基于双层优化的电动汽车优化调度研究MATLAB程序
参考文献：
《考虑大规模电动汽车接入电网的双层优化调度策略_胡文平》中文版
《Abi-layer optimization based temporal and spatial scheduling for large-scaleelectric vehicles》完全复现
仿真平台：MATLAB+CPLEX平台
主要内容：
主要做的是一个双层的电动汽车充放电行为优化问题，具体来讲，输电网上层优化将电动汽车与发电机、基本负荷协调，同时考虑风力发电，从而在时域内优化电动汽车的负荷周期。然后，配电网的下层优化在空间上调度电动汽车负荷的位置。同时代码考虑了风电的出力场景，研究了不同风电出力下电动汽车的适应性，该代码具有一定的创新性，适合新手学习以及在此基础上进行拓展，代码质量非常高，保姆级的注释以及人性化的模块子程序，所有数据均有可靠来源，下单后会直接发您资料，保证您学得会，用的起来，简直是萌新福利！
部分程序：
Ji=10;%机组数量;
Time=24;%时间尺度;
SS=20;%场景数量;
Pmax=[455,455,130,130,162,80,85,55,55,55];%机组最大出力;
Pmin=[150,150,20,20,25,20,25,10,10,10];%机组最小出力;
a=[1000,970,700,680,450,370,480,660,665,670];
b=[16.19,17.26,16.60,16.50,19.7,22.26,27.74,25.92,27.27,27.79];
c=[0.00048,0.00031,0.002,0.0021,0.00398,0.00712,0.00079,0.00413,0.00222,0.00173];
Ton=[8,8,5,5,6,3,3,1,1,1];%最小开机时间;
Toff=[8,8,5,5,6,3,3,1,1,1];%最小停机时间;
Tcs=[5,5,4,4,4,2,2,0,0,0];%冷启动时间;
Sh=[4500,5000,550,560,900,170,260,30,30,30];%热启动费用;
Sc=[9000,10000,1100,1120,1800,340,520,60,60,60];%冷启动费用;
T=[8,8,-5,-5,-6,-3,-3,-1,-1,-1];%初始运行状态;
Xbefore=zeros(8,10);
for t=1:8
for j=1:10
if T(j)+t<=0
Xbefore(t,j)=0;
else
Xbefore(t,j)=1;
end
end
end
Xf=Xbefore(1,:);%初始序列;
Xbefore=[zeros(1,10);Xbefore];
PL=[700,750,850,950,1000,1100,1150,1200,1300,1400,1450,1500,1400,1300,1200,1050,1000,1100,1200,1400,1300,1100,900,800];%日负荷;
delta_hot=[130,130,60,60,90,40,40,40,40,40];%爬坡速率
delta_cold=[150,150,20,20,25,20,25,10,10,10];%开停机爬坡速率
R=0.1*PL;%备用容量，这里取10%PL;
aa=[100,105,82,49,72,29,32,40,25,15];%污染物排放;
bb=[1.1285,1.1954,1.2130,1.2643,1.5354,1.8015,1.6966,1.8518,1.9101,2.2034];
cc=[0.00135,0.00127,0.00148,0.00289,0.00261,0.00212,0.00382,0.00393,0.00396,0.00510];
Ce=3000;%污染物成本;
Cw=100;%弃风成本;
w=[0.067,0.031,0.037,0.054,0.067,0.052,0.040,0.038,0.035,0.086,0.059,0.039,0.044,0.066,0.032,0.053,0.049,0.055,0.057,0.039];%场景概率;
Pd=1.8*10/1000;%放电功率;
Pc=1.8*10/1000;%充电功率;
Ndmax=15000*0.4*ones(24,20);%每时段最大接入放电电动汽车数量;150000辆电动车;
Ncmax=15000*0.95*ones(24,20);%每时段最大接入充电电动汽车数量;150000辆电动车;
%Ndmax=10000*0.4*ones(24,20);%每时段最大接入放电电动汽车数量;100000辆电动车;
%Ncmax=10000*0.95*ones(24,20);%每时段最大接入充电电动汽车数量;100000辆电动车;
%Ndmax=5000*0.4*ones(24,20);%每时段最大接入放电电动汽车数量;50000辆电动车;
%Ncmax=5000*0.95*ones(24,20);%每时段最大接入充电电动汽车数量;50000辆电动车;
%Ndmax=zeros(24,20);%输电网中不含电动汽车
%Ncmax=zeros(24,20);%输电网中不含电动汽车
Ndsummax=15000*3*ones(1,20);%全天电动汽车放电需求;150000辆电动车;
Ncsummax=15000*6*ones(1,20);%全天电动汽车充电需求;150000辆电动车;
%Ndsummax=10000*3*ones(1,20);%全天电动汽车放电需求;100000辆电动车;
%Ncsummax=10000*6*ones(1,20);%全天电动汽车充电需求;100000辆电动车;
%Ndsummax=5000*3*ones(1,20);%全天电动汽车放电需求;50000辆电动车;
%Ncsummax=5000*6*ones(1,20);%全天电动汽车充电需求;50000辆电动车;
%Ndsummax=zeros(1,20);%输电网中不含电动汽车
%Ncsummax=zeros(1,20);%输电网中不含电动汽车
输出结果：
