Hybrid PSO-GWO optimization for converter-free grid integration of parallel induction generators with experimental...

This paper presents a hybrid Particle Swarm Optimization-Grey Wolf Optimizer (PSO-GWO) approach for optimal slip coordination and power management of converter-free grid-connected parallel induction generators (2.2 kW and 5.5 kW) in micro-hydro power plants. The methodology addresses multi-objective optimization of slip values for maximum power extraction, inrush current mitigation through intelligent synchronization, and power flow coordination without power electronic converters. The hybrid PSO-GWO achieves superior convergence compared to standalone PSO (18.3% faster), GWO (12.7% faster), and five recent hybrid methods (AGWOPSO, HFPSO, FFA, HCHOPSO, PSO-AHA), attaining 96.4% global optimum detection rate across 500 Monte Carlo simulations confirmed by the Wilcoxon rank-sum test ([Formula: see text] for all comparisons). Experimental validation demonstrates 68.8% inrush current reduction (45.2 A to 14.1 A), 126% active power improvement through optimal slip matching (2328 W to 5262 W), and 74-79% cost reduction ($960 versus $3,650-$4,650). The optimization identifies the Pareto-optimal slip range of [Formula: see text] to [Formula: see text] with power factor between 0.85 and 0.92. A comprehensive distribution network model incorporating transformer and feeder impedances validates voltage regulation within ±4.2% at the point of common coupling, with uncertainty analysis confirming predictions within instrument accuracy. Robustness evaluation under four fault conditions (LL, LG, LLG, LLL) confirms stable recovery satisfying IEEE Standard 1547-2018 fault ride-through requirements. The proposed approach offers a computationally efficient and economically viable solution for rural electrification with total harmonic distortion below 4.2%.