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dc.contributor.author
Nesmachnow, Sergio
dc.contributor.author
Rossit, Diego Gabriel
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Toutouh, Jamal
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Luna, Francisco
dc.date.available
2021-08-13T18:45:12Z
dc.date.issued
2021-05-12
dc.identifier.citation
Nesmachnow, Sergio; Rossit, Diego Gabriel; Toutouh, Jamal; Luna, Francisco; An explicit evolutionary approach for multiobjective energy consumption planning considering user preferences in smart homes; Growing Science; International Journal of Industrial Engineering Computations; 12; 4; 12-5-2021; 365-380
dc.identifier.issn
1923-2926
dc.identifier.uri
http://hdl.handle.net/11336/138290
dc.description.abstract
Modern Smart Cities are highly dependent on an efficient energy service since electricity is used in an increasing number of urban activities. In this regard, Time-of-Use prices for electricity is a widely implemented policy that has been successful to balance electricity consumption along the day and, thus, diminish the stress and risk of shortcuts of electric grids in peak hours. Indeed, residential customers may now schedule the use of deferrable electrical appliances in their smart homes in off-peak hours to reduce the electricity bill. In this context, this work aims to develop an automatic planning tool that accounts for minimizing the electricity costs and enhancing user satisfaction, allowing them to make more efficient usage of the energy consumed. The household energy consumption planning problem is addressed with a multiobjective evolutionary algorithm, for which problem-specific operators are devised, and a set of state-of-the-art greedy algorithms aim to optimize different criteria. The proposed resolution algorithms are tested over a set of realistic instances built using real-world energy consumption data, Time-of-Use prices from an electricity company, and user preferences estimated from historical information and sensor data. The results show that the evolutionary algorithm is able to improve upon the greedy algorithms both in terms of the electricity costs and user satisfaction and largely outperforms to a large extent the current strategy without planning implemented by users.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Growing Science
dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
SMART CITIES
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ENERGY CONSUMPTION PLANNING PROBLEM
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USER PREFERENCES
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MULTIOBJECTIVE OPTIMIZATION
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EVOLUTIONARY ALGORITHM
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GREEDY ALGORITHMS
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Otras Ingenierías y Tecnologías
dc.subject.classification
Otras Ingenierías y Tecnologías
dc.subject.classification
INGENIERÍAS Y TECNOLOGÍAS
dc.title
An explicit evolutionary approach for multiobjective energy consumption planning considering user preferences in smart homes
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2021-07-21T16:51:56Z
dc.identifier.eissn
1923-2934
dc.journal.volume
12
dc.journal.number
4
dc.journal.pagination
365-380
dc.journal.pais
Canadá
dc.description.fil
Fil: Nesmachnow, Sergio. Facultad de Ingeniería; Uruguay
dc.description.fil
Fil: Rossit, Diego Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería; Argentina
dc.description.fil
Fil: Toutouh, Jamal. Massachusetts Institute of Technology. Science And Artificial Intelligence Laboratory; Estados Unidos
dc.description.fil
Fil: Luna, Francisco. Universidad de Málaga.
Instituto de Tecnologías e Ingeniería del Software; España
dc.journal.title
International Journal of Industrial Engineering Computations
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/http://growingscience.com/beta/ijiec/4893-an-explicit-evolutionary-approach-for-multiobjective-energy-consumption-planning-considering-user-preferences-in-smart-homes.html
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.5267/j.ijiec.2021.5.005
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/http://www.growingscience.com/ijiec/Vol12/IJIEC_2021_15.pdf
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