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High resolution dataset from a net-zero home that demonstrates zero-carbon living and transportation capacity

This dataset includes high resolution, detailed end use data from a net-zero occupied home that demonstrates zero-carbon living and transportation capacity. The house is located in Davis, California, U.S., and the dataset includes full year data from 2020 with 1 minute time resolution. The data has...

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Autores principales: Cui, Borui, Lee, Sangkeun, Im, Piljae, Koenig, Michael, Bhandari, Mahabir
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9679727/
https://www.ncbi.nlm.nih.gov/pubmed/36425985
http://dx.doi.org/10.1016/j.dib.2022.108703
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author Cui, Borui
Lee, Sangkeun
Im, Piljae
Koenig, Michael
Bhandari, Mahabir
author_facet Cui, Borui
Lee, Sangkeun
Im, Piljae
Koenig, Michael
Bhandari, Mahabir
author_sort Cui, Borui
collection PubMed
description This dataset includes high resolution, detailed end use data from a net-zero occupied home that demonstrates zero-carbon living and transportation capacity. The house is located in Davis, California, U.S., and the dataset includes full year data from 2020 with 1 minute time resolution. The data has been monitored with more than 230 sensors installed in the house, and there are total 332 channels available. The data includes detailed end use electricity data (e.g., HVAC system, lighting, plug load including major appliances), building's interior thermal conditions (e.g., indoor air temperatures in multiple rooms and relative humidity), HVAC system operation data (e.g., soil temperatures around ground bores and supply water temperatures), on-site power generation system data (e.g., PV power supply and PV surface temperatures) and etc. The original dataset from the house has been curated, and the data has been carefully reviewed for quality check. The data quality check revealed there are 156 minutes of data were missing in the month of April, and around 1,404 minutes of data was missing in August. The data gap was filled with linear interpolation in case the gap is less than continuous 6 hours. Otherwise, the data is filled with -9999. The data curation has been processed using the Tsdat framework (https://github.com/tsdat/tsdat). In addition, a semantic description for the dataset was generated by leveraging the Brick (https://brickschema.org/). The final curated and processed data as well as raw data are currently available through https://bbd.labworks.org/ds/bbd/hshus.
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spelling pubmed-96797272022-11-23 High resolution dataset from a net-zero home that demonstrates zero-carbon living and transportation capacity Cui, Borui Lee, Sangkeun Im, Piljae Koenig, Michael Bhandari, Mahabir Data Brief Data Article This dataset includes high resolution, detailed end use data from a net-zero occupied home that demonstrates zero-carbon living and transportation capacity. The house is located in Davis, California, U.S., and the dataset includes full year data from 2020 with 1 minute time resolution. The data has been monitored with more than 230 sensors installed in the house, and there are total 332 channels available. The data includes detailed end use electricity data (e.g., HVAC system, lighting, plug load including major appliances), building's interior thermal conditions (e.g., indoor air temperatures in multiple rooms and relative humidity), HVAC system operation data (e.g., soil temperatures around ground bores and supply water temperatures), on-site power generation system data (e.g., PV power supply and PV surface temperatures) and etc. The original dataset from the house has been curated, and the data has been carefully reviewed for quality check. The data quality check revealed there are 156 minutes of data were missing in the month of April, and around 1,404 minutes of data was missing in August. The data gap was filled with linear interpolation in case the gap is less than continuous 6 hours. Otherwise, the data is filled with -9999. The data curation has been processed using the Tsdat framework (https://github.com/tsdat/tsdat). In addition, a semantic description for the dataset was generated by leveraging the Brick (https://brickschema.org/). The final curated and processed data as well as raw data are currently available through https://bbd.labworks.org/ds/bbd/hshus. Elsevier 2022-10-26 /pmc/articles/PMC9679727/ /pubmed/36425985 http://dx.doi.org/10.1016/j.dib.2022.108703 Text en © 2022 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Data Article
Cui, Borui
Lee, Sangkeun
Im, Piljae
Koenig, Michael
Bhandari, Mahabir
High resolution dataset from a net-zero home that demonstrates zero-carbon living and transportation capacity
title High resolution dataset from a net-zero home that demonstrates zero-carbon living and transportation capacity
title_full High resolution dataset from a net-zero home that demonstrates zero-carbon living and transportation capacity
title_fullStr High resolution dataset from a net-zero home that demonstrates zero-carbon living and transportation capacity
title_full_unstemmed High resolution dataset from a net-zero home that demonstrates zero-carbon living and transportation capacity
title_short High resolution dataset from a net-zero home that demonstrates zero-carbon living and transportation capacity
title_sort high resolution dataset from a net-zero home that demonstrates zero-carbon living and transportation capacity
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9679727/
https://www.ncbi.nlm.nih.gov/pubmed/36425985
http://dx.doi.org/10.1016/j.dib.2022.108703
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