【配电网规划】配电网网架重构、DG位置选择容量配置（Matlab代码实现）

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📋📋📋本文目录如下：🎁🎁🎁

目录

💥1 概述

📚2 运行结果

🎉3 参考文献

🌈4 Matlab代码及数据

💥1 概述

在社会发展的新时期，我国的分布式光伏电源发展十分迅速，提供的电力在近些年的配电网销售电量中占比较大且呈现出逐年上升的趋势。文章分析了分布式光伏发电高渗透区域配电网规划研究的方法.配电网规划包括：配电网网架重构、DG位置选择容量配置。

📚2 运行结果

%% 基本参数

T=12; % 典型日 8-19h

% 8-19h 负荷各时段负荷总量
P_load=[828,1001,1105,1105,994,1105,1105,1049,1012,810,699,626];

% 8-19h 光伏各时段出力标幺(by)值
P_PVG=[0.29,0.03,0.51,0.55,0.47,0.46,0.55,0.64,0.22,0.20,0.38,0.03];

Node=23; % 节点
Line=34; % 线路

o1 = 1.1198; % 负荷功率因数角 0.9
o2 = 1.2532; % DG功率因素角 0.95

% 网损成本
Line_closs=0.6;

% 最大弃(abandon,a)光率
a_max_PVG=0.05;

% 单位弃光成本
PVG=0.6;

% 主网(zw)购电分时单价
zw_buy1_TR=[0.6 0.57 0.45 0.43 0.43 0.58 0.65 0.67 0.68 0.64 0.69 0.63 0.63 0.63 0.62 0.61 0.615 0.635 0.63 0.63 0.615 0.615 0.59 0.505 ];
zw_buy_TR=zw_buy1_TR(8:19);

SLmax=5300; % KVA
Umin=0.95*0.95*(12.66)^2; % 20KV
Umax=1.05*1.05*(12.66)^2; % 20KV

% P_TRmax=7500;
P_TRmax=4500;
P_TRmin=0;

M=99999; % 大M法处理非线性项

Model has 408 quadratic constraints
Variable types: 3636 continuous, 40 integer (40 binary)
Coefficient statistics:
Matrix range [3e-05, 2e+05]
QMatrix range [1e+00, 1e+00]
Objective range [4e-05, 7e-01]
Bounds range [1e+00, 1e+00]
RHS range [6e+00, 1e+05]
Presolve removed 6454 rows and 3475 columns
Presolve time: 0.08s
Presolved: 148 rows, 201 columns, 592 nonzeros
Presolved model has 34 quadratic constraint(s)
Variable types: 201 continuous, 0 integer (0 binary)
Root relaxation presolve time: 0.14s
Root relaxation presolved: 386 rows, 201 columns, 830 nonzeros
Root relaxation presolved model has 34 second-order cone constraints
Root barrier log...

Ordering time: 0.00s

Barrier statistics:
AA' NZ : 3.334e+03
Factor NZ : 5.145e+03
Factor Ops : 7.515e+04 (less than 1 second per iteration)
Threads : 1

Objective Residual
Iter Primal Dual Primal Dual Compl Time
0 -1.44100450e+05 -1.94306198e+06 6.22e+04 3.57e-01 2.38e+04 0s
1 -3.18003635e+04 -1.11128842e+06 1.93e+04 1.55e-04 3.38e+03 0s
2 -3.32510774e+03 -8.75211027e+04 2.63e+03 1.70e-10 2.59e+02 0s
3 1.60032580e+03 -1.28160838e+03 3.82e+02 4.46e-13 1.66e+01 0s
4 1.98895386e+03 1.30534203e+03 2.19e+02 5.13e-13 7.26e+00 0s
5 3.10026896e+03 2.35888313e+03 1.74e+00 1.70e-13 1.44e+00 0s
6 3.02078818e+03 2.76863576e+03 6.45e-01 7.23e-14 4.78e-01 0s
7 2.99412930e+03 2.92633212e+03 1.90e-01 2.33e-14 1.28e-01 0s
8 2.99001228e+03 2.96918960e+03 6.79e-02 6.44e-15 3.95e-02 0s
9 2.98881829e+03 2.97887602e+03 3.12e-02 2.84e-15 1.88e-02 0s
10 2.98808964e+03 2.98325309e+03 1.95e-08 1.23e-15 8.99e-03 0s
11 2.98733272e+03 2.98563455e+03 1.02e-09 4.50e-16 3.16e-03 0s
12 2.98712160e+03 2.98620869e+03 8.43e-11 2.65e-16 1.70e-03 0s
13 2.98706971e+03 2.98684841e+03 2.26e-11 9.85e-17 4.12e-04 0s
14 2.98705354e+03 2.98702514e+03 2.94e-11 9.16e-15 5.29e-05 0s
15 2.98704581e+03 2.98704303e+03 1.15e-10 5.27e-11 5.21e-06 0s
16 2.98704503e+03 2.98704469e+03 2.06e-10 9.10e-12 6.53e-07 0s
17 2.98704478e+03 2.98704477e+03 2.83e-09 1.61e-13 8.37e-09 0s

Barrier solved model in 17 iterations and 0.21 seconds (0.04 work units)
Optimal objective 2.98704478e+03

Root relaxation: objective 2.987045e+03, 0 iterations, 0.08 seconds (0.00 work units)

* 0 0 0 2987.0447775 2987.04478 0.00% - 0s

Explored 1 nodes (0 simplex iterations) in 0.24 seconds (0.04 work units)
Thread count was 16 (of 16 available processors)

Solution count 1: 2987.04

Optimal solution found (tolerance 1.00e-04)
Best objective 2.987044777456e+03, best bound 2.987044777456e+03, gap 0.0000%
时间已过 122.083744 秒。

数据：

部分代码：

% 光伏接入节点
PVG_jr=[4,8,11,12,16,20];

% 各光伏节点接入容量
int_pvg=[435,465,345,489,564,349];

Num_PVG=length(PVG_jr);

P_PVG_yc=sdpvar(Num_PVG,T,'full'); % 光伏预测（yc）出力
P_PVG=sdpvar(Num_PVG,T,'full');

x_pvg=binvar(1,Num_PVG); % 0-1变量，是否建设光伏

TR_jr=[1]; % 变压器接入节点也就是与主网相连节点

Num_TR=length(TR_jr);

P_TR=sdpvar(Num_TR,T,'full');
Q_TR=sdpvar(Num_TR,T,'full');

%% 负荷相关定义

% 各个节点基准(jz)负荷
P_load_jz=[0,188,180,136,184,160,172,164,244,252,180,204,248,160,196,144,172,188,223,145,135,268,193]/4136;

% 负荷曲线 0-24 求8:19
Load_timeine1=[0.78,0.75,0.7,0.68,0.65,0.63,0.7,0.75,0.79,0.90,0.90,0.90,0.90,0.9,0.9,0.9,0.9,0.9,0.9,0.9,0.85,0.83,0.80,0.78];
Load_timeine=Load_timeine1(8:19);

for t=1:T
for j=1:Node
P_LOAD(j,t)=total_P_LOAD(t)*P_load_jz(j)*Load_timeine(t);
end
end