Short-term load forecasting via artificial neural network

Load forecasting is a one of important element in Operation and Planning Division to predict behavior of load in future. There are several ways to forecast the load demand which can be categorized into two which are classical approach and artificial intelligence. Artificial intelligence has shown ab...

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Bibliographic Details
Main Author:	Muhtazaruddin, Mohd. Nabil
Format:	Thesis
Published:	2010
Subjects:	TK Electrical engineering Electronics Nuclear engineering
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id	my-utm-ep.36282
record_format	uketd_dc
spelling	my-utm-ep.362822017-08-16T02:52:58Z Short-term load forecasting via artificial neural network 2010 Muhtazaruddin, Mohd. Nabil TK Electrical engineering. Electronics Nuclear engineering Load forecasting is a one of important element in Operation and Planning Division to predict behavior of load in future. There are several ways to forecast the load demand which can be categorized into two which are classical approach and artificial intelligence. Artificial intelligence has shown ability to solve with this nonlinear characteristics and do not require any complex mathematical formulation. One of technique in artificial intelligence is Neural Network. This project focused on the neural network as a tool to project the electricity demand in the future. Before forecasting, first neural network must have to be designed by determine input, hidden layer and output numbers. The effectiveness of the neural network as a load forecasting is simulated using MATLAB Neural Network toolbox. In the neural network, back propagation technique is used as a learning algorithm and compares the final value with actual data by using Mean Absolute Percentage Error (MAPE) as percentage error between the output and actual value. Load forecasting using neural network has been tested using three models. Each of these models has different architecture in order to test the performance of neural network. The result shows that the load forecasting can be done by using neural network and MAPE of the models had achieved below than 10%. 2010 Thesis http://eprints.utm.my/id/eprint/36282/ masters Universiti Teknologi Malaysia, Faculty of Electrical Engineering Faculty of Electrical Engineering
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
topic	TK Electrical engineering Electronics Nuclear engineering
spellingShingle	TK Electrical engineering Electronics Nuclear engineering Muhtazaruddin, Mohd. Nabil Short-term load forecasting via artificial neural network
description	Load forecasting is a one of important element in Operation and Planning Division to predict behavior of load in future. There are several ways to forecast the load demand which can be categorized into two which are classical approach and artificial intelligence. Artificial intelligence has shown ability to solve with this nonlinear characteristics and do not require any complex mathematical formulation. One of technique in artificial intelligence is Neural Network. This project focused on the neural network as a tool to project the electricity demand in the future. Before forecasting, first neural network must have to be designed by determine input, hidden layer and output numbers. The effectiveness of the neural network as a load forecasting is simulated using MATLAB Neural Network toolbox. In the neural network, back propagation technique is used as a learning algorithm and compares the final value with actual data by using Mean Absolute Percentage Error (MAPE) as percentage error between the output and actual value. Load forecasting using neural network has been tested using three models. Each of these models has different architecture in order to test the performance of neural network. The result shows that the load forecasting can be done by using neural network and MAPE of the models had achieved below than 10%.
format	Thesis
qualification_level	Master's degree
author	Muhtazaruddin, Mohd. Nabil
author_facet	Muhtazaruddin, Mohd. Nabil
author_sort	Muhtazaruddin, Mohd. Nabil
title	Short-term load forecasting via artificial neural network
title_short	Short-term load forecasting via artificial neural network
title_full	Short-term load forecasting via artificial neural network
title_fullStr	Short-term load forecasting via artificial neural network
title_full_unstemmed	Short-term load forecasting via artificial neural network
title_sort	short-term load forecasting via artificial neural network
granting_institution	Universiti Teknologi Malaysia, Faculty of Electrical Engineering
granting_department	Faculty of Electrical Engineering
publishDate	2010
_version_	1747816423791525888

Short-term load forecasting via artificial neural network

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