Voltage stability prediction using artificial neural network for IEEE 69-bus and 30-bus / Nur Adha Hanif Mat Rahim

This project discusses the voltage stability prediction of a power system using Artificial Neural Network (ANN). Voltage instability is the one of the causes for a power system to breakdown. This incident is caused by severe low voltage condition which leads to blackouts to all system. The voltage s...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Mat Rahim, Nur Adha Hanif
التنسيق: أطروحة
اللغة:English
منشور في: 2014
الموضوعات:
الوصول للمادة أونلاين:https://ir.uitm.edu.my/id/eprint/78122/1/78122.pdf
الوسوم: إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
id my-uitm-ir.78122
record_format uketd_dc
spelling my-uitm-ir.781222024-05-17T09:01:09Z Voltage stability prediction using artificial neural network for IEEE 69-bus and 30-bus / Nur Adha Hanif Mat Rahim 2014 Mat Rahim, Nur Adha Hanif Neural networks (Computer science) This project discusses the voltage stability prediction of a power system using Artificial Neural Network (ANN). Voltage instability is the one of the causes for a power system to breakdown. This incident is caused by severe low voltage condition which leads to blackouts to all system. The voltage stability prediction is essential in power system planning in order to prevent voltage collapse due to instability of voltage in power system. The voltage stability for each bus 1s determined by Voltage Stability Index (VSI). The value obtain from the VSI can determine the voltage stability for each bus in the system. There are two types of bus that will be use to determine the voltage stability prediction in power system which is 69-bus and 30-bus. A comparative study was conducted with Artificial Neural Network (ANN)-based prediction. 2014 Thesis https://ir.uitm.edu.my/id/eprint/78122/ https://ir.uitm.edu.my/id/eprint/78122/1/78122.pdf text en public degree Universiti Teknologi MARA (UiTM) Faculty of Electrical Engineering Mohd. Arshad, Pauziah
institution Universiti Teknologi MARA
collection UiTM Institutional Repository
language English
advisor Mohd. Arshad, Pauziah
topic Neural networks (Computer science)
spellingShingle Neural networks (Computer science)
Mat Rahim, Nur Adha Hanif
Voltage stability prediction using artificial neural network for IEEE 69-bus and 30-bus / Nur Adha Hanif Mat Rahim
description This project discusses the voltage stability prediction of a power system using Artificial Neural Network (ANN). Voltage instability is the one of the causes for a power system to breakdown. This incident is caused by severe low voltage condition which leads to blackouts to all system. The voltage stability prediction is essential in power system planning in order to prevent voltage collapse due to instability of voltage in power system. The voltage stability for each bus 1s determined by Voltage Stability Index (VSI). The value obtain from the VSI can determine the voltage stability for each bus in the system. There are two types of bus that will be use to determine the voltage stability prediction in power system which is 69-bus and 30-bus. A comparative study was conducted with Artificial Neural Network (ANN)-based prediction.
format Thesis
qualification_level Bachelor degree
author Mat Rahim, Nur Adha Hanif
author_facet Mat Rahim, Nur Adha Hanif
author_sort Mat Rahim, Nur Adha Hanif
title Voltage stability prediction using artificial neural network for IEEE 69-bus and 30-bus / Nur Adha Hanif Mat Rahim
title_short Voltage stability prediction using artificial neural network for IEEE 69-bus and 30-bus / Nur Adha Hanif Mat Rahim
title_full Voltage stability prediction using artificial neural network for IEEE 69-bus and 30-bus / Nur Adha Hanif Mat Rahim
title_fullStr Voltage stability prediction using artificial neural network for IEEE 69-bus and 30-bus / Nur Adha Hanif Mat Rahim
title_full_unstemmed Voltage stability prediction using artificial neural network for IEEE 69-bus and 30-bus / Nur Adha Hanif Mat Rahim
title_sort voltage stability prediction using artificial neural network for ieee 69-bus and 30-bus / nur adha hanif mat rahim
granting_institution Universiti Teknologi MARA (UiTM)
granting_department Faculty of Electrical Engineering
publishDate 2014
url https://ir.uitm.edu.my/id/eprint/78122/1/78122.pdf
_version_ 1804889699004710912