Development Of Fault Zone Indentification Technique For Fault Location In A Medium Voltage Distribution Network
The power system network mainly consists of the generation, transmission, distribution and its loads (ordinary power consumers and large power consumers). Receiving feedback from the transmission system, the electric power distribution system forms the final stage in the delivery of electric powe...
Saved in:
Main Author: | |
---|---|
Format: | |
Language: | English |
Published: |
2023
|
Subjects: | |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Universiti Tenaga Nasional |
Language: | English |
id |
my.uniten.dspace-20680 |
---|---|
record_format |
dspace |
spelling |
my.uniten.dspace-206802023-05-05T04:08:44Z Development Of Fault Zone Indentification Technique For Fault Location In A Medium Voltage Distribution Network Isaac Mohandas John Full Final Thesis The power system network mainly consists of the generation, transmission, distribution and its loads (ordinary power consumers and large power consumers). Receiving feedback from the transmission system, the electric power distribution system forms the final stage in the delivery of electric power where the voltage value incoming from the transmission line is step down from high voltages such as 33kV, 22kV, 11kV and 6.6kV to low voltages 433/250V to be supplied to small power consumers. Fault occurrences is a continuous event that the distribution system experiences due to various phenomenon such as aging equipments, equipment failures in transformers and rotating machines, human errors and environmental conditions such as lightning strikes. These faults are abnormal conditions which can lead to interruption in electric flows, loss in voltage production resulting in power loss to consumers, equipment damages which results in costly and extensive repairs that affects the power system reliability to deliver electricity to its end consumers. Fault studies form an important part of power system analysis. When various types of fault occurs, the challenge is determining the bus voltages, line currents and locating the fault to minimize the impact of fault in distribution systems. Therefore, suitable methods are developed to overcome this problem such as impedance based methods and other fundamental frequency methods. Furthermore, much recently, knowledge-based methods have been developed which can be further divided to artificial intelligence techniques include Artificial Neural Network (ANN), hybrid methods, fuzzy logic, travelling wave and matching methods. The OpenDSS is an electric power Distribution System Simulator (DSS) used for supporting distributed resource integration and grid modernization efforts. The OpenDSS scripting language is designed to be reasonably close to common text data formats used in distribution system analysis tools and can be used to model transmission networks as well as distribution circuits. In this paper, we will use a machine learning language which is an open source distribution system simulation software (OpenDSS) to run fault simulations and identify the fault type. 2023-05-03T15:12:57Z 2023-05-03T15:12:57Z 2019-10 https://irepository.uniten.edu.my/handle/123456789/20680 en application/pdf |
institution |
Universiti Tenaga Nasional |
building |
UNITEN Library |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
Universiti Tenaga Nasional |
content_source |
UNITEN Institutional Repository |
url_provider |
http://dspace.uniten.edu.my/ |
language |
English |
topic |
Full Final Thesis |
spellingShingle |
Full Final Thesis Isaac Mohandas John Development Of Fault Zone Indentification Technique For Fault Location In A Medium Voltage Distribution Network |
description |
The power system network mainly consists of the generation, transmission,
distribution and its loads (ordinary power consumers and large power consumers).
Receiving feedback from the transmission system, the electric power distribution
system forms the final stage in the delivery of electric power where the voltage value
incoming from the transmission line is step down from high voltages such as 33kV,
22kV, 11kV and 6.6kV to low voltages 433/250V to be supplied to small power
consumers. Fault occurrences is a continuous event that the distribution system
experiences due to various phenomenon such as aging equipments, equipment failures
in transformers and rotating machines, human errors and environmental conditions
such as lightning strikes. These faults are abnormal conditions which can lead to
interruption in electric flows, loss in voltage production resulting in power loss to
consumers, equipment damages which results in costly and extensive repairs that
affects the power system reliability to deliver electricity to its end consumers. Fault
studies form an important part of power system analysis. When various types of fault
occurs, the challenge is determining the bus voltages, line currents and locating the
fault to minimize the impact of fault in distribution systems. Therefore, suitable
methods are developed to overcome this problem such as impedance based methods
and other fundamental frequency methods. Furthermore, much recently,
knowledge-based methods have been developed which can be further divided to
artificial intelligence techniques include Artificial Neural Network (ANN), hybrid
methods, fuzzy logic, travelling wave and matching methods. The OpenDSS is an
electric power Distribution System Simulator (DSS) used for supporting distributed
resource integration and grid modernization efforts. The OpenDSS scripting language
is designed to be reasonably close to common text data formats used in distribution
system analysis tools and can be used to model transmission networks as well as
distribution circuits. In this paper, we will use a machine learning language which is
an open source distribution system simulation software (OpenDSS) to run fault
simulations and identify the fault type. |
format |
|
author |
Isaac Mohandas John |
author_facet |
Isaac Mohandas John |
author_sort |
Isaac Mohandas John |
title |
Development Of Fault Zone Indentification Technique For Fault Location In A Medium Voltage Distribution Network |
title_short |
Development Of Fault Zone Indentification Technique For Fault Location In A Medium Voltage Distribution Network |
title_full |
Development Of Fault Zone Indentification Technique For Fault Location In A Medium Voltage Distribution Network |
title_fullStr |
Development Of Fault Zone Indentification Technique For Fault Location In A Medium Voltage Distribution Network |
title_full_unstemmed |
Development Of Fault Zone Indentification Technique For Fault Location In A Medium Voltage Distribution Network |
title_sort |
development of fault zone indentification technique for fault location in a medium voltage distribution network |
publishDate |
2023 |
_version_ |
1806427520465108992 |