Puma optimizer technique for optimal planning of different types of distributed generation units in radial distribution network considering different load models

The increasing load demand has caused issues in distribution systems, such as higher line losses, lower power factors, and voltage fluctuations. Addressing these challenges is crucial for power utilities to ensure the reliability and efficiency of the system. This study explores the efficient allocation of multi-type distributed generations (DGs) in radial distribution systems using an optimization approach to reduce power losses, improve voltage profiles, and maximize the total annual savings of the system. The paper introduces a novel utilization of the Puma Optimizer (PO) technique to address the optimal DG placement problem, incorporating different load models such as constant power, constant current, constant impedance, and composite load models to create a comprehensive framework for DG planning. The efficacy of the adopted PO to allocate different types of DG units is evaluated on 85-bus, 141-bus, and 415-bus systems. Additionally, the results obtained from the PO algorithm are compared with other well-known optimization algorithms and existing research in the field. Simulation results indicate that combining DG units operating at a zero-power factor with those operating at an optimal power factor significantly enhances system performance compared to DG units operating solely at a zero-power factor, a unity power factor, or a unity power factor combined with a zero-power factor. Numerical results demonstrate significant performance improvements across all network sizes. Specifically, active power losses are reduced by 96.99%, 92.33%, and 79.48%, while reactive power losses are reduced by 97.80%, 91.89%, and 78.40% for the 85-bus, 141-bus, and 415-bus systems, respectively. Additionally, the findings indicate that the PO algorithm is more robust than other selected algorithms in determining the optimal size and placement of DG units.