Optimum enhance time of use (ETOU) for demand side electricity pricing in regulated market: An implementation using evolutionary algorithm
The energy growth in Malaysia is rapidly increasing as the country moves forward with the advancement of industrial revolution. Peak hours require more energy generation, thus cost is also more expensive than during off-peak. Due to this reason, Demand Side Management (DSM) through Demand Response (...
Published in: | Indonesian Journal of Electrical Engineering and Computer Science |
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Institute of Advanced Engineering and Science
2017
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2-s2.0-85037672992 Sulaima M.F.; Dahlan N.Y.; Yasin Z.M.; Asari N.A.M.; Bohari Z.H. Optimum enhance time of use (ETOU) for demand side electricity pricing in regulated market: An implementation using evolutionary algorithm 2017 Indonesian Journal of Electrical Engineering and Computer Science 8 1 10.11591/ijeecs.v8.i1.pp253-261 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85037672992&doi=10.11591%2fijeecs.v8.i1.pp253-261&partnerID=40&md5=c14e84631f79c07bf46be78bac641ccd The energy growth in Malaysia is rapidly increasing as the country moves forward with the advancement of industrial revolution. Peak hours require more energy generation, thus cost is also more expensive than during off-peak. Due to this reason, Demand Side Management (DSM) through Demand Response (DR) technique is introduced to modify the demand profile by implementing different strategies of measures. The objective of this study is to optimize the energy profile for commercial sector, as well as analyse the significance of electricity cost reduction by using the optimization technique. A Meta-heuristic technique called as Evolutionary Algorithm (EA) has been implemented in this study to optimize the load profile of a commercial installation. Significant testing shows that the proposed optimization technique has the ability to reform the Maximum Demand from peak zone to off-peak zone to reduce electricity cost. The test results have been validated through 4 cases, which are conventional method for C1 ETOU, C2 ETOU, and C1 ETOU with Optimization technique, and C2 ETOU with optimization technique tariff, respectively. The impact of the EP has been analysed, while the performance of six-time segmentation of C1 and C2 ETOU tariff indicate that the electricity cost for the medium voltage of installation has been reduced. It is hoped that the results from this study can benefit consumers by giving them the flexibility to rearrange their own energy consumption profile, so that the demand side will enjoy significant reduction of electricity cost in the future. © 2017 Institute of Advanced Engineering and Science. All rights reserved. Institute of Advanced Engineering and Science 25024752 English Article |
author |
Sulaima M.F.; Dahlan N.Y.; Yasin Z.M.; Asari N.A.M.; Bohari Z.H. |
spellingShingle |
Sulaima M.F.; Dahlan N.Y.; Yasin Z.M.; Asari N.A.M.; Bohari Z.H. Optimum enhance time of use (ETOU) for demand side electricity pricing in regulated market: An implementation using evolutionary algorithm |
author_facet |
Sulaima M.F.; Dahlan N.Y.; Yasin Z.M.; Asari N.A.M.; Bohari Z.H. |
author_sort |
Sulaima M.F.; Dahlan N.Y.; Yasin Z.M.; Asari N.A.M.; Bohari Z.H. |
title |
Optimum enhance time of use (ETOU) for demand side electricity pricing in regulated market: An implementation using evolutionary algorithm |
title_short |
Optimum enhance time of use (ETOU) for demand side electricity pricing in regulated market: An implementation using evolutionary algorithm |
title_full |
Optimum enhance time of use (ETOU) for demand side electricity pricing in regulated market: An implementation using evolutionary algorithm |
title_fullStr |
Optimum enhance time of use (ETOU) for demand side electricity pricing in regulated market: An implementation using evolutionary algorithm |
title_full_unstemmed |
Optimum enhance time of use (ETOU) for demand side electricity pricing in regulated market: An implementation using evolutionary algorithm |
title_sort |
Optimum enhance time of use (ETOU) for demand side electricity pricing in regulated market: An implementation using evolutionary algorithm |
publishDate |
2017 |
container_title |
Indonesian Journal of Electrical Engineering and Computer Science |
container_volume |
8 |
container_issue |
1 |
doi_str_mv |
10.11591/ijeecs.v8.i1.pp253-261 |
url |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85037672992&doi=10.11591%2fijeecs.v8.i1.pp253-261&partnerID=40&md5=c14e84631f79c07bf46be78bac641ccd |
description |
The energy growth in Malaysia is rapidly increasing as the country moves forward with the advancement of industrial revolution. Peak hours require more energy generation, thus cost is also more expensive than during off-peak. Due to this reason, Demand Side Management (DSM) through Demand Response (DR) technique is introduced to modify the demand profile by implementing different strategies of measures. The objective of this study is to optimize the energy profile for commercial sector, as well as analyse the significance of electricity cost reduction by using the optimization technique. A Meta-heuristic technique called as Evolutionary Algorithm (EA) has been implemented in this study to optimize the load profile of a commercial installation. Significant testing shows that the proposed optimization technique has the ability to reform the Maximum Demand from peak zone to off-peak zone to reduce electricity cost. The test results have been validated through 4 cases, which are conventional method for C1 ETOU, C2 ETOU, and C1 ETOU with Optimization technique, and C2 ETOU with optimization technique tariff, respectively. The impact of the EP has been analysed, while the performance of six-time segmentation of C1 and C2 ETOU tariff indicate that the electricity cost for the medium voltage of installation has been reduced. It is hoped that the results from this study can benefit consumers by giving them the flexibility to rearrange their own energy consumption profile, so that the demand side will enjoy significant reduction of electricity cost in the future. © 2017 Institute of Advanced Engineering and Science. All rights reserved. |
publisher |
Institute of Advanced Engineering and Science |
issn |
25024752 |
language |
English |
format |
Article |
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record_format |
scopus |
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Scopus |
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1809677908160020480 |