Data-driven Energy Flexibility KPIs
This is the official repository prepared for the review article, entitled “Data-Driven Key Performance Indicators and Datasets for Building Energy Flexibility: A Review and Perspectives”
Appendices
Appendix A
The details of the reviewed articles and KPIs in the paper’s Appendix can be found in this Google sheet:
The Jupyter Notebook that analyzes the reviewed articles and KPIs can be found here.
Appendix B
The complete list of the 16 identified available datasets of buildings performing DR with detailed information about their respective study and a link to download the datasets when the latter are available can be found in this Google sheet.
The Jupyter Notebook that analyzes the collected datasets can be found here.
Acknowledgements
This work has been carried out within the framework of International Energy Agency (IEA) Energy in Buildings and Communities (EBC) Annex 81: “Data-Driven Smart Buildings” (https://annex81.iea-ebc.org/). The authors would like to gratefully acknowledge the IEA EBC Annex 81 for providing an excellent research network and thus enabling fruitful collaborative research studies like the present one.
- Lawrence Berkeley National Laboratory’s (LBNL) effort was supported by the Assistant Secretary for Energy Efficiency and Renewable Energy, Building Technologies Office, of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231.
- University College Dublin’s (UCD) and CARTIF’s effort was supported by: (a) the CBIM-ETN funded by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 860555 and, (b) the NeXSyS project under the auspices of Science Foundation Ireland (SFI) Grant 21/SPP/3756.
- Texas A&M University’s (TAMU) effort was supported by: 1) NSF project # 2050509 “PFI-RP: Data-Driven Services for High Performance and Sustainable Buildings.” and 2) the Building Technologies Office at the U.S. Department of Energy through the Emerging Technologies program under award number DE-EE0009150.
- Syracuse University’s (SU) effort was supported by the U.S. National Science Foundation (Award No. 1949372).
- Aalborg University’s (AAU, Denmark) effort was supported by the IEA-EBC Annex 81 Participation project funded by The Energy Technology Development and Demonstration Programme - EUDP (Case no. 64019-0539).
- DEWA R&D Center’s effort was supported and funded by the Dubai Electricity and Water Authority.
- Concordia University’s effort was supported by funding from the Canada Excellence Research Chairs Program and the Tri-Agency Institutional Program Secretariat (Grant CERC-2018-00005), the Natural Sciences and Engineering Research Council of Canada (Discover Grant RGPIN 2020-06804), and the Fonds de recherche du Québec: Nature et technologies (FRQNT) Doctoral Research Scholarship.
Contact
If you have general questions, please reach out to Hicham Johra.