Bacteria Foraging Algorithm based economic load dispatch with wind energy

This paper presents new optimization approach involving a modified Bacteria Foraging Algorithm (BFA) applied to economic load dispatch involving wind energy conversion systems (WECS). The approach utilizes the natural selection of global optimum bacterium having successful foraging strategies in the cost function including the factors of overestimation and underestimation of available wind energy. According to the stochastic nature of wind speed characteristics based on Weibull probability density function, the optimization problem is numerically solved for a scenario involving three conventional and two wind-powered generators. The simulation results provide optimal solutions of scheduling of generators under the risk of over estimation and underestimation of available wind power.