Intelligent identification of power quality disturbances

The increasing use of electronics in electrical equipment has made them more vulnerable to power quality disturbances. Customers are becoming more knowledgeable in these issues and demand for more detailed and precise information whenever an unfortunate event occurs. Therefore, power companies are e...

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Main Author: Loi, Kevin Jin Han.
Other Authors: Wang Peng
Format: Final Year Project
Language:English
Published: 2009
Subjects:
Online Access:http://hdl.handle.net/10356/17162
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-171622023-07-07T17:34:28Z Intelligent identification of power quality disturbances Loi, Kevin Jin Han. Wang Peng School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Electric power::Production, transmission and distribution The increasing use of electronics in electrical equipment has made them more vulnerable to power quality disturbances. Customers are becoming more knowledgeable in these issues and demand for more detailed and precise information whenever an unfortunate event occurs. Therefore, power companies are expanding the use of information processing techniques in the attempt to determine the cause and severity of power quality event so that remedy actions can be undertaken swiftly. One such process is to pinpoint the type of disturbance that has occurred. This is achieved through some form of pattern matching where signature patterns from past experiences or simulations are used to match the recorded event. However, there are many uncertainties with the network operating conditions and devices complicating the identification process. Some research works have been done in NTU in this area involving the use of advanced signal processing and fuzzy-logic based pattern matching techniques. This project is to test the proposed method for its robustness in handling the various uncertainties. Sample disturbances will be generated using Matlab and incorporated with various uncertainties. These are then used to test out the proposed method. Bachelor of Engineering 2009-06-01T03:36:56Z 2009-06-01T03:36:56Z 2009 2009 Final Year Project (FYP) http://hdl.handle.net/10356/17162 en Nanyang Technological University 67 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering::Electric power::Production, transmission and distribution
spellingShingle DRNTU::Engineering::Electrical and electronic engineering::Electric power::Production, transmission and distribution
Loi, Kevin Jin Han.
Intelligent identification of power quality disturbances
description The increasing use of electronics in electrical equipment has made them more vulnerable to power quality disturbances. Customers are becoming more knowledgeable in these issues and demand for more detailed and precise information whenever an unfortunate event occurs. Therefore, power companies are expanding the use of information processing techniques in the attempt to determine the cause and severity of power quality event so that remedy actions can be undertaken swiftly. One such process is to pinpoint the type of disturbance that has occurred. This is achieved through some form of pattern matching where signature patterns from past experiences or simulations are used to match the recorded event. However, there are many uncertainties with the network operating conditions and devices complicating the identification process. Some research works have been done in NTU in this area involving the use of advanced signal processing and fuzzy-logic based pattern matching techniques. This project is to test the proposed method for its robustness in handling the various uncertainties. Sample disturbances will be generated using Matlab and incorporated with various uncertainties. These are then used to test out the proposed method.
author2 Wang Peng
author_facet Wang Peng
Loi, Kevin Jin Han.
format Final Year Project
author Loi, Kevin Jin Han.
author_sort Loi, Kevin Jin Han.
title Intelligent identification of power quality disturbances
title_short Intelligent identification of power quality disturbances
title_full Intelligent identification of power quality disturbances
title_fullStr Intelligent identification of power quality disturbances
title_full_unstemmed Intelligent identification of power quality disturbances
title_sort intelligent identification of power quality disturbances
publishDate 2009
url http://hdl.handle.net/10356/17162
_version_ 1772828554438901760