US 12,392,520 B2
HVAC control system and method
Shang Hsin Julian Lee, Hong Kong (CN); and Martin Raphael Pierre Noel Boissier, Hong Kong (CN)
Assigned to Ambi Labs Limited, Hong Kong (CN)
Appl. No. 17/767,609
Filed by Ambi Labs Limited, Hong Kong (CN)
PCT Filed Oct. 9, 2020, PCT No. PCT/CN2020/119923
§ 371(c)(1), (2) Date Apr. 8, 2022,
PCT Pub. No. WO2021/068882, PCT Pub. Date Apr. 15, 2021.
Claims priority of application No. 19130534.1 (HK), filed on Oct. 8, 2019.
Prior Publication US 2023/0134772 A1, May 4, 2023
Int. Cl. F24F 11/63 (2018.01); F24F 11/50 (2018.01); F24F 11/56 (2018.01); F24F 110/10 (2018.01); F24F 110/20 (2018.01); F24F 120/20 (2018.01); F24F 140/60 (2018.01); G05B 19/042 (2006.01); F24F 120/10 (2018.01); F24F 130/20 (2018.01); F24F 130/30 (2018.01)
CPC F24F 11/63 (2018.01) [F24F 11/50 (2018.01); F24F 11/56 (2018.01); G05B 19/042 (2013.01); F24F 2110/10 (2018.01); F24F 2110/20 (2018.01); F24F 2120/10 (2018.01); F24F 2120/20 (2018.01); F24F 2130/20 (2018.01); F24F 2130/30 (2018.01); F24F 2140/60 (2018.01); G05B 2219/2614 (2013.01)] 16 Claims
OG exemplary drawing
 
1. A HVAC control system comprising:
at least one user interface adapted to receive comfort feedback from a plurality of users; and
a processor adapted to receive the comfort feedback and input data corresponding to one or more comfort factors and respective values of the comfort factors, the processor adapted to build a respective comfort model for each respective user based on both the comfort feedback and the input data in respect of the respective user, the respective comfort model correlating a respective comfort score for the respective user to one or more values of one or more of the comfort factors affecting the respective user, and the processor adjusting one or more functions of one or more HVAC units to vary one or more of the comfort factors such that a respective predetermined comfort score for each respective user is achieved;
wherein the processor is adapted to receive a power abatement instruction from a power utility, the processor adjusting one or more functions of one or more of the HVAC units to vary one or more comfort factors such that one or more of the predetermined comfort scores is achieved while complying with the power abatement instruction, wherein the power abatement instruction corresponds to a total power abatement value across a plurality of the HVAC units, and the power abatement instruction for each user of the plurality of users is complied with when the total power abatement value is achieved, and wherein one or more of the comfort models is a machine learning regression model.