Research On Operation Optimization Of Regional Integrated Energy System With Interaction Of Supply And Demand

The integrated energy system is a multi-energy joint supply system centered on the power system,which realizes multi-energy cooperation,complementarity and energy cascade utilization by using the mutual coupling of energy.And the system also provides a crucial mean to solve the energy and environmental problems at present.Therefore,it is of great significance to research the operation optimization of the integrated energy system.For the optimization of the comprehensive energy system,accurate load prediction on the demand side is the fundamental precondition of the optimization of the integrated energy system,and how to optimize the supply-side and demand-side resources of the comprehensive energy system is the key to improve the performance of the integrated energy system.Thus,this paper takes the interaction between supply and demand of the comprehensive energy system as the starting point to study the operation optimization of the comprehensive energy system.The main contents of this paper are as follows.Firstly,the components and the working principle of the integrated energy system are introduced in this paper.According to the function of each equipment,the equipment of the integrated energy system is divided into energy supply equipment,conversion equipment,new energy generation equipment and energy storage equipment.The mathematical models of gas turbine,gas boiler,electric refrigerator,absorption refrigerator,electricity-to-gas equipment,energy storage equipment and photovoltaic power generation equipment are established and analyzed.Secondly,the multi-load forecasting problem of the integrated energy system is researched.This paper analyzes the prediction methods of Elman neural network,traditional wavelet neural network,and it also points out the defects of traditional wavelet prediction.In order to solve the problem that the traditional wavelet neural network load prediction model of the integrated energy system has some shortcomings(such as slow convergence speed and easily falling into local optimality)leading to low prediction accuracy,a short-term load prediction method of wavelet neural network based on improved particle swarm optimization is proposed.Thirdly,this paper also researched the integrated demand response.As an important way of interaction between supply and demand in the system,this paper adopts different demand response strategies according to different load types and divides the comprehensive demand response into three types:price demand response,direct control demand response and substitution load demand response.The three different response mathematical models are established and the principle of their response is analyzed in the different model.On this basis,a demand response strategy for a regionally integrated energy system is proposed.Finally,in this paper,the optimization of the regionally integrated energy system is researched.On the basis of determining the demand-side load and the schedulable load,the multi-objective optimization model of the integrated energy system with the interaction between supply and demand was established with propose of optimizing the economic,environmental and energy efficiency,and the Minlp algorithm was used to optimize the model.The results verified in a housing estate integrated energy system in Qingdao show that the optimization method proposed in this paper can effectively improve the performance of the integrated energy system.