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Identifying services for short-term load forecasting using data driven models in a Smart City platform

The paper describes an ongoing work to embed several services in a Smart City architecture with the aim of achieving a sustainable city. In particular, the main goal is to identify services required in such framework to define the requirements and features of a reference architecture to support the data-driven methods for energy efficiency monitoring or load prediction. With this object in mind, a use case of short-term load forecasting in non-residential buildings in the University of Girona is provided, in order to practically explain the services embedded in the described general layers architecture. In the work, classic data-driven models for load forecasting in buildings are used as an example

This research project has been partially funded through BR-UdGScholarship of the University of Girona granted to Joaquim MassanaRaurich. Work developed with the support of the research groupSITES awarded with distinction by the Generalitat de Catalunya(SGR 2014–2016), the MESC project funded by the Spanish MINECO (Ref. DPI2013-47450-C2-1-R) and the European Union’s Horizon2020 Research and Innovation Programme under grant agreementNo 680708

© Sustainable Cities and Society, 2017, vol. 28, p. 108-117

Elsevier

Manager: Ministerio de Economía y Competitividad (Espanya)
Author: Massana i Raurich, Joaquim
Pous i Sabadí, Carles
Burgas Nadal, Llorenç
Meléndez i Frigola, Joaquim
Colomer Llinàs, Joan
Abstract: The paper describes an ongoing work to embed several services in a Smart City architecture with the aim of achieving a sustainable city. In particular, the main goal is to identify services required in such framework to define the requirements and features of a reference architecture to support the data-driven methods for energy efficiency monitoring or load prediction. With this object in mind, a use case of short-term load forecasting in non-residential buildings in the University of Girona is provided, in order to practically explain the services embedded in the described general layers architecture. In the work, classic data-driven models for load forecasting in buildings are used as an example
This research project has been partially funded through BR-UdGScholarship of the University of Girona granted to Joaquim MassanaRaurich. Work developed with the support of the research groupSITES awarded with distinction by the Generalitat de Catalunya(SGR 2014–2016), the MESC project funded by the Spanish MINECO (Ref. DPI2013-47450-C2-1-R) and the European Union’s Horizon2020 Research and Innovation Programme under grant agreementNo 680708
Format: application/pdf
Citation: 025833
ISSN: 2210-6707
Document access: http://hdl.handle.net/10256/13412
Language: eng
Publisher: Elsevier
Collection: MINECO/PE 2014-2016/DPI2013-47450-C2-1-R
Versió postprint del document publicat a: http://dx.doi.org/10.1016/j.scs.2016.09.001
Articles publicats (D-EEEiA)
info:eu-repo/grantAgreement/EC/H2020/680708
Is part of: © Sustainable Cities and Society, 2017, vol. 28, p. 108-117
Rights: Tots els drets reservats
Subject: Arquitectura sostenible
Sustainable architecture
Ciutats digitals (Xarxes d’ordinadors)
Electronic villages (Computer networks)
Energia elèctrica -- Consum
Electric power consumption
Title: Identifying services for short-term load forecasting using data driven models in a Smart City platform
Type: info:eu-repo/semantics/article
Repository: DUGiDocs

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