Applications of differential evolution in power system optimization

Abstract

Modern power systems are very large, complex and widely distributed. Scarcity in energy resources, increasing power generation cost and ever-growing demand for electric energy necessitates optimal operation of power systems. Even a small reduction in production cost may lead to a large savings. Hence efficient algorithms for solving the power system scheduling are needed. New optimization methods based on evolutionary computation that abstract the principle of natural selection and genetics are employed for scheduling problems. They are easy to implement and have the capability to converge to global optimum at a relatively lesser computational effort. Differential Evolution (DE), a numerical optimization approach is simple, easy to implement, significantly faster and robust. It has been verified as a promising candidate for solving real-valued engineering optimization problems. This chapter is concerned with the applications of differential evolution and its variants for various power system scheduling problems like economic dispatch, dynamic economic dispatch and unit commitment. Different case studies have been conducted including nonlinearities such as the valve-point effects, prohibited operating zones and transmission losses. This chapter enumerates the advantages of differential evolution to determine the most economic conditions of the electric power system. © 2008 Springer-Verlag Berlin Heidelberg.