Multi-Objective Optimization And Decision-Making And Its Application In Microgrid Scheduling

Microgrid optimization scheduling is a multi-objective optimization problem with multiple constraints,high dimensions,and nonlinearity,which puts forward higher requirements for algorithm performance and rationality of decision-making.For the multiobjective optimization scheduling problem of microgrids,the use of intelligent optimization algorithms for linearly weighted models has drawbacks such as being prone to falling into local optima and low convergence accuracy.It is worth studying how to improve the performance of the algorithm on the basis of traditional algorithms;From the perspective of multi-objective decision-making,microgrid scheduling problems often set multiple optimization objectives.When using the Pareto optimal solution method to solve,how to select a compromise optimal solution from the Pareto optimal solution set also has important theoretical significance and application value.Therefore,this article proposes solutions to multi-objective optimization problems at the algorithmic and decision-making levels,and applies them to multi-objective optimization problems in microgrids,the main contents of this thesis are as follows.1.Aiming at the multi-objective optimal scheduling problem of grid-connected microgrids.Firstly,a multi-objective optimal scheduling model considering load transfer and multiple operational constraints are established.Secondly,considering the nonlinear discrete characteristics of the transferred load,taking into account the new energy generation capacity and the time-of-use electricity price in the system,a load transfer strategy under the influence of multiple factors is proposed to determine the load transfer in and out period in advance.Finally,combining the probability distribution model and charging and discharging strategies,the Monte Carlo method is used to simulate and analyze the charging and discharging loads of electric vehicles,laying the foundation for subsequent chapters.2.Aiming at the linear weighted processing method for solving multi-objective optimal scheduling in power grids,the Whale Optimization Algorithms exhibit defects such as being prone to falling into local optimizations when solving such high-dimensional nonlinear problems.An improved Whale Optimization Algorithm(IMWOA)incorporating multiple strategies is proposed to improve the uniformity of the initial population and improve the convergence speed through chaotic mapping and opposing learning mechanisms;Updating individual positions through nonlinear convergence factors and adaptive weighting strategies improves the optimization ability and convergence accuracy of the algorithm.Then,multiple tests were conducted on multiple unimodal and multimodal test functions to verify the effectiveness of the improved strategy.Finally,the IMWOA algorithm is used to solve the established multi-objective optimal scheduling model for microgrids.Compared to the Whale Optimization Algorithm(WOA)and the Grey Wolf Algorithm(GWO),the ability of IMWOA to solve multi-objective optimal scheduling problems for microgrids has been improved,further proving the effectiveness of the improved algorithm.3.Aiming at the shortcomings of linear weighting method in dealing with multiobjective optimization problems,Pareto optimal solution method is used to solve the multi-objective optimization problem of microgrid.Considering how to select the compromise optimal solution from the solution set,a dual positive distance decision making method(ECDPD-MCDM)considering equivalence is proposed.Firstly,based on the LINMAP decision method(called positive distance),the Euclidean distance(called negative distance)of the worst distance solution is introduced,and the negative distance is converted into positive distance,forming a dual positive distance index.Secondly,for a problem where multiple non inferior solutions with dual positive distance indicators may be equal and cannot be re determined,a quadratic decision strategy is proposed in the case of equivalence.Finally,in the multi-objective optimal scheduling problem of microgrid,the Pareto optimal solution set is applied to decision-making.Compared with the existing decision-making methods in the literature,the experimental results show that the proposed selection strategy can screen out reasonable compromise optimal solutions from the optimal solution set,and reflect a certain degree of bias.