Please use this identifier to cite or link to this item: http://dspace.uniten.edu.my/jspui/handle/123456789/13186
Title: Artificial neural network based technique for energy management prediction
Authors: Wahab, N.Ab. 
Mat Yasin, Z. 
Salim, N.A. 
Aziz, N.F.A. 
Issue Date: 2019
Abstract: 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.
DOI: 10.11591/ijeecs.v17.i1.pp94-101
Appears in Collections:UNITEN Scholarly Publication

Show full item record

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.