Power Economic Dispatch with Valve-Point Loading Effects and Multiple Fuels Using Chaotic Based Differential Evolution

Abstract

The power economic dispatch (PED) problem is one of the fundamental issues in power system. In essence, it is an optimization problem and its main objective is to reduce the total generation cost of units, while satisfying constraints. The work done in this thesis presents differential evolution (DE) and an improved differential evolution (IDE) with self-adaptive parameters setting for DE with chaos theory. Among various evolutionary algorithms (EAs), DE which characterized by the different mutation operator and competition strategy from the other EAs, has shown great promise in many numerical benchmark problems and real-world optimization applications. The potentialities of DE are its simple structure, easy use, convergence speed and robustness. To improve the global optimization property of DE, its parameters CR and m f that needs to be adjusted by the user are generally the key factors affecting the DE’s convergence. The utilization of chaotic sequences in DE can be useful to escape more easily from local minima than with the standard DE and improve its global convergence. . In this thesis work, differential evolution and improved differential evolution techniques are used to solve power economic dispatch (PED) problem of all thermal units with valve point loading effects and multiple fuels for no loss transmission line as well considering transmission loss.