Identification and sensitivity analysis of synchronous machine d-axis parameters

• Autorzy: Niewierowicz, T. , Escarela-Perez, R. , Campero-Littlewood, E.
• Języki publikacji: EN

Abstrakty

EN

A sensitivity analysis is performed to study the characteristics of the parameters of two-axis equivalent circuits (used in the modelling of solid rotor synchronous machines). The equivalent circuit parameters are determined by using a hybrid genetic algorithm, which also gives the right number of circuit damper branches that must be used to accurately reproduce the standstill frequency response of the synchronous machine. The sensitivity analysis clearly shows the relative importance of each parameter within the fitness Junction used in the identification process. Hence, it is observed that care must be taken in the identification process since the fitness function has very low sensitivity to some parameters. The results show that a sensitivity analysis of the circuit parameters could lead to a better understanding of the accepted two-axis equivalent circuits.

Słowa kluczowe

PL

obwód zastępczy; modelowanie numeryczne; wirnik całokuty

EN

equivalent circuit; numerical modelling; solid rotor

• Czasopismo: Journal of Applied Computer Science
• Rocznik: 2002
• Tom: Vol. 10, nr 1
• Strony: 91-103
• Opis fizyczny: Bibliogr. 7 poz.

Twórcy

autor

Niewierowicz, T.

• Instituto Politecnico National, ESIME-SEPI, U.P. Adolfo Lopez Mateos, Edif. z-4, col. Lindavista, C.P. 07738 Mexico, D.F., Mexico,

autor

Escarela-Perez, R.

• Universidad Autonoma Metropolitana, Av. San Pablo No. 180, C.P. 02200, Mexico, D.F., Mexico,

autor

Campero-Littlewood, E.

• Universidad Autonoma Metropolitana, Av. San Pablo No. 180, C.P. 02200, Mexico, D.F., Mexico

Bibliografia

• [1] Canay I.M.: Modelling of Alternating-Current Machines Having Multiple Rotor Circuits, IEEE Trans, on Energy Conversion, 1993, 8, 2, pp.280-296.
• [2] Escarela-Perez R., Niewierowicz T.: Campero-Littlewood E., Synchronous Machine Parameters from Frequency-Response Finite-Element Simulations and Genetic Algorithms, IEEE Trans, on Energy Conversion, 2001,16, 2, pp.198-203.
• [3] Goldberg D.E.: Genetic Algorithms In Search, Optimization And Machine Learning, Adison-Wesley, 1989.
• [4] IEEE Guide: Test Procedures for synchronous machines, IEEE Std. p. 115, 1995.
• [5] Kamwa I., Viarouge P., Le-Huy J., Dickinson J.: A frequency domain maximum likelihood estimation of synchronous machine high-order models using SSFR test data, IEEE Trans, on Energy Conversion, 1992, 7, 3, pp.525-536.
• [6] Niewierowicz T., Escarela-Perez R., Campero-Littlewood E.: Hybrid Genetic Algorithm for the Identification of High-Order Synchronous Machine Two-Axis Equivalent Circuits, Computers & Electrical Engineering Journal, Elsevier Science Ltd., 2001, in press.
• [7] Silvester P.P., Ferrari R.L.: Finite Elements for Electrical Engineers, Cambridge University Press, 1996.