matlab-(含教程)基于遗传优化的微电网调度优化matlab仿真

clc; clear; close all; warning off; addpath(genpath(pwd)); pop=100; % population m_rate = .1; % mutation rate c_pt = 2; % crossover point good_enough = .08; % when to stop weights = [1, .6, .4]; % chromosome format ------------------------------------------------------- power = 1; cost = 2; emission = 3; source_1 = [20, .02, .01]; source_2 = [120, .20, .05]; source_3 = [15, .01, .02]; source_4 = [50, .02, .04]; sources = [source_1; source_2; source_3; source_4]; % define ranges [num_sources, num_genes] = size(sources); boundaries = zeros(num_genes, 2); boundaries(1,:) = [15, 100]; % requested power range boundaries(2,:) = [.15, 6.55]; % minimum cost to get max power boundaries(3,:) = [.15, 3.75]; % minimum emissions to get max power r = 2; s = 2; reproduction = @crossover; survival = @elitism; load = TimeSeries(); chromosomes = chromosome_gen(pop, sources); vector = zeros(24, num_sources); % initialze vector for best chromosomes econ = zeros(24, 1); % initialize vector for econonmic factor enviro = zeros(24, 1); % intialize vector for environmental factor time = zeros(24, 1); % vector to store time for i = 1:length(load) tic; % get fitness vector fit = fitness(chromosomes, sources, boundaries, weights, load(i)); [best, best_i] = min(fit); % loop until a suitable chromosome is found while(~stop_condition(fit, good_enough)) % reproduce with selected method chromosomes = reproduction(chromosomes, pop, sources, boundaries, m_rate, c_pt); fit = fitness(chromosomes, sources, boundaries, weights, load(i)); % kill with selected method chromosomes = survival(pop, chromosomes, fit); % check fitness of modified set fit = fitness(chromosomes, sources, boundaries, weights, load(i)); [best,best_i]=min(fit); % get rid of NaN if(isnan(best)) best = 1; end end % store elapsed time elapsed = toc; time(i) = elapsed; % store chromosome in vector vector = store_best(vector, fit, chromosomes, i); % store economic factor econ(i) = econ_fitness(chromosomes(best_i, :), sources, boundaries, weights); % store environmental factor enviro(i) = enviro_fitness(chromosomes(best_i, :), sources, boundaries, weights); end % plot information enviro_plot(enviro); econ_plot(econ); power_plot(vector,load); calculation_plot(time);