智能微电网中利用粒子群算法实现微电网多目标优化.rar

clear all; clc; format short; tic XDCRL=10; %蓄电池容量 pgridmax=7;%交互功率 m=100; %种群规模数 dd=500; %迭代次数 c1=1; c2=1; vmax=1; vmin=-1; wmax=0.9; wmin=0.4; d=25;%24时刻蓄电池SOC0 CFX =[];%惩罚项 cfx = 0;%惩罚项 PV=load('Ppv2.txt');%光伏发电量 % Pev=zeros(1,24); Pev=load('PEV.txt');%电动汽车 LOAD= load('Load2.txt');%负荷 sub=load('C_sub2.txt'); buy=load('C_buy2.txt'); sell=load('C_sell2.txt'); xdccl=zeros(m,24);%蓄电池出力 v=zeros(m,d);%初始化速度 SOC=rand(m,d);%蓄电池的SOC grid=zeros(m,24);%微网 GRID=zeros(1,24); fx=zeros(1,m); %%初始化粒子更新 for n=1:m; %每一次更新粒子群（100个粒子）都有判断是否满足条件 for i=2:d %保证蓄电池的SOC大于0.3,小于0.95 if SOC(n,i)<0.3 SOC(n,i)=0.3; end if SOC(n,i)>0.95 SOC(n,i)=0.95; end SOC(n,1)=0.4;%蓄电池的SOC不变，都为0.4 SOC(n,25)=0.4;%蓄电池的SOC不变，都为0.4 end %储能系统的功率约束 for i=1:24 %蓄电池 j =SOC(n,i)-SOC(n,i+1); if j > 0.3 j = 0.3;%放电 SOC(n,i+1)= SOC(n,i) - j; elseif j <= -0.3; j = -0.3;%充电 SOC(n,i+1)= SOC(n,i) - j; end xdccl(n,i) =j*XDCRL;%蓄电池出力 end %确定大电网出力 for i = 1:24 grid(n,i)=LOAD(i)+Pev(i) - PV(i)- xdccl(n,i); if grid(n,i)>pgridmax %买电 grid(n,i)=pgridmax; end if grid(n,i)<-pgridmax %卖电 grid(n,i)=-pgridmax; % grid(n,i)=LOAD(i)+Pev(i) - PV(i)- xdccl(n,i); end end cfx = (SOC(n,1)-SOC(n,25))*1000000; CFX=[CFX;cfx]; end %初始粒子群的更新结束 %需要带入函数计算运行成本的单元：大电网出力，蓄电池出力 for i=1:m fx(i)=fitnessEcoVir(CFX(i,:),grid(i,:),xdccl(i,:),sub,PV,buy,sell); end [fgbest, best_x]=min(fx);%fitgbest全局最佳适应度值 gbest=SOC(best_x,:);%全局最优位置 pbest=SOC;%个体最优位置的初始值，粒子的初始位置 fpbest=fx;%个体最佳适应度值 for t=1:dd for f=1:m %m=100 %量子粒子更新 alpha=(-0.8*(t-1))/(dd-1)+1.2; mbest=sum(pbest)/m; fi1=rand(1,d); fi2=rand(1,d); p=(2*fi2.*pbest(f,:)+2.1*fi1.*gbest)./(2*fi2+2.1*fi1); u=rand(1,d); b=alpha*abs(mbest-SOC(f,:)); v=-log(u); SOC(f,:)=p+((-1).^ceil(0.5+rand(1,d))).*b.*v; % %普通粒子更新 % v(f,:) =v(f,:)+c1*rand*(pbest(f,:)-SOC(f,:))+c2*rand*(gbest-SOC(f,:));%%SOC速度更新 % SOC(f,:)=SOC(f,:)+v(f,:);%%SOC位置更新 % if(v(f,:)>vmax) % v(f,:)=vmax; % elseif(v(f,:)<vmin) % v(f,:)=vmin; % end for h=2:d if SOC(f,h)<0.3 SOC(f,h)=0.3; end if SOC(f,h)>0.95 SOC(f,h)=0.95; end SOC(f,1)=0.4; end for i=1:24 j =SOC(f,i)-SOC(f,i+1); if j > 0.3 j = 0.3; SOC(f,i+1)= SOC(f,i) - j; elseif j<-0.3 j=-0.3; SOC(f,i+1)= SOC(f,i) - j; end xdccl(f,i) =j*XDCRL; %蓄电池出力 end for i=1:24 grid(f,i)=LOAD(i)+Pev(i) - PV(i)- xdccl(f,i); if grid(f,:)>pgridmax %买电 grid(f,:)=pgridmax; elseif grid(f,:)<-pgridmax %卖电 grid(f,:)=-pgridmax; end end CFX= (SOC(f,1)-SOC(f,25))*1000000; %%%%%%%%%SOC约束 fx(f)=fitnessEcoVir(CFX,grid(f,:),xdccl(f,:),sub,PV,buy,sell);%适应度更新 %个体最优 if fx(f)<fpbest(f) pbest(f,:)=SOC(f,:); fpbest(f)=fx(f); end %群体最优 if fx(f)<fgbest gbest=SOC(f,:); fgbest=fx(f); GRID=grid(f,:); end end MINIMUM(t)=fgbest; end db=gbest; for j=1:24 xdc(j)=(gbest(j)-gbest(j+1))*XDCRL; end % for j=1:24 % GRID(j)=LOAD(j)+Pev(i) - PV(j)- xdc(j); % end GRID % 电网 xdc %蓄电池 a=sum(xdc) fitgbest=min(MINIMUM) plot(MINIMUM) % figure % l=1:24; % plot(l,GRID,'o-',l,xdc,'*-',l,PV,'--') % legend('大电网出力','蓄电池出力','光伏出力') % xlabel('小时/h') % ylabel('功率/kW') % % set(gca,'xtick',0:2:24) % hold off SOC=db(1:25) figure(2) ll=0:24; plot(ll,SOC,'o-') xlabel('小时/h') ylabel('SOC') xlim([0 24]) title('蓄电池SOC') set(gca,'xtick',0:2:24) %将数据导入到excel表格中 % xlswrite('C:\Users\Administrator\Desktop\出力',GRID',1,'A1') % xlswrite('C:\Users\Administrator\Desktop\出力',PV',1,'B1') % xlswrite('C:\Users\Administrator\Desktop\出力',xdc',1,'C1') % xlswrite('C:\Users\Administrator\Desktop\出力',LOAD',1,'D1') % xlswrite('C:\Users\Administrator\Desktop\出力',Pev',1,'E1') toc