This paper presents a particle swarm optimization (PSO)‎ based algorithm for optimal power

Abstract EN

This paper presents a Particle Swarm Optimization (PSO) based algorithm for Optimal Power Flow (OPF) in Combined Economic Emission Dispatch (CEED) environment of thermal units while satisfying the constraints such as generator capacity limits, power balance and line flow limits.

Particle Swarm Optimization is a population based stochastic optimization, developed by Kennedy and Eberhart [12], in which members within a group share the information among them to achieve the global best position.

This method is dynamic in nature and it overcomes the shortcomings of other evolutionary computation techniques such as premature convergence and provides high quality solutions.

The performance of the proposed method has been demonstrated on IEEE 30 bus system with six generating units.

The problem has been formulated as a single optimization problem to obtain the solution for optimal power flow problem with combined fuel cost and environment impact as objectives.

The results obtained by the proposed method are better than any other evolutionary computation techniques proposed so far.