ENHANCED CUCKOO SEARCH-BASED OPTIMIZATION FOR SINGLE DISTRIBUTED GENERATION PLACEMENT AND SIZING IN RADIAL DISTRIBUTION SYSTEMS

This paper presents an Enhanced Cuckoo Search Algorithm (ECSA) to optimally place and size Distributed Generation (DG) in radial distribution systems to minimize real power loss within operating constraints. The proposed ECSA has exponentially decaying adaptive Lévy flights, constraint-aware solution repair with dynamic penalty coefficients, and diversity-directed stochastic replacement to enhance search robustness and convergence speed. It was tested with 30 independent runs on the IEEE 33-bus, IEEE 69-bus, and a practical Nigerian 32-bus distribution network. The simulations show that the ECSA lowers the active power loss of the IEEE 33-bus system from 201.58 kW to 102.75 kW (49.03%), and the IEEE 69-bus system from 224.60 kW to 81.59 kW (61.67%), both statistically significant at p> 0.01. For the 32-bus network of Imalefalafia, losses were reduced from 95.07 kW to 14.78 kW (84.45%), and the minimum voltage was increased from 0.9524 p.u. to 0.9821 p.u. For all test systems, the proposed ECSA consistently outperformed fifteen benchmark metaheuristic algorithms in convergence speed, solution quality, and strength, making it useful for DG planning applications.