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Research on Flashover Voltage Prediction of Catenary Insulator Based on CaSO4 Pollution with Different Mass Fraction

Sihua Wang1,2, Junjun Wang1,2,*, Lijun Zhou1,2, Long Chen1,2, Lei Zhao1,2
1 College of Automation & Electrical Engineering, Lanzhou Jiaotong University, Lanzhou, 730070, China
2 Rail Transit Electrical Automation Engineering Laboratory of Gansu Province, Lanzhou Jiaotong University, Lanzhou, 730070, China
* Corresponding Author: Junjun Wang. Email:
(This article belongs to this Special Issue: The Role of Artificial Intelligence for Modeling and Optimizing the Energy Systems )

Energy Engineering 2022, 119(1), 219-236. https://doi.org/10.32604/EE.2022.016899

Received 07 April 2021; Accepted 28 June 2021; Issue published 22 November 2021

Abstract

Pollution flashover accidents occur frequently in railway OCS in saline-alkali areas. To accurately predict the pollution flashover voltage of insulators, a pollution flashover warning should be made in advance. According to the operating environment of insulators along the Qinghai-Tibet railway, the pollution flashover experiments were designed for the cantilever composite insulator FQBG-25/12. Through the experiments, the flashover voltage under the influence of soluble contaminant density (SCD) of different pollution components, non-soluble deposit density (NSDD), temperature (T), and atmospheric pressure (P) was obtained. On this basis, the GA-BP neural network prediction model was established. P, SCD, NSDD, CaSO4 mass fraction (w(CaSO4)), and T were taken as input parameters, 50% flashover voltage (U50%) of the insulator was taken as output parameters. The results showed that the prediction deviation was less than 10%, which meets the basic engineering requirements. The results could not only provide early warning for the anti-pollution flashover work of the railway power supply department, but also be used as an auxiliary contrast to verify the accuracy of the results of the experiments, and provide a theoretical basis for the classification of pollution levels in different regions.


Keywords

Overhead contact system; (CaSO); insulator; pollution flashover test; genetic algorithm-back propagation (GA-BP) neural network; flashover voltage prediction

Cite This Article

Wang, S., Wang, J., Zhou, L., Chen, L., Zhao, L. (2022). Research on Flashover Voltage Prediction of Catenary Insulator Based on CaSO Pollution with Different Mass Fraction. Energy Engineering, 119(1), 219–236.



This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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