Optimal Distribution Substations Placement using Genetic Algorithm: SP_instcost(substation) - File Exchange

No BSD License

Highlights from
Optimal Distribution Substations Placement using Genetic Algorithm

DSP(varargin)
FValue=SP_tlosscost1(InValue) this function return the transformer's (input argument) loss
FValue=SP_tlosscost1(InValue) this function return the transformer's (input argument) loss
SP_2kva(InVal) this function convert the input to a correspounding kVA.
SP_create(NVARS,FitnessFcn,op... this function creates the first population used by Genetic Algorithm
SP_crossover(parents,options,... this function is dedicated for crossover operation used by MATLAB ga
SP_fitness(x,FinalTLDistances... here, the fitness function is created. the sum of distances from loads to
SP_instcost(substation) this function dedicates the primary installation cost
SP_main() this program is designed for optimal substation placement
SP_mutation(parents ,options,... this function is dedicated for crossover operation used by MATLAB ga
SP_stepup(CurVal,X_Cord,Y_Cor... this function step-up the transformers size until it can feed the total
DSP_help.m
SP_initialize.m
View all files

from Optimal Distribution Substations Placement using Genetic Algorithm by Amir Pouya Khansaryan
Finds the optimal location and capacity of distribution substations

SP_instcost(substation)

% this function dedicates the primary installation cost
% for any distribution substation in $
function subscost = SP_instcost(substation)

global KWTransformersTypes InstallCosts
Tag = find(KWTransformersTypes == substation);
subscost = InstallCosts(1,Tag);
d=0;

Highlights from Optimal Distribution Substations Placement using Genetic Algorithm

Highlights from
Optimal Distribution Substations Placement using Genetic Algorithm