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Abstract

The objective of an Optimal Power Flow (OPF) algorithm is to find steady state operating point which minimizes generation cost loss etc. or maximizes social welfare, load ability etc. while maintaining an acceptable system performance in terms of limits on generators’ real and reactive powers, line flow limits, output of various compensating devices etc. Traditionally, classical optimization methods were used to effectively solve OPF. But more recently due to incorporation of FACTS devices and deregulation of a power sector, the traditional concepts and practices of power systems are superimposed by an economic market management. So OPF have become complex. In recent years, Artificial Intelligence (AI) methods have emerged which can solve highly complex OPF problems. The purpose of this paper is to present a study of some optimization techniques used to solve OPF problems and a technique for optimal sizing and implementation of the SVC in optimal power flow. A 26-bus system has been studied to show the effectiveness of the algorithm.