Particle Swarm Optimization as a general design tool in power engineering

Particle swarm optimization (PSO) is a relative new evolutionary computation technique. The algorithm is theoretically simple, and computationally efficient. In the past decade, PSO has been widely applied to different problems. In this paper, we present our work on the application of PSO to four problems related to power systems, machine, and power electronics. The four problems are power system islanding, tuning of conventional power system stabilizers, parameter identification of permanent magnet synchronous motor, and tuning the of a harmonic detection algorithm. For each of the above problems, background, algorithm design, and some simulations are provided. PSO applications to the above four problem are all implemented offline. To achieve better performance, our recent work on the real time implementation of PSO to PMSM parameter identification is introduced.