Optimal Power Flow Using Refined Genetic Algorithm

This article presents a simple, effective, and reliable refined genetic algorithm (RGA) for solving the optimal power flow (OPF) problem. This genetic algorithm with the exponential variation of crossover probability, mutation probability, anddynamic hierarchy of the coding system has the ability to code a large number of control variables in a practical system, within a reasonable length of chromosome, and the algorithm is less sensitive to starting points. It is, therefore, able to regulate the active power outputs of generators, bus voltages, shunt capacitors/reactors, and transformer tap-settings to minimize the fuel cost. The feasibility of the algorithm is demonstrated using the IEEE 6-bus and 30-bus systems.