TY - JOUR
T1 - High resolution dataset from a net-zero home that demonstrates zero-carbon living and transportation capacity
AU - Cui, Borui
AU - Lee, Sangkeun
AU - Im, Piljae
AU - Koenig, Michael
AU - Bhandari, Mahabir
N1 - Publisher Copyright:
© 2022 The Authors
PY - 2022/12
Y1 - 2022/12
N2 - 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.
AB - 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.
KW - Electrification
KW - Energy Efficiency
KW - Ground Source Heat Pump
KW - Net-zero home
KW - Renewable Energy
KW - Smart Home
KW - Sustainable Home
UR - http://www.scopus.com/inward/record.url?scp=85141312899&partnerID=8YFLogxK
U2 - 10.1016/j.dib.2022.108703
DO - 10.1016/j.dib.2022.108703
M3 - Article
AN - SCOPUS:85141312899
SN - 2352-3409
VL - 45
JO - Data in Brief
JF - Data in Brief
M1 - 108703
ER -