## PSO solution to economic dispatch

Version 1.0.0.0 (49.4 KB) by
This program solves the economic dispatch problem by PSO toolbox developed by Brian birge.Two exampl

Updated Wed, 06 Aug 2008 13:19:10 +0000

This software contains two examples psotest.m and psotest.1.By running the programs
(psotest.m or psotest1.m) as they are in the default pso1 folder the economic dispatch problem
can be solved. The allocation minimum fuel cost and transmission losses are determined.
3. I am using the PSOt, particle swarm optimization toolbox for matlab developed by Prof Brian
Birge(Reference).My sincere thanks to him for the efficient toolbox.
% 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
%no of rows denote the no of plants(n)
clear
clc;
format long;
global data B B0 B00
data=[0.008 7 200 10 85
0.009 6.3 180 10 80
0.007 6.8 140 10 70];
B=.01*[.0218 .0093 .0028;.0093 .0228 .0017;.0028 .0017 .0179];
B0=0*[.0003 .0031 .0015];
Pd=150;
l=data(:,4)';
u=data(:,5)';
ran=[l' u'];
n=length(data(:,1));
Pdef = [100 100000 100 2 2 0.9 0.4 1500 1e-6 5000 NaN 0 0];
[OUT]=pso_Trelea_vectorized('f6',n,1,ran,0,Pdef);
out=abs(OUT)
P=out(1:n)
[F Pl]=f6(P')
The results
P =
32.88968876120133
64.59837992682773
54.85448624558800
F = 1.597481635286200e+003
Pl = 2.34255491258807
This solution is better than the solution given in the book
P=[33.4701 64.0974 55.1011];
F=1599.98
Reference:
Birge, B., 2003, PSOt, A Particle Swarm Optimization Toolbox for Matlab,
IEEE Swarm Intelligence Symposium Proceedings, April 24-26
ALL THE BEST

### Cite As

RMS Danaraj (2023). PSO solution to economic dispatch (https://www.mathworks.com/matlabcentral/fileexchange/20984-pso-solution-to-economic-dispatch), MATLAB Central File Exchange. Retrieved .

##### MATLAB Release Compatibility
Created with R14SP1
Compatible with any release
##### Platform Compatibility
Windows macOS Linux
##### Acknowledgements

Inspired by: Particle Swarm Optimization Toolbox

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#### pso1/

Version Published Release Notes
1.0.0.0