Optimum cable bonding with pareto optimal and hybrid neural methods to prevent high-voltage cable insulation faults in distributed generation systems
dc.contributor.author | Akbal, Bahadır | |
dc.date.accessioned | 2025-02-07T13:56:59Z | |
dc.date.available | 2025-02-07T13:56:59Z | |
dc.date.issued | 2024 | |
dc.department | Mühendislik Fakültesi | |
dc.description.abstract | The high voltage, current and harmonic distortion in high-voltage cable metal sheaths cause cable insulation faults. The SSBLR (Sectional Solid Bonding with Inductance (L) and Resistance) method was designed as a new cable grounding method to prevent insulation faults. SSBLR was optimized using multi-objective optimization (MOP) with the prediction method (PM) to minimize these factors. The Pareto optimal method was used for MOP. The artificial neural network, hybrid artificial neural network and regression methods were used as the PM. When the artificial neural network–genetic algorithm hybrid method was used as the PM, and the genetic algorithm was used as the optimization method, the voltage and current were significantly reduced in the metal sheath of the cable. | |
dc.identifier.doi | 10.3390/pr12122909 | |
dc.identifier.issn | 2227-9717 | |
dc.identifier.issue | 12 | en_US |
dc.identifier.scopusquality | Q2 | |
dc.identifier.uri | https://dx.doi.org/10.3390/pr12122909 | |
dc.identifier.uri | https://hdl.handle.net/20.500.12451/12940 | |
dc.identifier.volume | 12 | en_US |
dc.indekslendigikaynak | Scopus | |
dc.language.iso | en | |
dc.publisher | Multidisciplinary Digital Publishing Institute (MDPI) | |
dc.relation.ispartof | Multidisciplinary Digital Publishing Institute (MDPI) | |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Başka Kurum Yazarı | |
dc.rights | info:eu-repo/semantics/openAccess | |
dc.subject | Multi-objective Optimization | |
dc.subject | Hybrid Neural Network | |
dc.subject | Optimization | |
dc.subject | High-Voltage Cable Grounding | |
dc.title | Optimum cable bonding with pareto optimal and hybrid neural methods to prevent high-voltage cable insulation faults in distributed generation systems | |
dc.type | Article |