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Research Article |

Intelligent Capacitor Selection and Analysis for Self-Excited Reluctance Generator under Variable Conditions

Author(s): Rewan M. Abo Elwafa1*, M. Elwany2,A. B. Kotb3

Published In : International Journal of Electrical and Electronics Research (IJEER)        Volume 14, Issue 2

Publisher : FOREX Publication

Published : 25 June 2026

e-ISSN : 2347-470X

Page(s) : 446-457

DOI: https://doi.org/10.37391/IJEER.140221

Abstract

This manuscript provides an analysis of a wind-driven self-excited reluctance generator (WDSERG) performance running under variable load conditions while maintaining a regular output voltage, and designs an Artificial Neural Network (ANN) model to forecast the value of the excitation capacitance required to maintain a WDSERG's generated voltage within desired bounds. The self-excited reluctance generator (SERG) has advantages over the induction generator (IG), which include steady frequency regardless of load or capacitance variation with proper performance. The analysis of steady-state for the reluctance generator (RG) is conducted according to d-q axes transformation. The suitable capacitance is determined for varying operating conditions to meet the main requirements for a loaded RG at constant voltage. To provide guidelines for designers, the variations of the capacitance corresponding to any change in the load impedance, power factor and prime mover speed are determined. The predicted excitation capacitance values that required to keep the generated voltage at a preferred constant level of 1± 0.1 pu under inputs condition. For example, at conditions (ZL (load impedance) =3pu (per unit), PF (power factor) =1, and constant speed) the capacitance 16.5275 µF (micro farad) make voltage constant at 1pu. It investigates how changing machine parameters affects the generator's performance and presents the speed above which excitation is not possible. Simulation results are supported through MATLAB coding analysis. This paper demonstrates the feasibility of steady voltage operation under in a variable load for SERG, presenting insights for practical implementation in standalone wind energy systems.

Keywords: Self-excited reluctance generator, Variable wind speed, Excitation Capacitance, Variable load, Artificial Neural Network, Evaluation metrics.




Rewan M. Abo Elwafa, Electrical Power and Machines Dept., Institute of Aviation Engineering and Technology, Egyptian Aviation Academy, Ministry of Civil Aviation, Imbaba Airport, Giza, Egypt; Email: rewanmohamad63@gmail.com

M. Elwany, Department of Elect. Eng. Faculty of Eng. Al-Azhar University, Cairo, Egypt; Email: MahmoudHosain1712.el@azhar.edu.eg

A. B. Kotb, Department of Elect. Eng. Faculty of Eng. Al-Azhar University, Cairo, Egypt; Email: moabdelsamie45@yahoo.com

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Rewan M. Abo Elwafa, M. Elwany, and A. B. Kotb (2026), Intelligent Capacitor Selection and Analysis for Self-Excited Reluctance Generator under Variable Conditions. IJEER 14(2), 446-457. DOI: 10.37391/IJEER.140221.