A Hybrid Genetic Algorithm Approach for Optimal Power Flow
Abstract: This paper puts
forward a reformed hybrid genetic algorithm (GA) based approach to the optimal
power flow. In the approach followed here, continuous variables are designed
using real-coded GA and discrete variables are processed as binary strings. The
outcomes are compared with many other methods like simple genetic algorithm
(GA), adaptive genetic algorithm (AGA), differential evolution (DE), particle
swarm optimization (PSO) and music based harmony search (MBHS) on a IEEE30 bus
test bed, with a total load of 283.4 MW. It’s found that the proposed algorithm
is found to offer lowest fuel cost. The proposed method is found to be
computationally faster, robust, superior and promising form its convergence
characteristics.
Author: Mithun M. Bhaskar M.
Bhaskar, Sydulu Maheswarapu
Journal Code: jptkomputergg110028
