Concordia University, Department of Building, Civil and Environmental Engineering, 1455 De Maisonneuve Blvd. W, Montreal, Quebec, Canada; CanmetENERGY in Varennes, Energy Efficiency and Technology Sector, 1615 Lionel-Boulet Blvd.,Varennes, QC J3 × 1S6, Canada
Anna-Maria Sigounis
Concordia University, Department of Building, Civil and Environmental Engineering, 1455 De Maisonneuve Blvd. W, Montreal, Quebec, Canada
Anand Krishnan Prakash
Lawrence Berkeley National Laboratory, Building Technology and Urban Systems, 1 Cyclotron Road, Berkeley, California 94720, United States
Marco Pritoni
Lawrence Berkeley National Laboratory, Building Technology and Urban Systems, 1 Cyclotron Road, Berkeley, California 94720, United States
Jessica Granderson
Lawrence Berkeley National Laboratory, Building Technology and Urban Systems, 1 Cyclotron Road, Berkeley, California 94720, United States
Shiyu Yang
Nanyang Technological University, School of Mechanical and Aerospace Engineering, 639798, Singapore; Cornell University, Systems Engineering, Ithaca, NY, USA, 14853
Man Pun Wan
Nanyang Technological University, School of Mechanical and Aerospace Engineering, 639798, Singapore
The data presented here were collected independently for 6 real buildings by researchers of different institutions and gathered in the context of the IEA EBC Annex 81 Data-driven Smart Buildings, as a joint effort to compile a diverse range of datasets suitable for advanced control applications of indoor climate and energy use in buildings. The data were acquired by energy meters, both consumption and PV generation, and sensors of technical installation and indoor climate variables, such as temperature, flow rate, relative humidity, CO2 level, illuminance. Weather variables were either acquired by local sensors or obtained from a close by meteorological station. The data were collected either during normal operation of the building, with observation periods between 2 weeks and 2 months, or during experiments designed to excite the thermal mass of the building, with observation periods of approximately one week. The data have a time resolution varying between 1 min and 15 min; in some case the highest resolution data are also averaged at larger intervals, up to 30 min.
