Failure rate analysis and prediction for switchgears in power systems

Electricity demand has been on an upward trend in recent years. Switchgears are becoming ever more relied upon by businesses and consumers. Power systems are crucial in generating and distributing electricity. Switchgears in power systems play an important role by protecting, controlling and isolati...

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Main Author: Khoo, Emelyne Mary Hui Li
Other Authors: Hu Guoqiang
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2022
Subjects:
Online Access:https://hdl.handle.net/10356/158010
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1580102023-07-07T19:19:02Z Failure rate analysis and prediction for switchgears in power systems Khoo, Emelyne Mary Hui Li Hu Guoqiang School of Electrical and Electronic Engineering GQHu@ntu.edu.sg Engineering::Electrical and electronic engineering Electricity demand has been on an upward trend in recent years. Switchgears are becoming ever more relied upon by businesses and consumers. Power systems are crucial in generating and distributing electricity. Switchgears in power systems play an important role by protecting, controlling and isolating electrical equipment. A failure in a switchgear would negatively impact the whole power grid, which may lead to serious losses in businesses and in essential services. If we are able to determine an effective method to predict switchgear faults and take preventive maintenance before switchgear faults occur, the probability of switchgear faults can be reduced to a large extent. In addition, preventive maintenance can also extend the lifetime of switchgears, leading to lower costs in the long run. This final year project report will explain the background of predicting switchgear faults, analyse simulated data using statistical modeling and using tests to compare the models and fit. The language used will be Python Programming in a Jupyter notebook environment. Survival analysis using Weibull distribution and estimating time-to-failure using Kaplan-Meier will also be implemented in this project. Bachelor of Engineering (Electrical and Electronic Engineering) 2022-05-26T13:41:21Z 2022-05-26T13:41:21Z 2022 Final Year Project (FYP) Khoo, E. M. H. L. (2022). Failure rate analysis and prediction for switchgears in power systems. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/158010 https://hdl.handle.net/10356/158010 en A1061-211 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering
spellingShingle Engineering::Electrical and electronic engineering
Khoo, Emelyne Mary Hui Li
Failure rate analysis and prediction for switchgears in power systems
description Electricity demand has been on an upward trend in recent years. Switchgears are becoming ever more relied upon by businesses and consumers. Power systems are crucial in generating and distributing electricity. Switchgears in power systems play an important role by protecting, controlling and isolating electrical equipment. A failure in a switchgear would negatively impact the whole power grid, which may lead to serious losses in businesses and in essential services. If we are able to determine an effective method to predict switchgear faults and take preventive maintenance before switchgear faults occur, the probability of switchgear faults can be reduced to a large extent. In addition, preventive maintenance can also extend the lifetime of switchgears, leading to lower costs in the long run. This final year project report will explain the background of predicting switchgear faults, analyse simulated data using statistical modeling and using tests to compare the models and fit. The language used will be Python Programming in a Jupyter notebook environment. Survival analysis using Weibull distribution and estimating time-to-failure using Kaplan-Meier will also be implemented in this project.
author2 Hu Guoqiang
author_facet Hu Guoqiang
Khoo, Emelyne Mary Hui Li
format Final Year Project
author Khoo, Emelyne Mary Hui Li
author_sort Khoo, Emelyne Mary Hui Li
title Failure rate analysis and prediction for switchgears in power systems
title_short Failure rate analysis and prediction for switchgears in power systems
title_full Failure rate analysis and prediction for switchgears in power systems
title_fullStr Failure rate analysis and prediction for switchgears in power systems
title_full_unstemmed Failure rate analysis and prediction for switchgears in power systems
title_sort failure rate analysis and prediction for switchgears in power systems
publisher Nanyang Technological University
publishDate 2022
url https://hdl.handle.net/10356/158010
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