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Statistical approach for insulation coordination of high voltage substation exposed to lightning strikes

Introduction. Insulation coordination requires accurate prediction of overvoltages at various points within a substation. Computer simulations of electromagnetic transients in real structures of substations become more precise due to the improvements of used models. Goal. This paper discusses in a f...

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Bibliographic Details
Main Authors: Bedoui, S., Bayadi, A.
Format: Article
Language:English
Published: National Technical University "Kharkiv Polytechnic Institute" and State Institution “Institute of Technical Problems of Magnetism of the National Academy of Sciences of Ukraine” 2024
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Online Access:http://eie.khpi.edu.ua/article/view/300906
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Summary:Introduction. Insulation coordination requires accurate prediction of overvoltages at various points within a substation. Computer simulations of electromagnetic transients in real structures of substations become more precise due to the improvements of used models. Goal. This paper discusses in a first step the use of the modified ZnO arrester dynamic model alongside other substation equipment models, considering electrical phenomena like the corona model for reproducing the stresses that lightning can cause in an air-insulated substation and (method) then conducting a statistical approach based on the Monte Carlo method. The implemented MATLAB/ATP procedure estimates not only the substation Mean Time between Failures (MTBF), but also is used to select surge arresters or substation basic insulation levels (BILs). In this procedure ATP transients program is used to calculate lightning overvoltages and multicore environment for the calculations. Results. The obtained MTBF curves offer guidance for selecting appropriate insulation levels based on specific system requirements and conditions. The obtained results comply well with existing international insulation standards. This valuable approach significantly contributes to the field of lightning protection. References 31, tables 3, figures 10.