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Digital Object Identifier (DOI) : 10.14569/IJACSA.2010.010511
Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 1 Issue 5, 2010.
Abstract: A substantial amount of power system load is made of large number of three phase induction machine. The transient phenomena of these machines play an important role in the behavior of the overall system. Thus, modeling of induction machine is an integral part of some power system transient studies. The analysis takes a detailed form only when its modeling becomes perfect to a greater accuracy. When the stator eddy current path is taken into account, the uniform air-gap theory in phase model analysis becomes inefficient to take care of the transients. This drawback necessitates the introduction of analysis of the machine in d-q axis frame. A widely accepted induction machine model for stability studies is the fifth-order model which considers the electrical transients in both rotor and stator windings and the mechanical transients. In practice, some flux-transient can be ignored due to the quasi-stationary nature of the variables concerned. This philosophy leads to the formation of reduced order model. Model Order Reduction (MOR) encompasses a set of techniques whose goal is to generate reduced order models with lower complexity while ensuring that the I/O response and other characteristics of the original model (such as passivity) are maintained. This paper takes the above matter as a main point of research. The authors use the philosophy of the speed-build up of induction machine to find the speed versus time profile for various load conditions and supply voltage disturbances using numerical methods due to Runge- Kutta, Trapezoidal and Euler’s in Matlab platform. The established fact of lesser computation time in reduced order model has been verified and improvement in accuracy is observed.
Sudhir kumar, P. K. Ghosh and S. Mukherjee, “Generalized Two Axes Modeling, Order Reduction and Numerical Analysis of Squirrel Cage Induction Machine for Stability Studies ” International Journal of Advanced Computer Science and Applications(IJACSA), 1(5), 2010. http://dx.doi.org/10.14569/IJACSA.2010.010511