Evidence map›Paper›PMID 42009931›Full record

ArticleScientific reports2026

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

Mrinal Kanti Rajak, Ingudam Chitrasen Meitei, Rajen Pudur

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Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Mrinal Kanti RajakDepartment of Electrical Engineering, SVERI's College of Engineering Pandharpur, Gopalpur, Maharashtra, India. mrinal.phd20@nitap.ac.in.
Ingudam Chitrasen MeiteiDepartment of Electrical Engineering, SVERI's College of Engineering Pandharpur, Gopalpur, Maharashtra, India.
Rajen PudurDepartment of Electrical Engineering, National Institute of Technology Arunachal Pradesh, Itanagar, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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 ([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%.

Indexed as

Grey Wolf OptimizerGrid IntegrationHybrid OptimizationInduction GeneratorsInrush Current MitigationMicro-Hydro Power PlantsParallel OperationParticle Swarm Optimization

Identifiers

PMID42009931
PMCPMC13260900

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