Optimum placement of active power conditioners by a dynamic discrete firefly algorithm to mitigate the negative power quality effects of renewable energy-based generators

This paper presents a novel solution for the optimal placement and sizing of active power conditioners in future smart distribution systems by using the dynamic discrete firefly algorithm. The proposed method aims to mitigate the power quality effects of hybrid renewable energy-based generators and electric vehicle stations in smart grids. A multi-objective optimization problem is formulated to improve the voltage profile, minimize the voltage total harmonic distortion, and reduce the total investment cost. The performance analysis of the proposed algorithm is conducted on a modified IEEE 16-bus test system by using Matlab software. The results are then compared with the conventional stationary firefly algorithm, hybrid improved genetic algorithm, and dynamic particle swarm optimization. The comparison proves that the proposed optimization algorithm is the most effective method among the other methods and that the proposed method can precisely determine the optimum location and size of active power conditioners in distribution systems.