Indian Journal of Science and Technology

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Background/Objectives: This paper aims to evaluate performance characteristics of standalone Self-Excited Induction Generator (SEIG) under varying load condition. Methods/Statistical Analysis: Prime mover speed, excitation capacitance and load significantly influence the performance of SEIG. Due to nonlinear magnetization, estimation of nonlinear magnetic characteristics involves clumsy mathematical computation. It gives an opportunity to model nonlinear magnetization characteristics suitable to obtain minimum impedance and optimal capacitance for improved performance. Findings: The effect of regression on nonlinear magnetization curve has been discussed while estimation of magnetization reactance by employing regression functions. It provides optimal value of magnetization reactance to compute performance variables of SEIG. Solution techniques are applied to calculate frequency and excitation capacitance and compared their results. Regression functions with solution techniques have been applied on comprehensive data of induction machines to exhibit validity and accuracy of proposed scheme. Applications/Improvements: The proposed techniques reveal lower capacitance requirement as compared to existing piece- wise linearization model.

Keywords

Comprehensive Analysis, Nonlinear Constraint Optimization, Optimal Performance Parameters, Stand-Alone Generator
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