⛄ 内容介绍
综合能源系统具有提高能源利用率,消纳不稳定新能源等显著优势,随着分布式能源的发展,综合能源系统已成为解决能源问题的重要举措.基于粒子群算法配电网分布式能源选址定容问题，求解以网损、电压偏差、投资运行费用最小为目标。
⛄ 部分代码
function f = replace_chromosome(intermediate_chromosome, M, V,pop)
%% function f = replace_chromosome(intermediate_chromosome,pro,pop)
% This function replaces the chromosomes based on rank and crowding
% distance. Initially until the population size is reached each front is
% added one by one until addition of a complete front which results in
% exceeding the population size. At this point the chromosomes in that
% front is added subsequently to the population based on crowding distance.
% Copyright (c) 2009, Aravind Seshadri
% All rights reserved.
%
% Redistribution and use in source and binary forms, with or without
% modification, are permitted provided that the following conditions are
% met:
%
% * Redistributions of source code must retain the above copyright
% notice, this list of conditions and the following disclaimer.
% * Redistributions in binary form must reproduce the above copyright
% notice, this list of conditions and the following disclaimer in
% the documentation and/or other materials provided with the distribution
%
% THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS “AS IS”
% AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
% IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
% ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
% LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
% CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
% SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
% INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
% CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
% ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
% POSSIBILITY OF SUCH DAMAGE.
[N, m] = size(intermediate_chromosome);
% Get the index for the population sort based on the rank
[temp,index] = sort(intermediate_chromosome(:,M + V + 1));
clear temp m
% Now sort the individuals based on the index
for i = 1 : N
sorted_chromosome(i,:) = intermediate_chromosome(index(i),:);
end
% Find the maximum rank in the current population
max_rank = max(intermediate_chromosome(:,M + V + 1));
% Start adding each front based on rank and crowing distance until the
% whole population is filled.
previous_index = 0;
for i = 1 : max_rank
% Get the index for current rank i.e the last the last element in the
% sorted_chromosome with rank i.
current_index = max(find(sorted_chromosome(:,M + V + 1) == i));
% Check to see if the population is filled if all the individuals with
% rank i is added to the population.
if current_index > pop
% If so then find the number of individuals with in with current
% rank i.
remaining = pop – previous_index;
% Get information about the individuals in the current rank i.
temp_pop = …
sorted_chromosome(previous_index + 1 : current_index, :);
% Sort the individuals with rank i in the descending order based on
% the crowding distance.
[temp_sort,temp_sort_index] = …
sort(temp_pop(:, M + V + 2),’descend’);
% Start filling individuals into the population in descending order
% until the population is filled.
for j = 1 : remaining
f(previous_index + j,:) = temp_pop(temp_sort_index(j),:);
end
return;
elseif current_index < pop
% Add all the individuals with rank i into the population.
f(previous_index + 1 : current_index, 🙂 = …
sorted_chromosome(previous_index + 1 : current_index, :);
else
% Add all the individuals with rank i into the population.
f(previous_index + 1 : current_index, 🙂 = …
sorted_chromosome(previous_index + 1 : current_index, :);
return;
end
% Get the index for the last added individual.
previous_index = current_index;
end
⛄ 运行结果
