Multi-Objective Analysis for Optimal location and location of Distributed Generation Focused on Improving Power Quality

Abstract

The increasing demand for electric power and heightened environmental protection awareness have rapidly grown distributed generation (DG) in recent years. Consequently, this research aims to investigate the optimal location and capacity for DG based on multiple objectives, such as the minimization of active power losses, the improvement of the voltage profile, and the cost reduction of the network. To this end, an algorithm inspired by the behavior of lion ants, known as the Ant Lion Optimizer (ALO), has been proposed as a possible solution. The ALO algorithm is a nature-inspired meta-heuristic that can provide near-optimal solutions for complex real-world optimization problems. Thus, the ALO algorithm is expected to provide solutions close to optimal while being computationally efficient.