A new methodology for optimal penetration of multiple type distributed generators based on large-scale unbalanced power distribution network

Abstract

Optimal integration of distributed generators (DGs) into unbalanced power distribution networks (PDNs) is critical for minimizing power losses and enhancing voltage stability. So, this study applies the novel walrus optimizer (WO) to determine the optimal placement, sizing, and power factors of DGs in unbalanced PDNs using the IEEE 123-bus system as realistic unbalanced network representative of real-world operating conditions. The unbalanced distribution IEEE 123-bus system is simulated in OpenDSS while the WO approach is implemented in Matlab and linked to OpenDSS for co-simulation. The primary goal is to reduce the network’s total active power loss while constraints of voltage and current restrictions, voltage control tap position limitations, DG generated power limits, and generation-demand power balance restrictions are examined. The proposed WO is rigorously benchmarked against established metaheuristics including skill optimization algorithm (SOA), giant trevally optimizer (GTO), osprey optimization algorithm (OOA), and equilibrium optimizer (EO). The fetched results demonstrate the WO’s superior efficacy as it succeeded in mitigating the network power loss by 70.48%, 83.47%, and 84.72% with installing Type I (active), Type II (reactive), and Type III (combined active and reactive) DGs, respectively. The corresponding voltage deviations are reduced by 18.44%, 16.41%, and 32.15%. These improvements significantly surpass those achieved by comparative algorithms highlighting the WO’s robustness in avoiding local optima and achieving faster convergence. The study concludes that, the WO effectively addresses the nonlinear complexities of PDNs, offering reliable tool for utilities to optimize DG integration. Its ability to concurrently optimize location, capacity, and power factors ensures tangible gains in grid efficiency and stability.