LAPSE:2023.11675
Published Article
LAPSE:2023.11675
Traction Load Modeling and Parameter Identification Based on Improved Sparrow Search Algorithm
Zhensheng Wu, Deling Fan, Fan Zou
February 27, 2023
In this paper, a traction load model parameter identification method based on the improved sparrow search algorithm (ISSA) is proposed. According to the load characteristics of the AC traction power supply system under transient disturbance, the model structure of the traction load is equated to the composite load model structure of the static load shunt induction motor’s dynamic load. The traditional sparrow search algorithm is improved to enhance its accuracy and convergence. The generalization ability of the model was tested, and the accuracy of the proposed model was verified. Using the ISSA to determine the load model from the measured data, the results can verify the effectiveness of the ISSA for comprehensive load model parameter identification. Comparing the ISSA with the traditional SSA and PSO algorithms, it shows that the ISSA has better accuracy and convergence.
Keywords
improved sparrow search algorithm, load modeling, parameter identification, traction load
Suggested Citation
Wu Z, Fan D, Zou F. Traction Load Modeling and Parameter Identification Based on Improved Sparrow Search Algorithm. (2023). LAPSE:2023.11675
Author Affiliations
Wu Z: School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China
Fan D: School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China [ORCID]
Zou F: Department of Earth Science, Uppsala University, 62157 Visby, Sweden
Journal Name
Energies
Volume
15
Issue
14
First Page
5034
Year
2022
Publication Date
2022-07-10
Published Version
ISSN
1996-1073
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Original Submission
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PII: en15145034, Publication Type: Journal Article
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LAPSE:2023.11675
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doi:10.3390/en15145034
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Feb 27, 2023
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