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:: Volume 8, Issue 1 (9-2019) ::
ieijqp 2019, 8(1): 62-71 Back to browse issues page
Cross Entropy-Based High-Impedance Fault Detection Algorithm for Distribution Networks
Shiva Nezamzadeh-Ejieh, Iman Sadeghkhani
Najafabad Branch, Islamic Azad University
Abstract:   (1295 Views)
The low fault current of high-impedance faults (HIFs) is one of the main challenges for the protection of distribution networks. The inability of conventional overcurrent relays in detecting these faults results in electric arc continuity that it causes the fire hazard and electric shock and poses a serious threat to human life and network equipment. This paper presents ​an HIF detection algorithm based on quantifying the nonlinear and asymmetry features of HIF waveforms. To this end, first, the substation current is sampled and then, the superimposed component of cross entropy signal calculated by comparing two subsequent half cycles of the current signal is determined as the HIF detection criteria. On the other hand, to overcome the challenge of the similar transient of device switching and HIF, the time duration of transient continuity is considered as the constraint of the proposed algorithm. The proposed scheme satisfactory works in the presence of nonlinear loads and does not need for training dataset, transformations, and calculation of harmonic and symmetrical components. The effectiveness of the proposed HIF detection algorithm is demonstrated using the time-domain simulation of IEEE 13 node test system.
 
Keywords: High-impedance fault, distribution network, cross entropy, protection
Full-Text [PDF 1263 kb]   (282 Downloads)    
Type of Study: Research | Subject: Special
Received: 2019/03/16 | Accepted: 2019/05/14 | Published: 2019/08/27
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Nezamzadeh-Ejieh S, Sadeghkhani I. Cross Entropy-Based High-Impedance Fault Detection Algorithm for Distribution Networks. ieijqp. 2019; 8 (1) :62-71
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Volume 8, Issue 1 (9-2019) Back to browse issues page
نشریه علمی- پژوهشی کیفیت و بهره وری صنعت برق ایران Iranian Electric Industry Journal of Quality and Productivity
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