Optimal Selection and Location of FACTS Devices for Enhancement of Power Transfer Capability using Bee Algorithm

Abstract

Flexible Alternating Current Transmission System (FACTS) devices are solid state converters that have the capability of controlling various electrical parameters such as reactance, power angle and voltage in a power system. Optimal selection and location of FACTS devices play a vital role in improving the static and dynamic performance of the power system. However, finding the suitable location and selection of FACTS devices simultaneously is a complex and challenging task. There are several Artificial Intelligent (AI) approaches proposed concerning the location and selection of FACTS devices. A number of research works have been undertaken aimed at achieving optimal location and selection of FACTS devices based on different methods. Recent researches on multi-dimensional and non-linear engineering optimization problems are using a relatively new AI method known as Bee Algorithm (BA). Its performance, efficiency, precision, and speed of convergence in optimization has demonstrated its superiority compared to other AI methods. In this thesis, the Bee Algorithm was used to develop a model for optimizing FACTS devices location and selection. The sensitivity of the system loading capability, corresponding to the active and reactive power balance equations was used to determine optimal location and selection of FACTS devices. The effectiveness of the model was tested by simulating on the IEEE 9 and 30-bus test systems operated under normal and contingency conditions using MATLAB®. The resulting optimization model has shown improvement of the solutions of optimal location and selection of FACTS devices by increasing power transfer capability of power system network in comparison with other AI techniques.