ABSTRACT
The application of soft computing techniques for solving optimal power flow (OPF) problem is increasing tremendously and has proved to be an optimistic approach when compared with classical optimization method. The major techniques of soft computing are evolutionary computing, artificial neural networks, fuzzy logic, and Bayesian statistics. Particle swarm optimization (PSO) is an evolutionary optimization technique inspired from swarm behavior such as bird flocking and very much familiar in solving various complex problems. As OPF is considered to be complex, the PSO algorithm is the reliable optimization algorithm and the obtained simulation results for Standard IEEE 30 bus system show reduction in generating cost and losses. The effectiveness of PSO approach is compared with other alternatives available in the literature.
