Methods for Arc-Flash Prediction in Medium Voltage and Low Voltage Switchgear

Ghulam Amjad Hussain

Research output: ThesisDoctoral ThesisCollection of Articles

Abstract

Nowadays we are highly dependent on the electricity. It has become a need of daily life including domestic, commercial, transformational, industrial, health care and telecommunication purposes. Switchgear forms an integral part of the distribution network in power system. Hence, the occurrence of an electrical fault in switchgear causes interruption of electricity to the end users. Being highly dependent on electricity, such unexpected interruptions are unbearable by the modern society. Arc-flash is the unintentional discharge of electricity through air which produces very high temperature (19,600 ºC), which is hotter than the surface of the sun and a force equivalent to being hit by a hand grenade. Occurrence of an arc-flash in switchgear not only causes interruption of electric supply but damage to the equipment and personnel working in the vicinity. In the worst cases, damage is extended to the whole substation, hence maintenance duration can last upto few weeks. In USA alone, five to ten explosions occur due to arc-flashes every day. Due to the importance of the matter, arc-flash protection has been highly demanded for last two decades. Several reactive protection techniques have been introduced in the literature and some of them were implemented commercially. Continuous monitoring of the equipment and earlier detection of potential failures can facilitate a more proactive and a comprehensive arc-flash prevention system. This thesis mainly focuses on the pre-emptive detection of potential arc-flash in medium voltage (MV) and low voltage (LV) switchgear using online condition monitoring techniques. Three non-intrusive sensors i.e. D-dot sensor, Rogowski coil and thermal ionization detector have been designed, implemented and tested in switchgear to detect partial discharge, low power arcing and hotspots due to bad connections. Assessment of reliability, sensitivity and operability of the mentioned sensors is done in the laboratory. D-dot sensor is also tested on-site in operational MV switchgear for partial discharge. An effective de-noising technique based on discrete wavelet transform (DWT) is presented in this thesis. Moreover a novel idea for the detection of multiple faults in a panel based on correlation between the cumulative energy and apparent charge of discharge events is also presented. Hybrid low cost and non-intrusive solution integrated to the supervisory control and data acquisition (SCADA) system capable of continuous monitoring of switchgear and indicating any potential arc faults in switchgear before they lead to severe damage to the equipment and vicinity will be a breakthrough solution in minimizing arc-flash accidents, emergency interruptions and saving precious lives.
Translated title of the contributionValokaarivikojen ennakointimenetelmät keski- ja pienjännitekojeistoissa
Original languageEnglish
QualificationDoctor's degree
Awarding Institution
  • Aalto University
Supervisors/Advisors
  • Lehtonen, Matti, Supervising Professor
  • Lehtonen, Matti, Thesis Advisor
Publisher
Print ISBNs978-952-60-6600-4
Electronic ISBNs978-952-60-6599-1
Publication statusPublished - 2015
MoE publication typeG5 Doctoral dissertation (article)

Keywords

  • medium voltage
  • low voltage
  • switchgear
  • arc fault
  • partial discharge
  • condition monitoring
  • non-intrusive sensor

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