Artificial neural network based technique for energy management prediction

The energy management of electrical machine is significant to ensure efficient power consumption. Mismanagement of energy consumption could give impact on low efficiency of energy consumption that leads to power wastage. This paper presents analysis of power consumption and electricity costing of th...

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Main Authors: Wahab N.Ab., Mat Yasin Z., Salim N.A., Aziz N.F.A.
Other Authors: 35790572400
Format: Article
Published: Institute of Advanced Engineering and Science 2023
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spelling my.uniten.dspace-249362023-05-29T15:29:08Z Artificial neural network based technique for energy management prediction Wahab N.Ab. Mat Yasin Z. Salim N.A. Aziz N.F.A. 35790572400 57211410254 36806685300 57221906825 The energy management of electrical machine is significant to ensure efficient power consumption. Mismanagement of energy consumption could give impact on low efficiency of energy consumption that leads to power wastage. This paper presents analysis of power consumption and electricity costing of the electrical machineries and equipment in High Voltage (HV) and Electrical Machine (EM) Laboratories at Faculty of Electrical Engineering (FKE), Universiti Teknologi MARA (UiTM) Shah Alam, Selangor, Malaysia. The electrical data are collected using Fluke Meter 1750. Based on the analysis, it is found that the estimated annually electricity cost for HV Laboratory and EM Laboratory are RM 392.00 and RM 3197.76 respectively. For prediction of energy consumption of the two laboratories, Artificial Neural Network (ANN) algorithm is applied as computational tool using feedforward network type. The results show that the ANN is successfully modelled to predict the energy consumption. Copyright � 2020 Institute of Advanced Engineering and Science. All rights reserved. Final 2023-05-29T07:29:08Z 2023-05-29T07:29:08Z 2019 Article 10.11591/ijeecs.v17.i1.pp94-101 2-s2.0-85073811697 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85073811697&doi=10.11591%2fijeecs.v17.i1.pp94-101&partnerID=40&md5=ccd9b201adb776bb02ec67887cd8b5e1 https://irepository.uniten.edu.my/handle/123456789/24936 17 1 94 101 All Open Access, Gold, Green Institute of Advanced Engineering and Science Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description The energy management of electrical machine is significant to ensure efficient power consumption. Mismanagement of energy consumption could give impact on low efficiency of energy consumption that leads to power wastage. This paper presents analysis of power consumption and electricity costing of the electrical machineries and equipment in High Voltage (HV) and Electrical Machine (EM) Laboratories at Faculty of Electrical Engineering (FKE), Universiti Teknologi MARA (UiTM) Shah Alam, Selangor, Malaysia. The electrical data are collected using Fluke Meter 1750. Based on the analysis, it is found that the estimated annually electricity cost for HV Laboratory and EM Laboratory are RM 392.00 and RM 3197.76 respectively. For prediction of energy consumption of the two laboratories, Artificial Neural Network (ANN) algorithm is applied as computational tool using feedforward network type. The results show that the ANN is successfully modelled to predict the energy consumption. Copyright � 2020 Institute of Advanced Engineering and Science. All rights reserved.
author2 35790572400
author_facet 35790572400
Wahab N.Ab.
Mat Yasin Z.
Salim N.A.
Aziz N.F.A.
format Article
author Wahab N.Ab.
Mat Yasin Z.
Salim N.A.
Aziz N.F.A.
spellingShingle Wahab N.Ab.
Mat Yasin Z.
Salim N.A.
Aziz N.F.A.
Artificial neural network based technique for energy management prediction
author_sort Wahab N.Ab.
title Artificial neural network based technique for energy management prediction
title_short Artificial neural network based technique for energy management prediction
title_full Artificial neural network based technique for energy management prediction
title_fullStr Artificial neural network based technique for energy management prediction
title_full_unstemmed Artificial neural network based technique for energy management prediction
title_sort artificial neural network based technique for energy management prediction
publisher Institute of Advanced Engineering and Science
publishDate 2023
_version_ 1806425676162531328
score 13.214268