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该程序是完全复现《Switch Opening and Exchange Method for Stochastic Distribution Network Reconfiguration》#xff0c;也是一个开源代码#xff0c;网上有些人卖的还挺贵#xff0c;本次免费分享给大家#xff0c;代码主要做的是一个通过配电网重构获取…1 主要内容
该程序是完全复现《Switch Opening and Exchange Method for Stochastic Distribution Network Reconfiguration》也是一个开源代码网上有些人卖的还挺贵本次免费分享给大家代码主要做的是一个通过配电网重构获取最优网络拓扑的问题从而有效降低网损提高经济效益同时考虑了光伏和负荷的随机性构建了多时段随机配电网重构模型考虑到大型网络中计算较为耗时采用一种基于开断和交换的SOE方法已获得良好的径向拓扑采用IEEE多个标准算例进行了测试更加创新而且求解的效果更好结果和论文基本是一致代码质量非常高但是子程序比较多适合有编程经验的同学学习 2 部分程序
% core programme in decrese_reconfig_33.m already obtain optimal solution, no need to execute tabu
clear all, clc, close all
addpath(./code)
%% basic setting
tic
fprintf(decrease_reconfig_33_tabu.m \n)
warning(off)
addpath(pathdef)
mpopt mpoption;
mpopt.out.all 0; % do not print anything
mpopt.verbose 0;
version_LODF 0 % 1: use decrease_reconfig_algo_LODF.m% 0: use decrease_reconfig_algo.m
candi_brch_bus []; % candidate branch i added to bus j
% mpc0 case33;
casei4
d33zhu_v2
substation_node 1; n_bus 33;
n1 3
n2 5
n1_down_substation n11; n2_up_ending n2;
Branch0 Branch;
brch_idx_in_loop0 unique(brch_idx_in_loop(:));
%% original networks power flow (not radial)
% show_biograph(Branch, Bus)
from_to show_biograph_not_sorted(Branch, substation_node, 0);
mpc generate_mpc(Bus, Branch, n_bus);
res_orig runpf(mpc, mpopt);
losses get_losses(res_orig.baseMVA, res_orig.bus, res_orig.branch);
loss0 sum(real(losses));
fprintf(case33_tabu: original loop networks loss is %.5f \n\n, loss0)
% for each branch in a loop,
% if open that branch does not cause isolation, check the two ending buses
% of that branch for connectivity, realized by shortestpath or conncomp
% calculate the lowest loss increase, print out the sorted loss increase
% open the branch with lowest loss increase
% stop criterion: number of buses - number of branches 1
%% ------------------------ Core algorithm ------------------------%%
ff0 Branch(:, 1); ff ff0;
tt0 Branch(:, 2); tt tt0;
t1 toc;
if version_LODF[Branch] decrease_reconfig_algo_LODF(Bus, Branch, brch_idx_in_loop, ...ff0, tt0, substation_node, n_bus, loss0); %%% core algorithm
else[Branch] decrease_reconfig_algo(Bus, Branch, brch_idx_in_loop, ff0, tt0, ...substation_node, n_bus, loss0); %%% core algorithm
end
t2 toc;
time_consumption.core t2 - t1
% output of core algorithm
show_biograph 0;
from_to show_biograph_not_sorted(Branch(:, [1 2]), substation_node, ...0);
from_to0 from_to;
mpc generate_mpc(Bus, Branch, n_bus);
res_pf_dec runpf(mpc, mpopt);
losses get_losses(res_pf_dec.baseMVA, res_pf_dec.bus, res_pf_dec.branch);
loss0_dec sum(real(losses)); %
fprintf(case33_tabu: radial network obtained by my core algorithms loss is %.5f \n\n, loss0_dec)
Branch_loss_record [];
% record Branch and loss
Branch_loss_record.core.Branch Branch;
Branch_loss_record.core.loss loss0_dec;
%% prepare force open branches for tabu: branch_idx_focused
[branch_idx_focused] get_branch_idx_focused_for_tabu( ...from_to, Branch0, Branch, substation_node, brch_idx_in_loop0, n_bus, ...n1_down_substation, n2_up_ending);
%% ------------------------ Tabu algorithm ------------------------%%
% run the core program for each upstream branch connected to the idx_force_open
% idx_considered [35 69]
% for iter idx_considered
for iter 1:length(branch_idx_focused)fprintf(iter%d/%d\n, iter, length(branch_idx_focused));Branch Branch0;Branch(branch_idx_focused(iter), :) [];ff0 Branch(:, 1); ff ff0;tt0 Branch(:, 2); tt tt0;brch_idx_in_loop brch_idx_in_loop0;idx_tmp find(brch_idx_in_loop branch_idx_focused(iter));if isempty(idx_tmp)elsebrch_idx_in_loop(idx_tmp) [];brch_idx_in_loop(idx_tmp:end) brch_idx_in_loop(idx_tmp:end)-1;end
t1 toc;%%------------------- core algorithm in Tabu loop--------------------%% if version_LODF[Branch] decrease_reconfig_algo_LODF(Bus, Branch, brch_idx_in_loop, ...ff0, tt0, substation_node, n_bus, loss0); %%% core algorithmelse[Branch] decrease_reconfig_algo(Bus, Branch, brch_idx_in_loop, ff0, tt0, ...substation_node, n_bus, loss0); %%% core algorithmendt2 toc; time_consumption.tabu(iter) t2-t1;
from_to show_biograph_not_sorted(Branch(:, [1 2]), substation_node, ...show_biograph); %%% show figure, take timempc generate_mpc(Bus, Branch, n_bus);t1 toc;res_pf runpf(mpc, mpopt);t2 toc; losses get_losses(res_pf.baseMVA, res_pf.bus, res_pf.branch);lossi sum(real(losses)) % loss 0.5364loss_tabu(iter,1) lossi;yij_dec generate_yij_from_Branch(Branch, Branch0);
