Scheduling of Hydrothermal and Renewable Energy Systems Using Enhanced PSO Technique

Abstract

The economics of emerging power systems heavily depend on the subject of hydrothermal scheduling. The purpose of this article is to suggest soft computing-based enhanced particle swarm optimization techniques for dealing with short-term hydrothermal scheduling problem. The article uses a test system made up of a multi-stream cascaded system with hydro, thermal plants and wind farms, to find the best solution while taking economic and environmental considerations into account. The mathematical models applied to solve the water outflow, generating cost, and harmful emissions from the above-mentioned power plants included in the IEEE-30 Bus system. Statistics have been used to gauge the dependability and consistency of the suggested algorithm. In order to find the optimal generating schedule for conventional scheduling issue, a solution technique called robust heuristic search algorithm has been used. The developed heuristic methodology has outperformed conventional and soft computing methodology.