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Energy forecast using linear regression methods

Energy analysis and forecasting have always been the essential part of an efficient energy system planning and operation. This thesis presents the mathematical methods based on regression analysis and energy profiling for energy modelling and forecasting. Two applications of energy were analyz...

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Main Author: Hanafi, Noor Hasnizam
Format: Thesis
Language:English
English
English
Published: 2004
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
TK1001-1841 Production of electric energy or power. Powerplants. Central stations
Online Access:http://eprints.uthm.edu.my/7915/1/24p%20NOOR%20HASNIZAM%20HANAFI.pdf
http://eprints.uthm.edu.my/7915/2/NOOR%20HASNIZAM%20HANAFI%20COPYRIGHT%20DECLARATION.pdf
http://eprints.uthm.edu.my/7915/3/NOOR%20HASNIZAM%20HANAFI%20WATERMARK.pdf
http://eprints.uthm.edu.my/7915/
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spelling my.uthm.eprints.79152022-10-17T06:24:37Z http://eprints.uthm.edu.my/7915/ Energy forecast using linear regression methods Hanafi, Noor Hasnizam TK Electrical engineering. Electronics Nuclear engineering TK1001-1841 Production of electric energy or power. Powerplants. Central stations Energy analysis and forecasting have always been the essential part of an efficient energy system planning and operation. This thesis presents the mathematical methods based on regression analysis and energy profiling for energy modelling and forecasting. Two applications of energy were analyzed such as energy heating demands and electricity demands. The methods are applied for the Energieversorgung Offenbach AG (EVO) in Gravenbruch and Offenbach at Germany, using 1995 and 2003 dat^ The models of energy heating demands were developed based on simple linear and multiple regression methods. The Mean Absolute Percentage Errors (MAPE) are compared between two models. Two approaches to determine the typical energy profile are proposed. The two approaches use similar outdoor temperature for energy heating demand profiles and for electricity demands using similar electricity profile. The proposed approaches were able to determine the typical profiles of different type of day. 2004-10 Thesis NonPeerReviewed text en http://eprints.uthm.edu.my/7915/1/24p%20NOOR%20HASNIZAM%20HANAFI.pdf text en http://eprints.uthm.edu.my/7915/2/NOOR%20HASNIZAM%20HANAFI%20COPYRIGHT%20DECLARATION.pdf text en http://eprints.uthm.edu.my/7915/3/NOOR%20HASNIZAM%20HANAFI%20WATERMARK.pdf Hanafi, Noor Hasnizam (2004) Energy forecast using linear regression methods. Masters thesis, Kolej Universiti Teknologi Tun Hussein Onn.
institution Universiti Tun Hussein Onn Malaysia
building UTHM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tun Hussein Onn Malaysia
content_source UTHM Institutional Repository
url_provider http://eprints.uthm.edu.my/
language English
English
English
topic TK Electrical engineering. Electronics Nuclear engineering
TK1001-1841 Production of electric energy or power. Powerplants. Central stations
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
TK1001-1841 Production of electric energy or power. Powerplants. Central stations
Hanafi, Noor Hasnizam
Energy forecast using linear regression methods
description Energy analysis and forecasting have always been the essential part of an efficient energy system planning and operation. This thesis presents the mathematical methods based on regression analysis and energy profiling for energy modelling and forecasting. Two applications of energy were analyzed such as energy heating demands and electricity demands. The methods are applied for the Energieversorgung Offenbach AG (EVO) in Gravenbruch and Offenbach at Germany, using 1995 and 2003 dat^ The models of energy heating demands were developed based on simple linear and multiple regression methods. The Mean Absolute Percentage Errors (MAPE) are compared between two models. Two approaches to determine the typical energy profile are proposed. The two approaches use similar outdoor temperature for energy heating demand profiles and for electricity demands using similar electricity profile. The proposed approaches were able to determine the typical profiles of different type of day.
format Thesis
author Hanafi, Noor Hasnizam
author_facet Hanafi, Noor Hasnizam
author_sort Hanafi, Noor Hasnizam
title Energy forecast using linear regression methods
title_short Energy forecast using linear regression methods
title_full Energy forecast using linear regression methods
title_fullStr Energy forecast using linear regression methods
title_full_unstemmed Energy forecast using linear regression methods
title_sort energy forecast using linear regression methods
publishDate 2004
url http://eprints.uthm.edu.my/7915/1/24p%20NOOR%20HASNIZAM%20HANAFI.pdf
http://eprints.uthm.edu.my/7915/2/NOOR%20HASNIZAM%20HANAFI%20COPYRIGHT%20DECLARATION.pdf
http://eprints.uthm.edu.my/7915/3/NOOR%20HASNIZAM%20HANAFI%20WATERMARK.pdf
http://eprints.uthm.edu.my/7915/
_version_ 1748182674480037888
score 13.211869

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