Testing of an Adaptive Algorithm for Estimating the Parameters of a Synchronous Generator Based on the Approximation of Electrical State Time Series

Author:

Senyuk MihailORCID,Beryozkina SvetlanaORCID,Berdin Alexander,Moiseichenkov Alexander,Safaraliev MurodbekORCID,Zicmane Inga

Abstract

The results of testing the algorithms of the adaptive model of a synchronous generator using theoretical and real physical data are presented in this study. The adaptive model of a synchronous machine is an equations system, which describes both the static and transient operation of a generator. Parameters of the adaptive model are found using measurements of a generator’s operational parameters. The single-machine model was created in Matlab/Simulink software to test the theoretical data. This single-machine model consists of a synchronous generator, a step-up transformer, and a transmission line. The test model also includes models of the automatic voltage regulator and steam turbine governor. The real electrodynamic model was used to verify the adaptive model of a synchronous machine. It consisted of four synchronous generators, with values of power capacity of 5 kW and 15 kW. The data logger with a sampling rate of 57.8 kHz was developed and installed to measure the operating parameters of each generator. As a result of testing on both models, the following values were estimated: inertia moment, d-axis and q-axis reactance, and load angle. These values were compared with the reference values. The adaptive model of a synchronous machine can be used in systems of emergency control and assessment of generator state.

Publisher

MDPI AG

Subject

General Mathematics,Engineering (miscellaneous),Computer Science (miscellaneous)

Reference43 articles.

1. A Review on Microgrids’ Challenges & Perspectives;Saeed;IEEE Access,2021

2. Fereidouni, A., Susanto, J., Mancarella, P., Hong, N., Smit, T., and Sharafi, D. Online Security Assessment of Low-Inertia Power Systems: A Real-Time Frequency Stability Tool for the Australian South-West Interconnected System. Proceedings of the 31st Australasian Universities Power Engineering Conference (AUPEC).

3. Moiseichenkov, A.N., Kovalenko, P.Y., Senyuk, M.D., and Mukhin, V.I. Synchronous Machine Adaptive Model for Power System Emergency Control and Technical State Diagnostic. Proceedings of the 2020 Ural Smart Energy Conference (USEC).

4. Adkins, B., and Harley, R.G. The General Theory of Alternating Current Machines: Applications to Practical Problems, 1975.

5. IEEE Guide: Test Procedures for Synchronous Machines, 1995.

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