Research Article
Parameter Identification of Six-Order Synchronous Motor Model Based on Grey Box Modeling
@INPROCEEDINGS{10.1007/978-3-030-62483-5_6, author={Xianzhong Xu and Xunwen Su and Dongni Zhang and Pengyu An and Jian Sun}, title={Parameter Identification of Six-Order Synchronous Motor Model Based on Grey Box Modeling}, proceedings={Green Energy and Networking. 7th EAI International Conference, GreeNets 2020, Harbin, China, June 27-28, 2020, Proceedings}, proceedings_a={GREENETS}, year={2020}, month={11}, keywords={Synchronous machine Parameter identification Least square method}, doi={10.1007/978-3-030-62483-5_6} }- Xianzhong Xu
Xunwen Su
Dongni Zhang
Pengyu An
Jian Sun
Year: 2020
Parameter Identification of Six-Order Synchronous Motor Model Based on Grey Box Modeling
GREENETS
Springer
DOI: 10.1007/978-3-030-62483-5_6
Abstract
As the “heart” of power system, synchronous generator’s accurate model parameters are the basis of power system simulation, operation analysis and fault diagnosis. These parameters also have a very important impact on the operation analysis of power grid. This paper introduces the mathematical model of the sixth-order synchronous generator and establishes the incremental model for its identification. The methods of grey box modeling and nonlinear least square are used to identify the parameters of the sixth-order synchronous generator. When a single - phase short - circuit fault occurs in the power system, the response data of the generator is simulated in the PSASP software. When a program for synchronous machine parameter identification is written, the result will verify the validity of this approach.
