Machine learning for energy consumption optimization in HVAC systems

This project aims to optimise energy consumption in Heating, Ventilation and Air Conditioning systems modifying their working schedules. Taking advantage of a machine learning algorithm I have developed (based on Python), schedules can be daily updated depending on multiple variables and guaranteein...

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Detalles Bibliográficos
Autor: Palat Pañella, Joan
Tipo de recurso: tesis de maestría
Fecha de publicación:2018
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/128008
Acceso en línea:https://hdl.handle.net/2117/128008
Access Level:acceso abierto
Palabra clave:Air conditioning
Ventilation
Aire condicionat
Ventilació
Àrees temàtiques de la UPC::Informàtica::Automàtica i control
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spelling Machine learning for energy consumption optimization in HVAC systemsPalat Pañella, JoanAir conditioningVentilationAire condicionatVentilacióÀrees temàtiques de la UPC::Informàtica::Automàtica i controlThis project aims to optimise energy consumption in Heating, Ventilation and Air Conditioning systems modifying their working schedules. Taking advantage of a machine learning algorithm I have developed (based on Python), schedules can be daily updated depending on multiple variables and guaranteeing comfort. To facilitate the interaction with the algorithm, I have also created a simple website to introduce the data required and to display the results. The project has been developed in Montrol Open Solutions, SL.Universitat Politècnica de CatalunyaAngulo Bahón, Cecilio20182018-06-2120192019-01-31master thesishttp://purl.org/coar/resource_type/c_bdccNAhttp://purl.org/coar/version/c_be7fb7dd8ff6fe43info:eu-repo/semantics/masterThesisapplication/pdfapplication/ziphttps://hdl.handle.net/2117/128008reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2http://creativecommons.org/licenses/by-nc-nd/3.0/es/info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/1280082026-05-27T15:37:01Z
dc.title.none.fl_str_mv Machine learning for energy consumption optimization in HVAC systems
title Machine learning for energy consumption optimization in HVAC systems
spellingShingle Machine learning for energy consumption optimization in HVAC systems
Palat Pañella, Joan
Air conditioning
Ventilation
Aire condicionat
Ventilació
Àrees temàtiques de la UPC::Informàtica::Automàtica i control
title_short Machine learning for energy consumption optimization in HVAC systems
title_full Machine learning for energy consumption optimization in HVAC systems
title_fullStr Machine learning for energy consumption optimization in HVAC systems
title_full_unstemmed Machine learning for energy consumption optimization in HVAC systems
title_sort Machine learning for energy consumption optimization in HVAC systems
dc.creator.none.fl_str_mv Palat Pañella, Joan
author Palat Pañella, Joan
author_facet Palat Pañella, Joan
author_role author
dc.contributor.none.fl_str_mv Angulo Bahón, Cecilio
dc.subject.none.fl_str_mv Air conditioning
Ventilation
Aire condicionat
Ventilació
Àrees temàtiques de la UPC::Informàtica::Automàtica i control
topic Air conditioning
Ventilation
Aire condicionat
Ventilació
Àrees temàtiques de la UPC::Informàtica::Automàtica i control
description This project aims to optimise energy consumption in Heating, Ventilation and Air Conditioning systems modifying their working schedules. Taking advantage of a machine learning algorithm I have developed (based on Python), schedules can be daily updated depending on multiple variables and guaranteeing comfort. To facilitate the interaction with the algorithm, I have also created a simple website to introduce the data required and to display the results. The project has been developed in Montrol Open Solutions, SL.
publishDate 2018
dc.date.none.fl_str_mv 2018
2018-06-21
2019
2019-01-31
dc.type.none.fl_str_mv master thesis
http://purl.org/coar/resource_type/c_bdcc
NA
http://purl.org/coar/version/c_be7fb7dd8ff6fe43
dc.type.openaire.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/128008
url https://hdl.handle.net/2117/128008
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2

http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2

http://creativecommons.org/licenses/by-nc-nd/3.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/zip
dc.publisher.none.fl_str_mv Universitat Politècnica de Catalunya
publisher.none.fl_str_mv Universitat Politècnica de Catalunya
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,301603

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