Cover Image

An artificial neural network in short term load forecasting / Norhayati Rahim

Load forecasting plays an important role in electric power system operations and planning purposes. Improving the accuracy of the load forecast can optimize the operation of the electrical system and save significant amount of money. Therefore, this study investigates the effectiveness of an artific...

Full description

Saved in:
Bibliographic Details
Main Author: Rahim, Norhayati
Format: Thesis
Language:English
Published: 1999
Online Access:https://ir.uitm.edu.my/id/eprint/103342/1/103342.pdf
https://ir.uitm.edu.my/id/eprint/103342/
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.uitm.ir.103342
record_format eprints
spelling my.uitm.ir.1033422024-09-28T16:42:49Z https://ir.uitm.edu.my/id/eprint/103342/ An artificial neural network in short term load forecasting / Norhayati Rahim Rahim, Norhayati Load forecasting plays an important role in electric power system operations and planning purposes. Improving the accuracy of the load forecast can optimize the operation of the electrical system and save significant amount of money. Therefore, this study investigates the effectiveness of an artificial neural network (ANN) approach to short term load forecasting (STLF) in power systems. Two approaches of ANN algorithms i.e. the Back-Propagation Network (BPN) and Modular Neural Network (MNN) were investigated. Accuracy of the networks depend on some associated factors which usually affect ANN structure and training parameters such as learning rate (TJ), momentum constant (a), number of hidden node (s) and number of iteration. Hourly loads (24 hour per day) of current day were used as the inputs with the type of day of weekdays (Monday to Friday), Saturday and Sunday. The 24-hour loads for the next day were chosen as the outputs. Both networks were trained and tested on actual load data and weather conditions for the next day's load forecast by using software package Professional II/PLUS and NeuralWorks. The capability of both networks based STLF has been found to be very encouraging 1999 Thesis NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/103342/1/103342.pdf An artificial neural network in short term load forecasting / Norhayati Rahim. (1999) Degree thesis, thesis, Universiti Teknologi MARA (UiTM). <http://terminalib.uitm.edu.my/103342.pdf>
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
description Load forecasting plays an important role in electric power system operations and planning purposes. Improving the accuracy of the load forecast can optimize the operation of the electrical system and save significant amount of money. Therefore, this study investigates the effectiveness of an artificial neural network (ANN) approach to short term load forecasting (STLF) in power systems. Two approaches of ANN algorithms i.e. the Back-Propagation Network (BPN) and Modular Neural Network (MNN) were investigated. Accuracy of the networks depend on some associated factors which usually affect ANN structure and training parameters such as learning rate (TJ), momentum constant (a), number of hidden node (s) and number of iteration. Hourly loads (24 hour per day) of current day were used as the inputs with the type of day of weekdays (Monday to Friday), Saturday and Sunday. The 24-hour loads for the next day were chosen as the outputs. Both networks were trained and tested on actual load data and weather conditions for the next day's load forecast by using software package Professional II/PLUS and NeuralWorks. The capability of both networks based STLF has been found to be very encouraging
format Thesis
author Rahim, Norhayati
spellingShingle Rahim, Norhayati
An artificial neural network in short term load forecasting / Norhayati Rahim
author_facet Rahim, Norhayati
author_sort Rahim, Norhayati
title An artificial neural network in short term load forecasting / Norhayati Rahim
title_short An artificial neural network in short term load forecasting / Norhayati Rahim
title_full An artificial neural network in short term load forecasting / Norhayati Rahim
title_fullStr An artificial neural network in short term load forecasting / Norhayati Rahim
title_full_unstemmed An artificial neural network in short term load forecasting / Norhayati Rahim
title_sort artificial neural network in short term load forecasting / norhayati rahim
publishDate 1999
url https://ir.uitm.edu.my/id/eprint/103342/1/103342.pdf
https://ir.uitm.edu.my/id/eprint/103342/
_version_ 1811598315994742784
score 13.211869

Similar Items