A standstill parameter identification technique for the synchronous generator

This work presents an offline standstill identification technique, where the synchronous machine is locked at an arbitrary (but known) angle, and a test is conducted over a short period of time. In contrast to the well-known standard Standstill Frequency Response (SSFR) technique, which could take more than 6 hours to conduct, the method proposed here collects all the required data in few seconds. This technique is based on nonlinear least squares estimation and algebraic elimination theory. The resulting algorithm is non-iterative where the data is used to construct polynomials that are solved for a finite number of roots which determine the electrical parameter values. Experimental results are presented showing the efficacy of the technique in furnishing the parameters of a salient pole synchronous machine.

[1]  L.M. Tolbert,et al.  An on-line method for tracking the rotor time constant of an induction machine , 2005, Proceedings of the 2005, American Control Conference, 2005..

[2]  David A. Cox,et al.  Ideals, Varieties, and Algorithms: An Introduction to Computational Algebraic Geometry and Commutative Algebra, 3/e (Undergraduate Texts in Mathematics) , 2007 .

[3]  M. Velez-Reyes,et al.  Developing robust algorithms for speed and parameter estimation in induction machines , 2001, Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228).

[4]  S.D. Sudhoff,et al.  A synchronous machine model with saturation and arbitrary rotor network representation , 2005, IEEE Transactions on Energy Conversion.

[5]  Paul C. Krause,et al.  Analysis of electric machinery , 1987 .

[6]  Longya Xu,et al.  Maximum likelihood estimation of synchronous machine parameters from flux decay data , 1992, Conference Record of the 1992 IEEE Industry Applications Society Annual Meeting.

[7]  H. Guesbaoui,et al.  Synchronous machine parameter identification by a multi-time scale technique , 1992, Conference Record of the 1992 IEEE Industry Applications Society Annual Meeting.

[8]  S.D. Sudhoff,et al.  Experimental characterization procedure for a synchronous machine model with saturation and arbitrary rotor network representation , 2005, IEEE Transactions on Energy Conversion.

[9]  Leon M. Tolbert,et al.  Algebraic Methods for Nonlinear Systems: Parameter Identification and State Estimation , 2006 .

[10]  Joachim von zur Gathen,et al.  Modern Computer Algebra , 1998 .

[11]  L.M. Tolbert,et al.  An Online Rotor Time Constant Estimator for the Induction Machine , 2005, IEEE Transactions on Control Systems Technology.

[13]  Philippe Viarouge,et al.  Identification of generalised models of synchronous machines from time-domain tests , 1991 .

[14]  Ahmed Oteafy.  Novel Parameter Identification Techniques for Large Synchronous Generators , 2011 .

[15]  P. Kundur,et al.  Adaptation and Validation of Turbogenerator Model Parameters Through On-Line Frequency Response Measurements , 1981, IEEE Transactions on Power Apparatus and Systems.

[16]  A. W. W. Cameron,et al.  Simplified measurement of subtransient reactances in synchronous machines , 1952, Electrical Engineering.

[17]  Azah Mohamed,et al.  A Systematic Approach in Estimating the Generator Parameters , 2002 .

[18]  A. Keyhani,et al.  Iteratively reweighted least squares for maximum likelihood identification of synchronous machine parameters from on-line tests , 1999 .

[19]  L. N. Hannett,et al.  Test and simulation of network dynamic response using SSFR and RTDR derived synchronous machine models , 1990 .

[20]  Ed.C. Bortoni,et al.  A standstill frequency response method for large salient pole synchronous machines , 2004, IEEE Transactions on Energy Conversion.

[21]  Peter W. Sauer,et al.  Power System Dynamics and Stability , 1997 .

[22]  Ali Keyhani,et al.  Identification of synchronous machine linear parameters from standstill step voltage input data , 1995 .

[23]  John Chiasson,et al.  Estimation of the rotor time constant of an induction machine at constant speed , 2007, 2007 European Control Conference (ECC).

[24]  Miguel Velez-Reyes,et al.  Decomposed algorithms for parameter estimation , 1992 .

[25]  G. Verghese,et al.  Subset selection for improved parameter estimation in on-line identification of a synchronous generator , 1999 .

[26]  David A. Cox,et al.  Using Algebraic Geometry , 1998 .

[27]  F. P. de Mello,et al.  Determination of Synchronous Machine Electrical Characteristics by Test , 1983, IEEE Power Engineering Review.

[28]  Leon M. Tolbert,et al.  An online rotor time constant estimator for induction machine , 2007, IEEE International Conference on Electric Machines and Drives, 2005..

[29]  John Chiasson,et al.  Modeling and High Performance Control of Electric Machines , 2005 .

[30]  H. H. Happ,et al.  Power System Control and Stability , 1979, IEEE Transactions on Systems, Man, and Cybernetics.

[31]  Jay Apt,et al.  Electrical Blackouts: A Systemic Problem , 2004 .

[32]  Ali Keyhani,et al.  On-line synchronous machine parameter estimation from small disturbance operating data , 1995 .

[33]  Leon M. Tolbert,et al.  A nonlinear least-squares approach for identification of the induction motor parameters , 2005, IEEE Transactions on Automatic Control.

[34]  Arthur R. Bergen,et al.  Power Systems Analysis , 1986 .

[35]  M. A. Arjona,et al.  Parameter Estimation of a Synchronous-Generator Two-Axis Model Based on the Standstill Chirp Test , 2013, IEEE Transactions on Energy Conversion.

[36]  Ali Keyhani,et al.  Synchronous generator model identification and parameter estimation from operating data , 2003 .

[37]  G.C. Verghese,et al.  Recursive speed and parameter estimation for induction machines , 1989, Conference Record of the IEEE Industry Applications Society Annual Meeting,.

[38]  Scott D. Sudhoff,et al.  Analysis of Electric Machinery and Drive Systems , 1995 .

[39]  L.M. Tolbert,et al.  Tracking the rotor time constant of an induction motor traction drive for HEVs , 2004, Power Electronics in Transportation (IEEE Cat. No.04TH8756).