Parallel Hybrid Particle Swarm-Grey Wolf Algorithms for Optimal Load-Shedding in An Isolated Network

In distribution networks integrated with distributed generation (DG), disconnection from the main grid reduces the power supply significantly. The power imbalance between DG generation and load degrades network stability. This paper proposes a hybrid parallel Particle Swarm Optimization - Grey Wolf Optimizer (PSGWO) algorithm for load shedding optimization. This optimization aims to reduce the DG power not absorbed by the remaining loads and maintain the voltage within the specified limits. The performance of PSGWO is tested on an IEEE 33 bus radial distribution system, considering loading levels of 80% to 140% of the baseload. At a 100% loading level, PSGWO showed the best performance, with a load shedding of 2.2297 MW and a voltage deviation of 0.0049. These values are the smallest compared to the results of the standard PSO and GWO algorithms. The PSGWO algorithm remains superior and converges faster than standard PSO and GWO at all loading levels.