A Genetic Algorithm for Solving Optimal Power Flow Problem

Abstract

Power flow study is the one which could provide solution for unknown electrical quantities of a larger interconnected system. There are different types of buses in a power system. Each bus has four electrical quantities, out of which two are specified and the remaining two are calculated by the power flow studies. The generation is scheduled for a minimal operating cost subjected to equality and inequality constraints. The equality constraint is such that the total power generated should equal the total demand and the system losses. The inequality constraint is related to line power flows and bus voltages to be within the limits for given schedule of generation. This is optimal power flow. Optimal Power Flow (OPF) aims to optimize a certain objective subjected to the equality and inequality constraints formed by the network Power flow equations and operating limits respectively. Minimization of generation cost by optimal scheduling of the generating stations and minimizing of losses is considered as the multiple objective function of interest. In this method the control variables are strategically varied using the binary coded Genetic Algorithm technique to satisfy both Equality & Inequality constraints. The standard IEEE 6 bus, 14 bus and 30 bus systems are considered for the analysis and an optimal power solution is achieved for a multiple objective function of minimizing both generation cost and system loss. The obtained results using Genetic Algorithm is are validated with the results using Particle Swarm Optimization (PSO) technique.