Akbal, Bahadir2020-03-262020-03-2620181392-1215https://dx.doi.org/10.5755/j01.eie.24.2.20633https://hdl.handle.net/20.500.12395/36827High temperature causes aging of insulation material of high voltage underground cable line (HVUL), so cable faults occurs. The sheath current (SC) is the most important factor for increasing of cable temperature, and SC can include harmonic, so cable temperature quickly increases. Namely harmonics facilitate SC based cable faults. Metallic sheath of HVUL is grounded to prevent SC based faults. Three bonding methods are used for grounding of metallic sheath in literature, but these methods do not exactly prevent SC effects, so the sectional solid bonding (SSB) is developed in literature, but these methods are not evaluated at the high harmonic distortion case. SSB should be optimized according to SC value. However, SC of HVUL which will be installed as a new line at project phase is not known. Thus, artificial neural network (ANN) and hybrid ANN methods are used to forecast SC of new line at the project phase. iPSO, PSO, GA and DEA methods are used for hybrid ANN methods and optimization of SSB. Performance of the optimized SSB (OSSB) at the high harmonic distortion case is evaluated to prove that use of OSSB for HVUL.en10.5755/j01.eie.24.2.20633info:eu-repo/semantics/openAccessHigh voltage cableSheath currentHybrid ANNBonding methodsArticle2423136Q3WOS:000431080000005Q4