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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2018
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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. |
format | Online Article Text |
id | pubmed-5988454 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
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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