Induction motor-based dynamic modeling of a load bus using extended Kalman filter parameter estimation

Date

2023-12-11

Author

Karahan, Mehmet

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Induction -or asynchronous- motors are significant AC electric machines frequently used in industry owing to their high reliability, torque capacity, low cost, and low inertia. Because of their widespread usage, representing load buses as aggregated induction motors rather than conventional static loads yields more accurate results in dynamic studies. Therefore, the accuracies of both the induction load model and the parameters constituting the model are essential for the precise determination of the behavior of the load. This study employs MATLAB/Simulink to simulate the dynamic state-space model derived for an induction motor. The extended Kalman filter is utilized to estimate the parameters of an induction motor using voltage and current data observed supposedly by a PMU located at a particular load bus. Estimating numerous parameters can lead to convergence problems; the proposed method analyses parameter sensitivities to reduce their quantity. Collinearity analysis enhances estimation convergence to this study's actual values for sensitive parameters. The proposed method developed a fulfilling parameter estimation of an induction motor through simulations with different scenarios implemented on the IEEE-9 Bus System in the PSS/E environment. The method proposed in this study enables the modeling of single-induction motor and multi-induction motor load buses as a single equivalent motor. Nevertheless, the restricted number of observations currently limits the practical applicability of this method in the industrial domain, as it yields results only under specific circumstances.

Subject Keywords

Induction Motor Modeling, Extended Kalman Filter, MATLAB/Simulink, PSS/E, IEEE 9 Bus System

URI

https://hdl.handle.net/11511/107746

Collections

Graduate School of Natural and Applied Sciences, Thesis