Title :
Online Synchronous Machine Parameter Extraction From Small-Signal Injection Techniques
Author :
Huang, Jing ; Corzine, Keith A. ; Belkhayat, Mohamed
Author_Institution :
Dept. of Electr. & Comput. Eng., Missouri Univ. of Sci. & Technol., Rolla, MO
fDate :
3/1/2009 12:00:00 AM
Abstract :
This paper proposes using a novel line-to-line voltage perturbation as a technique for online measurement of synchronous machine parameters. The perturbation is created by a chopper circuit connected between two phases of the machine. Using this method, it is possible to obtain the full set of four complex small-signal impedances of the synchronous machine d-q model over a wide frequency range. Typically, two chopper switching frequencies are needed to obtain one data point. However, it is shown herein that, due to the symmetry of the machine equations, only one chopper switching frequency is needed to obtain the information. A 3.7-kW machine system is simulated, and then constructed for validation of the impedance measurement technique. A genetic algorithm is then used to obtain IEEE standard model parameters from the d -q impedances. The resulting parameters are shown to be similar to those obtained by a series of tests involving synchronous reactance measurements and a standstill frequency response.
Keywords :
choppers (circuits); genetic algorithms; machine control; parameter estimation; synchronous machines; IEEE standard model parameters; chopper circuit; genetic algorithm; impedance measurement; line-to-line voltage perturbation; online measurement; online synchronous machine parameter extraction; small-signal injection techniques; standstill frequency response; synchronous machine d-q model; synchronous reactance measurements; Generator; genetic algorithm (GA); impedance; motor; online measurement; parameter; synchronous machine;
Journal_Title :
Energy Conversion, IEEE Transactions on
DOI :
10.1109/TEC.2008.2008953