Authors: Amr Khaled Khamees, N. M. Badra, Almoataz Y. Abdelaziz
Power flow study (load-flow study) is a steady-state analysis whose target is to determine the voltages, currents, and real and reactive power flows in a system under a given load conditions. The objective of an Optimal Power Flow (OPF) study is to find steady state operation point which minimizes generation cost, loss, emission etc. Over the past half-century, OPF has become one of the most important and widely studied nonlinear optimization problems 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. Therefore, OPF has become complex. In recent years, Artificial Intelligence (AI) methods have been emerged which can solve highly complex OPF problems. The purpose of this paper is to present a comprehensive survey of various optimization methods like traditional and AI methods used to solve OPF problems.
Artificial Intelligence, Optimal Power Flow
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