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High-resolution dataset for building energy management systems applications

Modelling and optimization of energy management systems (EMS) require different data types for operation and validation. In this article, a multi-purpose dataset is provided for EMS applications. It includes PV measurement data for the PV generation and prediction algorithms associated with EMS syst...

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Detalles Bibliográficos
Autores principales: El-Baz, Wessam, Honold, Johannes, Hardi, Lukas, Tzscheutschler, Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5988454/
https://www.ncbi.nlm.nih.gov/pubmed/29876380
http://dx.doi.org/10.1016/j.dib.2017.12.058
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author El-Baz, Wessam
Honold, Johannes
Hardi, Lukas
Tzscheutschler, Peter
author_facet El-Baz, Wessam
Honold, Johannes
Hardi, Lukas
Tzscheutschler, Peter
author_sort El-Baz, Wessam
collection PubMed
description Modelling and optimization of energy management systems (EMS) require different data types for operation and validation. In this article, a multi-purpose dataset is provided for EMS applications. It includes PV measurement data for the PV generation and prediction algorithms associated with EMS systems. Weather data has also been measured at the same location for the optimization of PV prediction algorithms and other applications such as building model simulations. Moreover, the dataset contains detailed measurements of a seminar room where not only temperatures have been measured, but also user feedback for comfort assessment. All documented measurements have been gathered at the same location in Munich, Germany.
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spelling pubmed-59884542018-06-06 High-resolution dataset for building energy management systems applications El-Baz, Wessam Honold, Johannes Hardi, Lukas Tzscheutschler, Peter Data Brief Energy Modelling and optimization of energy management systems (EMS) require different data types for operation and validation. In this article, a multi-purpose dataset is provided for EMS applications. It includes PV measurement data for the PV generation and prediction algorithms associated with EMS systems. Weather data has also been measured at the same location for the optimization of PV prediction algorithms and other applications such as building model simulations. Moreover, the dataset contains detailed measurements of a seminar room where not only temperatures have been measured, but also user feedback for comfort assessment. All documented measurements have been gathered at the same location in Munich, Germany. Elsevier 2018-01-03 /pmc/articles/PMC5988454/ /pubmed/29876380 http://dx.doi.org/10.1016/j.dib.2017.12.058 Text en © 2018 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Energy
El-Baz, Wessam
Honold, Johannes
Hardi, Lukas
Tzscheutschler, Peter
High-resolution dataset for building energy management systems applications
title High-resolution dataset for building energy management systems applications
title_full High-resolution dataset for building energy management systems applications
title_fullStr High-resolution dataset for building energy management systems applications
title_full_unstemmed High-resolution dataset for building energy management systems applications
title_short High-resolution dataset for building energy management systems applications
title_sort high-resolution dataset for building energy management systems applications
topic Energy
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5988454/
https://www.ncbi.nlm.nih.gov/pubmed/29876380
http://dx.doi.org/10.1016/j.dib.2017.12.058
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