- Title
- Estimation of induction motor parameters using hybrid algorithms for power system dynamic studies
- Creator
- Susanto, Julius; Islam, Syed
- Date
- 2013
- Type
- Text; Conference proceedings; Conference paper
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/167263
- Identifier
- vital:13657
- Identifier
-
https://doi.org/10.1109/AUPEC.2013.6725462
- Identifier
- ISBN:978-186295913-2
- Abstract
- This paper proposes a hybrid Newton-Raphson and genetic algorithm for the estimation of double cage induction motor parameters from commonly available manufacturer data. The hybrid algorithm was tested on a large data set of 6,380 IEC and NEMA motors and then compared with a baseline Newton-Raphson algorithm. The simulation results show that while the proposed hybrid algorithm is more computationally intensive, it does make significant improvements to convergence and error rates.
- Publisher
- University of Tasmania
- Relation
- 2013 Australasian Universities Power Engineering Conference, AUPEC 2013; Hobart, Australia; 29th September-3rd October 2013 p. 1-6
- Rights
- Copyright © 2013 Australasian Committee for Power Engineering (ACPE).
- Rights
- Open Access
- Rights
- This metadata is freely available under a CCO license
- Subject
- Hybrid algorithm; Parameter estimation; Induction motor
- Full Text
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