Residential Demand Response Scheduling with Consideration of Consumer Preferences

<p dir="ltr">This paper proposes a new demand response scheduling framework for an array of households, which are grouped into different categories based on socio-economic factors, such as the number of occupants, family decomposition and employment status. Each of the households is...

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Main Author: Raka Jovanovic (17947838) (author)
Other Authors: Abdelkader Bousselham (19730731) (author), Islam Bayram (19720132) (author)
Published: 2016
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author Raka Jovanovic (17947838)
author2 Abdelkader Bousselham (19730731)
Islam Bayram (19720132)
author2_role author
author
author_facet Raka Jovanovic (17947838)
Abdelkader Bousselham (19730731)
Islam Bayram (19720132)
author_role author
dc.creator.none.fl_str_mv Raka Jovanovic (17947838)
Abdelkader Bousselham (19730731)
Islam Bayram (19720132)
dc.date.none.fl_str_mv 2016-01-12T03:00:00Z
dc.identifier.none.fl_str_mv 10.3390/app6010016
dc.relation.none.fl_str_mv https://figshare.com/articles/journal_contribution/Residential_Demand_Response_Scheduling_with_Consideration_of_Consumer_Preferences/27094525
dc.rights.none.fl_str_mv CC BY 4.0
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Mathematical sciences
Applied mathematics
demand response
mixed integer linear programming
scheduling
smart grids
dc.title.none.fl_str_mv Residential Demand Response Scheduling with Consideration of Consumer Preferences
dc.type.none.fl_str_mv Text
Journal contribution
info:eu-repo/semantics/publishedVersion
text
contribution to journal
description <p dir="ltr">This paper proposes a new demand response scheduling framework for an array of households, which are grouped into different categories based on socio-economic factors, such as the number of occupants, family decomposition and employment status. Each of the households is equipped with a variety of appliances. The model takes the preferences of participating households into account and aims to minimize the overall production cost and, in parallel, to lower the individual electricity bills. In the existing literature, customers submit binary values for each time period to indicate their operational preferences. However, turning the appliances “on” or “off” does not capture the associated discomfort levels, as each appliance provides a different service and leads to a different level of satisfaction. The proposed model employs integer values to indicate household preferences and models the scheduling problem as a multi-objective mixed integer programming. The main thrust of the framework is that the multi-level preference modeling of appliances increases their “flexibility”; hence, the job scheduling can be done at a lower cost. The model is evaluated by using the real data provided by the Department of Energy & Climate Change, UK. In the computational experiments, we examine the relation between the satisfaction of consumers based on the appliance usage preferences and the electricity costs by exploring the Pareto front of the related objective functions. The results show that the proposed model leads to significant savings in electricity cost, while maintaining a good level of customer satisfaction.</p><h2>Other Information</h2><p dir="ltr">Published in: Applied Sciences<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.3390/app6010016" target="_blank">https://dx.doi.org/10.3390/app6010016</a></p>
eu_rights_str_mv openAccess
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identifier_str_mv 10.3390/app6010016
network_acronym_str Manara2
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oai_identifier_str oai:figshare.com:article/27094525
publishDate 2016
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spelling Residential Demand Response Scheduling with Consideration of Consumer PreferencesRaka Jovanovic (17947838)Abdelkader Bousselham (19730731)Islam Bayram (19720132)Mathematical sciencesApplied mathematicsdemand responsemixed integer linear programmingschedulingsmart grids<p dir="ltr">This paper proposes a new demand response scheduling framework for an array of households, which are grouped into different categories based on socio-economic factors, such as the number of occupants, family decomposition and employment status. Each of the households is equipped with a variety of appliances. The model takes the preferences of participating households into account and aims to minimize the overall production cost and, in parallel, to lower the individual electricity bills. In the existing literature, customers submit binary values for each time period to indicate their operational preferences. However, turning the appliances “on” or “off” does not capture the associated discomfort levels, as each appliance provides a different service and leads to a different level of satisfaction. The proposed model employs integer values to indicate household preferences and models the scheduling problem as a multi-objective mixed integer programming. The main thrust of the framework is that the multi-level preference modeling of appliances increases their “flexibility”; hence, the job scheduling can be done at a lower cost. The model is evaluated by using the real data provided by the Department of Energy & Climate Change, UK. In the computational experiments, we examine the relation between the satisfaction of consumers based on the appliance usage preferences and the electricity costs by exploring the Pareto front of the related objective functions. The results show that the proposed model leads to significant savings in electricity cost, while maintaining a good level of customer satisfaction.</p><h2>Other Information</h2><p dir="ltr">Published in: Applied Sciences<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.3390/app6010016" target="_blank">https://dx.doi.org/10.3390/app6010016</a></p>2016-01-12T03:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.3390/app6010016https://figshare.com/articles/journal_contribution/Residential_Demand_Response_Scheduling_with_Consideration_of_Consumer_Preferences/27094525CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/270945252016-01-12T03:00:00Z
spellingShingle Residential Demand Response Scheduling with Consideration of Consumer Preferences
Raka Jovanovic (17947838)
Mathematical sciences
Applied mathematics
demand response
mixed integer linear programming
scheduling
smart grids
status_str publishedVersion
title Residential Demand Response Scheduling with Consideration of Consumer Preferences
title_full Residential Demand Response Scheduling with Consideration of Consumer Preferences
title_fullStr Residential Demand Response Scheduling with Consideration of Consumer Preferences
title_full_unstemmed Residential Demand Response Scheduling with Consideration of Consumer Preferences
title_short Residential Demand Response Scheduling with Consideration of Consumer Preferences
title_sort Residential Demand Response Scheduling with Consideration of Consumer Preferences
topic Mathematical sciences
Applied mathematics
demand response
mixed integer linear programming
scheduling
smart grids