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Optimal residence energy management with time and device-based preferences using an enhanced binary grey wolf optimization algorithm

In residential energy management (REM), time of use (TOU) of appliances scheduling based on user-defined preferences is an essential task performed by the home energy management controller. This paper devised a robust REM technique capable of monitoring and controlling residential loads within a sma...

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Main Authors: Ayub, Sara, Md. Ayob, Shahrin, Tan, Chee Wei, Ayub, Lubna, Bukar, Abba Lawan
Format: Article
Published: Elsevier 2020
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://eprints.utm.my/id/eprint/93348/
http://dx.doi.org/10.1007/978-3-030-60839-2_8
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spelling my.utm.933482021-11-30T08:28:44Z http://eprints.utm.my/id/eprint/93348/ Optimal residence energy management with time and device-based preferences using an enhanced binary grey wolf optimization algorithm Ayub, Sara Md. Ayob, Shahrin Tan, Chee Wei Ayub, Lubna Bukar, Abba Lawan TK Electrical engineering. Electronics Nuclear engineering In residential energy management (REM), time of use (TOU) of appliances scheduling based on user-defined preferences is an essential task performed by the home energy management controller. This paper devised a robust REM technique capable of monitoring and controlling residential loads within a smart home. The method is based on an improved binary grey wolf accretive satisfaction algorithm (GWASA), which is developed based on four hypotheses that allow time-varying preferences to be quantifiable in terms of time and device-dependent features. Based on household appliances TOU, the absolute satisfaction derived from the preferences of appliance and power ratings, the GWASA can produce optimum energy consumption pattern that will give the customer maximum satisfaction at the predefined user budget. A cost per unit satisfaction index is also established to relate daily consumer expenses with the achieved satisfaction. Simulation results on three peak budgets from $1.5/day to $2.5/day with a step size of $0.5 are carried out to analyze the efficacy of GWASA. Accordingly, the result of each of the scenario is compared with the result obtained from three other different algorithms, namely, BPSO, BGA, BGWO. The simulation results reveal that the proposed demand side residential management based on GWASA offers the least cost per unit satisfaction and maximum percentage satisfaction in each scenario. Elsevier 2020 Article PeerReviewed Ayub, Sara and Md. Ayob, Shahrin and Tan, Chee Wei and Ayub, Lubna and Bukar, Abba Lawan (2020) Optimal residence energy management with time and device-based preferences using an enhanced binary grey wolf optimization algorithm. Sustainable Energy Technologies And Assessments, 41 . p. 100798. ISSN 2213-1396 http://dx.doi.org/10.1007/978-3-030-60839-2_8
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Ayub, Sara
Md. Ayob, Shahrin
Tan, Chee Wei
Ayub, Lubna
Bukar, Abba Lawan
Optimal residence energy management with time and device-based preferences using an enhanced binary grey wolf optimization algorithm
description In residential energy management (REM), time of use (TOU) of appliances scheduling based on user-defined preferences is an essential task performed by the home energy management controller. This paper devised a robust REM technique capable of monitoring and controlling residential loads within a smart home. The method is based on an improved binary grey wolf accretive satisfaction algorithm (GWASA), which is developed based on four hypotheses that allow time-varying preferences to be quantifiable in terms of time and device-dependent features. Based on household appliances TOU, the absolute satisfaction derived from the preferences of appliance and power ratings, the GWASA can produce optimum energy consumption pattern that will give the customer maximum satisfaction at the predefined user budget. A cost per unit satisfaction index is also established to relate daily consumer expenses with the achieved satisfaction. Simulation results on three peak budgets from $1.5/day to $2.5/day with a step size of $0.5 are carried out to analyze the efficacy of GWASA. Accordingly, the result of each of the scenario is compared with the result obtained from three other different algorithms, namely, BPSO, BGA, BGWO. The simulation results reveal that the proposed demand side residential management based on GWASA offers the least cost per unit satisfaction and maximum percentage satisfaction in each scenario.
format Article
author Ayub, Sara
Md. Ayob, Shahrin
Tan, Chee Wei
Ayub, Lubna
Bukar, Abba Lawan
author_facet Ayub, Sara
Md. Ayob, Shahrin
Tan, Chee Wei
Ayub, Lubna
Bukar, Abba Lawan
author_sort Ayub, Sara
title Optimal residence energy management with time and device-based preferences using an enhanced binary grey wolf optimization algorithm
title_short Optimal residence energy management with time and device-based preferences using an enhanced binary grey wolf optimization algorithm
title_full Optimal residence energy management with time and device-based preferences using an enhanced binary grey wolf optimization algorithm
title_fullStr Optimal residence energy management with time and device-based preferences using an enhanced binary grey wolf optimization algorithm
title_full_unstemmed Optimal residence energy management with time and device-based preferences using an enhanced binary grey wolf optimization algorithm
title_sort optimal residence energy management with time and device-based preferences using an enhanced binary grey wolf optimization algorithm
publisher Elsevier
publishDate 2020
url http://eprints.utm.my/id/eprint/93348/
http://dx.doi.org/10.1007/978-3-030-60839-2_8
_version_ 1718926055014662144
score 13.211869

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