Please use this identifier to cite or link to this item:
Title: Artificial intelligence based high voltage cable bonding to prevent cable termination faults
Authors: Akbal, Bahadır
Keywords: Bonding Method
High Voltage Cable Termination
Hybrid Artificial Neural Network
Insulation Fault
Power Transmission
Danish Experience
Issue Date: 2020
Abstract: Cable termination fault (CTF) is a major problem for high voltage cable lines (HVCL). Increasing of the sheath voltage (SV), zero sequence current (ZC) and current harmonic distortion (THDI) on metallic sheath (MS) of HVC are major factors for CTF. MS is grounded according to IEEE 575-1988 standard to reduce SV. However, these methods are not sufficient to prevent CTF based on ZC and THDI. The aims of this paper are minimization of SV, ZC and THDI to prevent CTF based on ZC and THDI. Thus, LSSB method is developed as a new bonding method. Also, LSSB parameters should be optimized to make the most economical and practical bonding. GA, DEA, PSO and iPSO are used optimization methods for optimization of LSSB. SV and THDI should be known for optimization of LSSB, so the forecasting methods (FM) are used as fitness function of optimization methods in LSSB optimization. The regression and hybrid artificial neural network methods are compared to determine the most suitable FM. When the optimized LSSB is used for bonding of long HVCL, SV reduces approximately 90%, ZC reduces approximately 93%, and THDI reduces approximately 70%. Thus CTF risk is minimized by using the optimized LSSB in HVCL.
ISSN: 0378-7796
Appears in Collections:Mühendislik ve Doğa Bilimleri Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collections
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collections

Files in This Item:
File SizeFormat 
  Until 2030-01-01
4.3 MBAdobe PDFView/Open    Request a copy
Show full item record

CORE Recommender

Page view(s)

checked on Dec 4, 2023


checked on Dec 4, 2023

Google ScholarTM



Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.