Hybrid Particle Swarm Optimization-Genetic Algorithm based Optimal dispatch of Wind and Thermal System

Abstract

This paper discusses a hybrid Particle Swarm Optimization-Genetic Algorithm for optimal dispatch of wind-thermal generation system. In the power system when wind power penetration increases, its impact need to be investigated on conventional thermal unit as wind power is intermittent and unpredictable. Particle Swarm Optimization and Genetic Algorithm are used to coordinate the wind and thermal power system to find the minimum production cost including the valve effect of thermal units. The effectiveness of the proposed approach is validated using three IEEE test systems consisting of 6, 13 and 40 units and a NTPS utility system consisting of 7 generating units with two wind farms of 100MW and 150MW respectively. Simulation results show that the inclusion of wind power generation reduces the total fuel cost.