Multi-objective optimization and hybrid AI-based cable grounding method to prevent insulation failures in armored high voltage cables
| dc.contributor.author | Akbal, Bahadır | |
| dc.date.accessioned | 2024-04-19T06:04:43Z | |
| dc.date.available | 2024-04-19T06:04:43Z | |
| dc.date.issued | 2024 | |
| dc.department | Mühendislik Fakültesi | |
| dc.description.abstract | High voltage cable insulation fault is a major problem in high voltage lines. Armour current, armour voltage and current harmonics are major causes of the insulation faults in high voltage underground cables. These factors are major factors for high voltage insulation faults. Thus, cable bonding methods are used to prevent the cable insulation faults. The used methods in the literature do not prevent insulation faults that are based on armour harmonic current. In this study, a new cable bonding method is developed with multi-objective optimization and hybrid intelligence algorithm to prevent cable insulation faults. The proposed bonding method is shown in Figure A, and the parameters of these method is optimized with multi-objective optimization and hybrid intelligence algorithms. (Figure Presented) Purpose: The aim of this study is to prevent the cable insulation fault based on armour current harmonic and voltage by using intelligence algorithms. Theory and Methods: Metallic sheath voltage should be known for optimization of the proposed method. Thus, the forecasting methods are used to determine the sheath voltage. Hybrid artificial neural networks and regression methods are used to forecast sheath voltage. Also, multi objective optimization methods are used because there are many objective functions for optimization of the proposed bonding method. Artificial bee colony, genetic algorithm, gravitational search algorithm and particle swarm optimization are used as optimization methods, and the forecasting methods are used as objective function in optimization algorithms. Results: When H-ABC method is used as objective function for optimization of the proposed method, armour current, armour voltage and current harmonics values decrease according to solid bonding method that is used in the literature. Also, armour voltage is lower than touch voltage limit, and Armour current is lower than armour ampacity of the high voltage cable. Conclusion: Since armour current does not exceed armour ampacity, temperature of the insulation layer does not increase. Hence, insulation faults do not occur in the high voltage cable terminations. Also, since armour voltage is lower than touch voltage limit, electroshock for person is prevented by the suggested method. | |
| dc.identifier.doi | 10.17341/gazimmfd.979747 | |
| dc.identifier.endpage | 1364 | en_US |
| dc.identifier.issn | 1300-1884 | |
| dc.identifier.issue | 3 | en_US |
| dc.identifier.scopusquality | Q2 | |
| dc.identifier.startpage | 1351 | en_US |
| dc.identifier.uri | https:/dx.doi.org10.17341/gazimmfd.979747 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12451/11650 | |
| dc.identifier.volume | 39 | en_US |
| dc.indekslendigikaynak | Scopus | |
| dc.indekslendigikaynak | TR-Dizin | |
| dc.language.iso | tr | |
| dc.publisher | Gazi Universitesi | |
| dc.relation.ispartof | Journal of the Faculty of Engineering and Architecture of Gazi University | |
| dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | |
| dc.rights | info:eu-repo/semantics/closedAccess | |
| dc.subject | Cable Grounding | |
| dc.subject | Hybrid Artificial Neural Networks | |
| dc.subject | Insulation Faults | |
| dc.subject | Multi-objective Optimization | |
| dc.subject | Optimization | |
| dc.title | Multi-objective optimization and hybrid AI-based cable grounding method to prevent insulation failures in armored high voltage cables | |
| dc.title.alternative | Zırhlı yüksek gerilim kablolarında yalıtım arızalarını önlemek için çok amaçlı optimizasyon ve hibrit yapay zekâ tabanlı kablo topraklama yöntemi | |
| dc.type | Article |
