Comparative studies between ant lion optimizer and evolutionary programming in optimal distributed generation placement

Abstract

Integration of Distributed Generation (DG) has become one of the popular research interests in power system. DG used small-scale technologies to generate electricity near to the consumer and the size is normally small, range from 50 MW to 100 MW. However, in order to integrate DG into the power system distribution, it is very crucial to consider several factors such as location, size and the number of DG to maintain its benefits. This paper proposes comparison of three techniques for optimal placement of DG in distribution system. The optimal placement was done using Evolutionary Programming (EP), Ant Lion Optimizer (ALO) and Loss Sensitivity Factor (LSF) to minimize the power losses in distribution system. These techniques were tested in three conditions; base case (without loading increment), 50% loading and 100% loading to observe the performance of the techniques in various phenomena. The test was conducted using IEEE 10-bus radial distribution system and the result shows that the integration of DG does minimize the power losses with ALO provides the most promising results.