Optimal Dispatch Of Community Integrated Energy System Considering Multiple Objectives

Facing the problems of fossil energy depletion and environmental pollution,building a clean and efficient energy supply system is increasingly recognized by countries around the world.Integrated energy system can integrate a variety of energy inputs and realize the coupling transformation between energy sources.It has significant advantages in absorbing renewable energy for power generation,improving energy efficiency and meeting the diversity of energy supply.In recent years,the acceleration of China's urbanization process makes the total amount of urban buildings rise,the energy consumption of residents' community increases year by year,and residents have higher requirements for comfort.In order to cope with the change of community energy supply,integrated community energy system develops rapidly.Under the background of demand response technology,it is necessary to ensure the comfort of residents,reduce the operating cost of the integrated community energy system and realize good interaction with the power grid.Based on the demand response,this dissertation constructs the optimal scheduling model of integrated community energy system,and uses intelligent algorithm to solve the model to obtain the corresponding scheduling scheme,as follows:In this dissertation,the framework of community integrated energy system is briefly described,the mathematical models of energy conversion equipment and energy storage equipment in community integrated energy system are established,and the coupling relationship between equipments is clarified.The demand response technology is introduced,and the load in the ICES is classified.Taking the minimum operation cost of community integrated energy system as the objective function,the optimal scheduling model of community integrated energy system considering demand response is constructed,and the improved particle swarm optimization algorithm is used to solve the model.The simulation results show that the proposed model can effectively reduce the operation cost of community integrated energy system,and the improved particle swarm optimization algorithm has stronger optimization performance than the traditional particle swarm optimization algorithm.On the premise of not affecting the residents' energy consumption experience,on the one hand,the operation cost of the community integrated energy system is considered,on the other hand,the load of the whole community is smoothly connected to the power grid to stabilize the load fluctuation.This dissertation establishes a multi-objective community integrated energy system optimal scheduling model considering operation cost and load fluctuation,introduces multi-verse optimizer,and proposes a multi-objective multi-verse optimizer based on Pareto theory to solve the model.By setting four scenarios,the operation of community integrated energy system under single objective optimization and multi-objective optimization is compared and analyzed.The simulation results show that the multi-objective scheduling scheme can effectively reduce the operation cost of community integrated energy system,stabilize the load fluctuation,and improve the operation reliability of power grid.At the same time,the performance of multi-objective multi-verse optimizer is better than that of multi-objective particle swarm optimization algorithm.This dissertation provides theoretical support for the scheduling of community integrated energy system.