Dynamic Hunting Leadership Algorithm for Optimal Allocation of Unified Power Quality Conditioner in Distribution Systems

This paper presents the application of Dynamic Hunting Leadership Algorithm (DHLA) algorithm to the optimal allocation of Unified Power Quality Conditioners (UPQCs) in electrical distribution systems, with the aim of minimizing operating costs, power losses, and voltage instability. DHLA is a novel metaheuristic optimization method inspired by the hunting behavior of social predators. The algorithm dynamically balances exploration and exploitation, enabling efficient convergence to optimal solutions. Simulation studies of the proposed DHLA-based UPQC allocation were carried out on the IEEE 33-bus and Nigerian Dada 46-bus distribution networks. The cost-benefit analysis of the simulation results shows that placement and sizing of three UPQCs with DHLA is the optimal scenario in both networks. From the observed results, DHLA is highly efficient in terms of convergence speed, optimization accuracy, cost efficiency, and power quality enhancement, demonstrating its effectiveness and robustness for complex distribution system optimization tasks.