Integrated particle swarm optimization variants for economic load dispatch problem

Abstract

According to no free lunch theorem, a single search technique cannot perform best under different conditions. The integration of principally similar search techniques is one of the option, that has been explored to effectively investigate the search area. In order to avoid stagnation at local minima and to enhance the search capability of particle swarm optimization, this paper proposes a technique that integrates predator prey optimization and anti-predatory particle swarm optimization. The integrated algorithm utilizes the capability of particle swarm optimization to find high quality solution, the capability of anti predatory particle swarm optimization to avoid search in worst solution regions and capability of predator prey optimization to escape from local minima under the effect of predator. The proposed algorithm has been implemented to solve economic dispatch problem. The different practical constraints such as ramp rate limits, prohibited operating zone(s) along with power balance constraint and generator limit are undertaken. The multiple fuel system is considered with transmission losses. The proposed algorithm is tested on various models of ED problems and compared with results reported in literature and found satisfactory.