TY - GEN
T1 - Risk Assessment of Electrical Defects in MV Switchgear Using Partial Discharge Diagnostics
AU - Hussain, G. Amjad
AU - Hassan, Waqar
AU - Mahmood, Farhan
AU - Kay, John A.
N1 - Funding Information:
This research work is funded by the Kuwait Foundation for the Advancement of Sciences (KFAS) via project code PR18- 18EO-01
Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Partial discharge (PD) diagnostic is regarded as a powerful method for diagnosing the potential electrical insulation defects in a medium voltage (MV) and high voltage (HV) switchgear. This paper proposes a method, termed as a risk-based approach, to identify the severity of several critical electrical defects in MVI HV switchgear based on partial discharge testing. To accomplish this, several defects have been artificially created in a MV switchgear. Testing was carried out to investigate the characteristics of PD signals using nonintrusive sensors. Accordingly, the specific PD intensity of the discharge pulse has been considered as stress parameters and then statistically modelled by suitable probability distribution. In this way, the probability of dielectric failure has been quantified. The consequences of dielectric failure, and hence the failure of the switchgear are given by the power outage cost and repair expenditures. The risk assessment is made by combing both of these factors. The estimated risk is an indication of the criticality of the fault and can be specified as low, medium, high, or maximum. In this way, the proposed approach can be easily adopted by asset manager for risk assessment of switchgear in the petroleum and chemical industries.
AB - Partial discharge (PD) diagnostic is regarded as a powerful method for diagnosing the potential electrical insulation defects in a medium voltage (MV) and high voltage (HV) switchgear. This paper proposes a method, termed as a risk-based approach, to identify the severity of several critical electrical defects in MVI HV switchgear based on partial discharge testing. To accomplish this, several defects have been artificially created in a MV switchgear. Testing was carried out to investigate the characteristics of PD signals using nonintrusive sensors. Accordingly, the specific PD intensity of the discharge pulse has been considered as stress parameters and then statistically modelled by suitable probability distribution. In this way, the probability of dielectric failure has been quantified. The consequences of dielectric failure, and hence the failure of the switchgear are given by the power outage cost and repair expenditures. The risk assessment is made by combing both of these factors. The estimated risk is an indication of the criticality of the fault and can be specified as low, medium, high, or maximum. In this way, the proposed approach can be easily adopted by asset manager for risk assessment of switchgear in the petroleum and chemical industries.
KW - Cumulative energy function
KW - MV/ HV switchgear
KW - Probability distributions
KW - insulation defects
KW - partial discharge measurements
KW - risk assessment
UR - https://www.scopus.com/pages/publications/85166740343
U2 - 10.1109/PCIC42668.2022.10181273
DO - 10.1109/PCIC42668.2022.10181273
M3 - Conference contribution
AN - SCOPUS:85166740343
T3 - Record of Conference Papers - Annual Petroleum and Chemical Industry Conference
SP - 357
EP - 364
BT - 2022 IEEE IAS Petroleum and Chemical Industry Technical Conference, PCIC 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 IEEE IAS Petroleum and Chemical Industry Technical Conference, PCIC 2022
Y2 - 26 September 2022 through 29 September 2022
ER -