% record Branch and lossBranch_loss_record.tabu(iter,1).Branch Branch; Branch_loss_record.tabu(iter,1).loss lossi;[PQ, PV, REF, NONE, BUS_I, BUS_TYPE, PD, QD, GS, BS, BUS_AREA, VM, ...VA, BASE_KV, ZONE, VMAX, VMIN, LAM_P, LAM_Q, MU_VMAX, MU_VMIN] idx_bus;
% Vm res_pf.bus(:, VM);
% Va res_pf.bus(:, VA);
% ending_bus find_ending_node(Branch, substation_node);
% [ending_bus; Vm(ending_bus)]; %% ---------------------one open and one close---------------------%% % prepare nodes_focused for one_open_one_closet1 toc;[nodes_focused] get_nodes_focused_o1c1( ...from_to, Branch, Branch0, substation_node, brch_idx_in_loop, ...n1_down_substation, n2_up_ending);
loss_before_switch0 lossi;[record_o1c1_loss_dec, loss_after_switch_combine_two_o1c1, Branch_loss] ...one_open_one_close(nodes_focused, Bus, Branch0, Branch, from_to, ...substation_node, n_bus, loss_before_switch0);t2 toc;time_consumption.tabu_o1c1(iter) t2-t1;
% record Branch and lossBranch_loss_record.tabu_o1c1_dec{iter}.Branch Branch_loss.Branch_o1c1_dec;
% Branch_loss_record.tabu_o1c1_dec(iter,1).Branch Branch_loss.Branch_o1c1_dec; Branch_loss_record.tabu_o1c1_dec{iter}.loss Branch_loss.loss_o1c1_dec; Branch_loss_record.tabu_combine_2_o1c1_dec{iter}.Branch ...Branch_loss.Branch_after_switch_combine_two_o1c1; Branch_loss_record.tabu_combine_2_o1c1_dec{iter}.loss ...Branch_loss.loss_after_switch_combine_two_o1c1;
min_loss_o1c1 min(record_o1c1_loss_dec(:,1));fprintf(case33_tabu: minimum loss obtained after one open and one close: %.5f\n, ...min_loss_o1c1);
min_loss_combine_two_o1c1 1e9;fprintf(case33_tabu: loss obtained after combine two one open and one close: \n)for i 1:length(loss_after_switch_combine_two_o1c1)temp min(loss_after_switch_combine_two_o1c1{i});if temp %.5f \n, temp);end fprintf(case33_tabu: minimum loss obtained after combine two one open and one close: %.5f \n, ...min_loss_combine_two_o1c1) %% ---------------------two open and two close---------------------%%flag_2o2c 0if flag_2o2c 1t1 toc;loss_before_switch0 lossi;[record_o2c2_loss_dec, loss_after_switch_combine_two_o2c2] ...two_open_two_close(nodes_focused, Bus, Branch0, Branch, from_to, ...substation_node, n_bus, loss_before_switch0);t2 toc;time_consumption.tabu_o2c2(iter) t2-t1;min_loss_o2c2 min(record_o2c2_loss_dec(:,1));fprintf(case33_tabu: minimum loss obtained after two open and two close: %.5f\n, ...min_loss_o2c2);
min_loss_combine_two_o2c2 1e9;fprintf(case33_tabu: loss obtained after combine two two open and two close: \n)for i 1:length(loss_after_switch_combine_two_o2c2)temp min(loss_after_switch_combine_two_o2c2{i});if temp %.5f \n, temp);endfprintf(case33_tabu: minimum loss obtained after combine two two open and two close: %.5f \n, ...min_loss_combine_two_o2c2) res_save{iter}.min_loss_o2c2 min_loss_o2c2;res_save{iter}.min_loss_combine_two_o2c2 min_loss_combine_two_o2c2;end
res_save{iter}.yij_dec yij_dec;res_save{iter}.Branch Branch;res_save{iter}.lossi lossi; res_save{iter}.record_o1c1_loss_dec record_o1c1_loss_dec;res_save{iter}.min_loss_o1c1 min_loss_o1c1;res_save{iter}.min_loss_combine_two_o1c1 min_loss_combine_two_o1c1;% file_name [case33_yij_Branch_, num2str(idx_force_open(iter)), .mat];
% save(file_name, yij_dec, Branch, lossi);file_name [id1_case33_yij_Branch, .mat];save(file_name, res_save, branch_idx_focused, Branch_loss_record, ...time_consumption); end
file_name [id1_case33_yij_Branch, .mat];
save(file_name, res_save, branch_idx_focused, Branch_loss_record, ...time_consumption);
% find_all_losses(Branch_loss_record);
fprintf(case33_tabu: losses obtained after applying tabu strategy: \n) % 0.28343 zjp 2018-1-18
fprintf(%.5f \n, loss_tabu)
fprintf(----- min: %.5f -----\n, min(loss_tabu))
min_loss 1e9;
for i 1:length(res_save)if min_lossres_save{i}.min_loss_o1c1 min_loss res_save{i}.min_loss_o1c1 ;endif min_lossres_save{i}.min_loss_combine_two_o1c1 min_loss res_save{i}.min_loss_combine_two_o1c1 ;end
end
min_loss_o1c1 min_loss
if flag_2o2c 1min_loss 1e9;for i 1:length(res_save)if min_lossres_save{i}.min_loss_o2c2 min_loss res_save{i}.min_loss_o2c2 ;endif min_lossres_save{i}.min_loss_combine_two_o2c2 min_loss res_save{i}.min_loss_combine_two_o2c2 ;endend min_loss_o2c2 min_loss
end
3 部分模型级文献结果 4 下载链接
