Optimal capacitor value calculation for self excited induction generators using hybrid grey wolf differential evolution optimization with experimental validation
- 1Department of Electrical Engineering, SVERI’s College of Engineering
- 2Department of Electronics and Telecommunication Engineering, SVERI’s College of Engineering
- 3Department of Electrical Engineering, National Institute of Technology Arunachal Pradesh
Abstract
Self-excited induction generators (SEIGs) are extensively used in isolated micro-hydro and wind energy systems due to their rugged construction, low maintenance, and inherent short-circuit protection. However, the determination of optimal excitation capacitance remains a challenging nonlinear problem. The capacitor value directly governs voltage buildup, steady-state regulation, operating frequency, and power quality under varying speed and load conditions. This paper proposes a hybrid Grey Wolf Optimizer–Differential Evolution (GWO-DE) algorithm for optimal capacitor value calculation in three-phase SEIGs. The capacitor selection is formulated as a constrained single-objective optimization problem. Three design criteria (voltage-regulation quality, operating-speed range, and capacitor cost) are combined a priori through a fixed weighted-sum scalarization, based on the steady-state per-phase equivalent circuit incorporating core losses and a fifth-order polynomial magnetizing characteristic. An adaptive switching parameter transitions the search from GWO-dominant exploration to DE-dominant exploitation, while an elite archive and stagnation-triggered reinitialization prevent premature convergence. The proposed GWO-DE is benchmarked against PSO, standard GWO, GA, and Nelder-Mead across 24 operating conditions spanning six speed levels and four load levels. All reported optimization metrics are obtained from 30 independent runs. Results demonstrate that GWO-DE achieves 3.07× better mean fitness than PSO, 15.18× better than standard GWO, and 22.92× better than GA, with 38.7% faster convergence than PSO. The optimized capacitor maintains terminal voltage within ±5% of rated value up to 85% load, with voltage THD compliant with IEEE 519 limits. Experimental validation on a 3.7 kW laboratory SEIG prototype using a Fluke 435-II power quality analyzer confirms the predictions with an average error of 2.32%. A capacitor value contour map across the speed-load space is provided as a practical design tool for field installations.
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BibTeX
@article{jadhav2026optimal,
title = {{Optimal capacitor value calculation for self excited induction generators using hybrid grey wolf differential evolution optimization with experimental validation}},
author = {Sanket Prakash Jadhav and Mrinal Kanti Rajak and Meenakshi Mukund Pawar and Rajen Pudur},
journal = {Scientific Reports},
year = {2026},
month = jul,
doi = {10.1038/s41598-026-62604-1},
url = {https://doi.org/10.1038/s41598-026-62604-1},
note = {CC BY},
}
RIS
TY - JOUR
TI - Optimal capacitor value calculation for self excited induction generators using hybrid grey wolf differential evolution optimization with experimental validation
AU - Sanket Prakash Jadhav
AU - Mrinal Kanti Rajak
AU - Meenakshi Mukund Pawar
AU - Rajen Pudur
PY - 2026
DA - 2026/07/01
JO - Scientific Reports
DO - 10.1038/s41598-026-62604-1
UR - https://doi.org/10.1038/s41598-026-62604-1
AB - Self-excited induction generators (SEIGs) are extensively used in isolated micro-hydro and wind energy systems due to their rugged construction, low maintenance, and inherent short-circuit protection. However, the determination of optimal excitation capacitance remains a challenging nonlinear problem. The capacitor value directly governs voltage buildup, steady-state regulation, operating frequency, and power quality under varying speed and load conditions. This paper proposes a hybrid Grey Wolf Optimizer–Differential Evolution (GWO-DE) algorithm for optimal capacitor value calculation in three-phase SEIGs. The capacitor selection is formulated as a constrained single-objective optimization problem. Three design criteria (voltage-regulation quality, operating-speed range, and capacitor cost) are combined a priori through a fixed weighted-sum scalarization, based on the steady-state per-phase equivalent circuit incorporating core losses and a fifth-order polynomial magnetizing characteristic. An adaptive switching parameter transitions the search from GWO-dominant exploration to DE-dominant exploitation, while an elite archive and stagnation-triggered reinitialization prevent premature convergence. The proposed GWO-DE is benchmarked against PSO, standard GWO, GA, and Nelder-Mead across 24 operating conditions spanning six speed levels and four load levels. All reported optimization metrics are obtained from 30 independent runs. Results demonstrate that GWO-DE achieves 3.07× better mean fitness than PSO, 15.18× better than standard GWO, and 22.92× better than GA, with 38.7% faster convergence than PSO. The optimized capacitor maintains terminal voltage within ±5% of rated value up to 85% load, with voltage THD compliant with IEEE 519 limits. Experimental validation on a 3.7 kW laboratory SEIG prototype using a Fluke 435-II power quality analyzer confirms the predictions with an average error of 2.32%. A capacitor value contour map across the speed-load space is provided as a practical design tool for field installations.
SN - 2045-2322
ER -