Integrated Energy System Optimization Based On Multi-objective Evolutionary Algorithm

Accompanied by development of human society and the progress of science and technology,more and more attention has been paid to multi-objective optimization problems in various industrial fields.Multi-objective optimization problems are very common in engineering applications nowadays.Therefore,studying multi-objective optimization problems and improving algorithms related to multi-objective optimization problems have strong practical significance.Early research on integrated energy systems mainly aimed at economic optimization.However,accompanied by the increasingly serious problems of environmental pollution and resource shortage,factors such as energy consumption and carbon emissions should be considered in addition to costs.Therefore,the optimization of integrated energy system has changed from single objective problem to multi-objective problem.Nowadays,the development of integrated energy system is restricted by many factors.In addition to the multi-objective optimization algorithm,the lack of appropriate operation strategy optimization method is also an important factor restricting its development.In this thesis,the optimization model of integrated energy system does not fully consider factors such as environmental pollution and energy loss.And the multi-objective evolutionary algorithm has the problems of slow operation speed,poor convergence,low discrimination of operation plan optimization results,and unreasonable index weight determination.A new operation optimization model of integrated energy system is constructed,and the multi-objective evolutionary algorithm and operation strategy optimization method are improved.The specific work is as follows:Aiming at the problems of insufficient consideration of pollutant emission model and poor convergence of multi-objective evolutionary algorithm in the optimization process of integrated energy system.Firstly,the electricity purchase cost,gas cost and maintenance cost are taken as the operation cost,and the treatment cost of CO₂,SO₂ and NO_x is taken as the environmental cost.A comprehensive energy system operation optimization model considering operational and environmental costs is established.Secondly,in order to overcome the shortcomings of NSGA-2-DE algorithm,such as slow running speed and poor convergence.An improved NSGA-2-DE algorithm based on efficient non-dominated sort is proposed.Finally,the superiority of the improved algorithm proposed in this thesis is verified by an example analysis of the actual integrated energy system.The optimization method of integrated energy system does not fully consider the energy loss model of energy conversion device,which easily leads to the problem of low energy utilization rate.Firstly,an optimal operation model of integrated energy system considering energy loss and flexibility is constructed,and the Pareto optimal solution set of system operation strategy is obtained by using improved NSGA-2-DE algorithm.Secondly,in order to obtain the best solution from the Pareto optimal solution set,a TOPSIS optimization method based on improved game theory combined weighting is proposed.Finally,an example of an integrated energy system in a park is analyzed to verify the accuracy and effectiveness of the method in this thesis.