Computational intelligence based technique for congestion management and compensation scheme in power system / Nur Zahirah Mohd Ali

Congestion problem is a crucial issue in power system. Its occurrence is closely related to loss increment and voltage decay in power system. The increment of load in a transmission system is one of the main factors that causes current increase. This leads to loss increment, while at the same time a...

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Main Author: Mohd Ali, Nur Zahirah
Format: Thesis
Language:English
Published: 2019
Subjects:
Online Access:https://ir.uitm.edu.my/id/eprint/82783/1/82783.pdf
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spelling my-uitm-ir.827832024-01-10T00:47:30Z Computational intelligence based technique for congestion management and compensation scheme in power system / Nur Zahirah Mohd Ali 2019 Mohd Ali, Nur Zahirah TK Electrical engineering. Electronics. Nuclear engineering Congestion problem is a crucial issue in power system. Its occurrence is closely related to loss increment and voltage decay in power system. The increment of load in a transmission system is one of the main factors that causes current increase. This leads to loss increment, while at the same time affecting the congestion event in the system. The impact leads to the increment in generation cost during congestion. Therefore, congestion management needs to be performed properly in order to deliver enough power to the system resulted by transmission line congestion. Failure to handle this situation may lead to bigger problems such as voltage collapse and cascading blackout. This thesis presents computational intelligence-based technique for congestion management and compensation scheme in power systems. In this study, a new model termed as Integrated Multilayer Artificial Neural Networks (IMLANNs) is developed to predict congested line and voltage stability index separately. Consequently, a new optimization technique termed as Clonal Evolutionary Particle Swarm Optimization (CEPSO) was developed. CEPSO integrates the element of cloning and swarm in the original Evolutionary Programming algorithm. CEPSO is initially used to optimize the location and sizing of FACTS devices for compensation scheme. In this study, Static VAR Compensator (SVC) and Thyristor Control Static Compensator (TCSC) are the two chosen Flexible AC Transmission System (FACTS) devices used in this compensation scheme. 2019 Thesis https://ir.uitm.edu.my/id/eprint/82783/ https://ir.uitm.edu.my/id/eprint/82783/1/82783.pdf text en public phd doctoral Universiti Teknologi MARA (UiTM) Faculty of Electrical Engineering Musirin, Ismail
institution Universiti Teknologi MARA
collection UiTM Institutional Repository
language English
advisor Musirin, Ismail
topic TK Electrical engineering
Electronics
Nuclear engineering
spellingShingle TK Electrical engineering
Electronics
Nuclear engineering
Mohd Ali, Nur Zahirah
Computational intelligence based technique for congestion management and compensation scheme in power system / Nur Zahirah Mohd Ali
description Congestion problem is a crucial issue in power system. Its occurrence is closely related to loss increment and voltage decay in power system. The increment of load in a transmission system is one of the main factors that causes current increase. This leads to loss increment, while at the same time affecting the congestion event in the system. The impact leads to the increment in generation cost during congestion. Therefore, congestion management needs to be performed properly in order to deliver enough power to the system resulted by transmission line congestion. Failure to handle this situation may lead to bigger problems such as voltage collapse and cascading blackout. This thesis presents computational intelligence-based technique for congestion management and compensation scheme in power systems. In this study, a new model termed as Integrated Multilayer Artificial Neural Networks (IMLANNs) is developed to predict congested line and voltage stability index separately. Consequently, a new optimization technique termed as Clonal Evolutionary Particle Swarm Optimization (CEPSO) was developed. CEPSO integrates the element of cloning and swarm in the original Evolutionary Programming algorithm. CEPSO is initially used to optimize the location and sizing of FACTS devices for compensation scheme. In this study, Static VAR Compensator (SVC) and Thyristor Control Static Compensator (TCSC) are the two chosen Flexible AC Transmission System (FACTS) devices used in this compensation scheme.
format Thesis
qualification_name Doctor of Philosophy (PhD.)
qualification_level Doctorate
author Mohd Ali, Nur Zahirah
author_facet Mohd Ali, Nur Zahirah
author_sort Mohd Ali, Nur Zahirah
title Computational intelligence based technique for congestion management and compensation scheme in power system / Nur Zahirah Mohd Ali
title_short Computational intelligence based technique for congestion management and compensation scheme in power system / Nur Zahirah Mohd Ali
title_full Computational intelligence based technique for congestion management and compensation scheme in power system / Nur Zahirah Mohd Ali
title_fullStr Computational intelligence based technique for congestion management and compensation scheme in power system / Nur Zahirah Mohd Ali
title_full_unstemmed Computational intelligence based technique for congestion management and compensation scheme in power system / Nur Zahirah Mohd Ali
title_sort computational intelligence based technique for congestion management and compensation scheme in power system / nur zahirah mohd ali
granting_institution Universiti Teknologi MARA (UiTM)
granting_department Faculty of Electrical Engineering
publishDate 2019
url https://ir.uitm.edu.my/id/eprint/82783/1/82783.pdf
_version_ 1794191945655910400