an effective way to achieve energy saving and emission reduction,improve energy efficiency and promote local consumption of new energy.and gradually become a key strategy to tap the potential of demand-side response and realize source-load collaborative optimization in the current energy market environment.Based on the above background,this paper carries out the research work from the following aspects: take the CIES as the research object,establish the mathematical model of its key equipment and use the energy bus structure to establish the CIES model,and take the energy cost as the objective function to simulate the CIES economic dispatching model.the electricity and gas demand response model is formed according to the transferable characteristics of electricity and natural gas load in CIES.Considering the heat storage characteristics of building maintenance structure in CIES,the thermal energy demand response model is established,and then the electricity-gas-thermal IDR strategy is established to simulate and analyze the response behavior of all kinds of load under the guidance of energy price signal.the integrated energy service provider(IESP)model is introduced to establish the interactive optimization model of CIES source and load guided by IESP price signal,and IESP is used instead of energy network to guide multi-energy collaborative and flexible transaction,and the electricity and gas price signals are optimized by comprehensively considering the energy demand of the park,the response feedback and the power change of the connection line between the main network and the park.In this paper,a neighborhood center of gravity reverse learning particle swarm optimization algorithm combined with mixed integer linear programming(NCOPSO-MILP)bi-level optimization algorithm is proposed to optimize the price signal of the upper service provider,the demand response of the lower park and the economic dispatching behavior,simulate the interaction between supply and demand,and solve the interaction strategy when each party pursues the interest goal through cyclic iteration.The simulation example shows that the proposed strategy can tap its response potential on the basis of ensuring the participation satisfaction and energy economy of the park,"cut the peak and fill the valley" for the electric interaction power between the park and the main network,and optimize the allocation of system energy resources.improve the overall economy of the system.