Information Gap Decision Theory based Multiobjective OPF for a Power System with Wind Energy Resources

Abstract

Optimal power flow (OPF) problem has been one of the most important issues in power system operation for many years. The OPF solution is generally sought by optimizing a selected objective, such as the generation cost, subject to security or reliability constraints of the power system. Nowadays, the aim of achieving a desired optimality is not an easy task because of many uncertainties due to various factors or components, notably the generation by means of wind turbines. In this paper, our focus is to present a multi-objective optimal power flow study to be performed for a power system that is considerably dependent on power generation through wind farms. A new risk-based method, information gap decision theory (IGDT), is used to tackle the problem of uncertainties in power generation introduced by the wind turbines. The objectives in the formulated optimization problem are the minimization of the fuel cost, the minimization of the voltage deviations from nominal values and optimizing the reactive power generation. The weighted sum approach is used to solve this problem using a single equivalent objective function.