Hybrid PSO-GWO optimization for converter-free grid integration of parallel induction generators with experimental validation in micro-hydro power plants

Abstract

Abstract 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 ( $$p < 10^{-5}$$ 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 $$-1.8\%$$ to $$-1.0\%$$ 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%.