stateestimation-self-derivatives-measurementdistribution/@SEOpti/fun.m

function [ Objective ] = fun(this, x )
%FUN Summary of this function goes here
%   Detailed explanation goes here
Objective=0;
SEVolt=x(1:this.Busnum);
SEVAngel=x(this.Busnum+1:2*this.Busnum);
Objective=sum(((SEVolt-this.mVolt)./this.sigma).^2);%<EFBFBD><EFBFBD>ѹ
%% ֧·<EFBFBD><EFBFBD><EFBFBD><EFBFBD>
cmpSEV=SEVolt.*exp(1j*SEVAngel); %<EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>ѹ
cmpSEBranchI=(cmpSEV(this.lineI)-cmpSEV(this.lineJ))./(this.lineR+1j*this.lineX);%<EFBFBD><EFBFBD><EFBFBD><EFBFBD>֧·<EFBFBD><EFBFBD><EFBFBD><EFBFBD>
SEBranchI=abs(cmpSEBranchI);% ֧·<EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>ֵ
% (SEBranchI-this.mBranchI).^2./(this.sigma^2)
Objective=Objective+sum((SEBranchI-this.mBranchI).^2./(this.sigma^2));%%<EFBFBD><EFBFBD><EFBFBD><EFBFBD>
%% <EFBFBD><EFBFBD>·<EFBFBD><EFBFBD><EFBFBD><EFBFBD>
SEBranchP=real((cmpSEV(this.lineI)-cmpSEV(this.lineJ)).*conj(cmpSEBranchI));
SEBranchQ=imag((cmpSEV(this.lineI)-cmpSEV(this.lineJ)).*conj(cmpSEBranchI));
% (SEBranchP-this.mBranchP).^2/(this.sigma^2)./(this.mBranchP.^2);
Objective=Objective+sum((SEBranchP-this.mBranchP).^2/(this.sigma^2));
Objective=Objective+sum((SEBranchQ-this.mBranchQ).^2/(this.sigma^2));
%% <EFBFBD><EFBFBD>ѹ<EFBFBD><EFBFBD>
newwordParameter=this.newwordParameter;
cmpY=this.cmpY;
transP=TransPower( newwordParameter,cmpY,SEVolt,SEVAngel );
Objective=Objective+sum((transP-this.mTransP).^2/(this.sigma^2));
transQ=TransReactivePower( newwordParameter,cmpY,SEVolt,SEVAngel );
Objective=Objective+sum((transQ-this.mTransQ).^2/(this.sigma^2));
%% 0ע<EFBFBD><EFBFBD><EFBFBD>ڵ<EFBFBD>
PQ=diag(cmpSEV)*conj(this.cmpY*cmpSEV);
%% <EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>ע<EFBFBD>빦<EFBFBD><EFBFBD>
% Objective=Objective+sum(((this.mPG(this.onlyPG)-real(PQ(this.onlyPG)))/this.sigma).^2);
% Objective=Objective+sum(((this.mQG(this.onlyQG)-imag(PQ(this.onlyQG)))./this.sigma).^2);
end