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Highlights from
Improved PSO program to solve Economic Dispatch

from Improved PSO program to solve Economic Dispatch by Saloman Danaraj
This program solves the economic dispatch problem by improved PSO algorithm

psotest.m
% the data matrix should have 5 columns of fuel cost coefficients and plant  limits.
% 1.a ($/MW^2) 2. b $/MW 3. c ($) 4.lower lomit(MW) 5.Upper limit(MW)
% This Example system is taken from the book Power System Analysis  by Prof Haadi Sadaat Example 7.8
%no of rows denote the no of plants(n)
clear
clc;
format long;
global data B  Pd
data=[0.15247	38.53973	756.79886	10	125
0.10587	46.15916	451.32513	10	150
0.02803	40.3965	1049.9977	35	225
0.03546	38.30553	1243.5311	35	210
0.02111	36.32782	1658.569	130	325
0.01799	38.27041	1356.6592	125	315];
B=1e-4*[1.4 .17 .15 .19 .26 .22;.17 .60 .13 .16 .15 .20;.15 .13 .65 .17 .24 .19;.19 .16 .17 .71 .30 .25;.26 .15 .24 .30 .69 .32;.22 .20 .19 .25 .32 .85];
Pd=700;
 l=data(:,4)';
u=data(:,5)';
ran=[l' u'];
n=length(data(:,1));
Pdef = [50 1000 10 2 2 0.9 0.4 1500 1e-6 5000 NaN 0 0];
 [OUT]=pso_Trelea_vectorized('psoeld',n,1,ran,0,Pdef);
 out=abs(OUT)
 P=out(1:n)
  [F P Pl]=psoeld(P')
  % comparision by quadratic programming
  [P1 Fcost1 Pl1]=eld(data,B,Pd)

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