Genetic algorithm, particle swam optimization and differential evolution algorithm for optimal hydro generation scheduling

Optimum scheduling of hydro plants generation is of great importance to electric utilities. Hydro generation scheduling is a nonlinear programming problem. The nonlinearity is due to the generating characteristic of hydro plant, whose outputs are generally a non linear function of water discharge and net hydraulic head. Evolutionary algorithms are popular due to their low convergence time and high accuracy. In this paper the comparison of Particle swam optimization (PSO), Differential Evolution (DE) algorithm and Genetic Algorithm (GA) are use to show the optimal generation scheduling of hydro generation. The comparisons of these methods are shown for four generating plants of hydro here.