HVAC control fine-grained occupancy pattern estimation
Abstract
A thermal state of a plurality of zones of the building is updated according to a building thermal model and information received from temperature sensors of the building. Predicted occupant counts for an upcoming plurality of time slots for each of the plurality of zones are updated using actual occupancy counts for each of the plurality of zones. A misprediction type distribution for the upcoming plurality of time slots for each of the plurality of zones is updated, the misprediction type distribution indicating misprediction for true negatives, false positives, false negatives, and true positives. A total misprediction cost expectation is updated according to the predicted occupant counts and the misprediction type distribution. HVAC power for each of the plurality of zones is determined to optimize occupant thermal comfort weighted according to the predicted occupant counts while minimizing the total misprediction cost expectation. HVAC operation is controlled per the HVAC power.
- Inventors:
- Issue Date:
- Research Org.:
- Robert Bosch GmbH, Stuttgart (Germany)
- Sponsoring Org.:
- USDOE; National Science Foundation (NSF)
- OSTI Identifier:
- 2222075
- Patent Number(s):
- 11719458
- Application Number:
- 16/850,860
- Assignee:
- Robert Bosch GmbH (Stuttgart, DE)
- DOE Contract Number:
- EE0007682; CNS-1553273
- Resource Type:
- Patent
- Resource Relation:
- Patent File Date: 04/16/2020
- Country of Publication:
- United States
- Language:
- English
Citation Formats
Lin, Shan, and Munir, Sirajum. HVAC control fine-grained occupancy pattern estimation. United States: N. p., 2023.
Web.
Lin, Shan, & Munir, Sirajum. HVAC control fine-grained occupancy pattern estimation. United States.
Lin, Shan, and Munir, Sirajum. Tue .
"HVAC control fine-grained occupancy pattern estimation". United States. https://www.osti.gov/servlets/purl/2222075.
@article{osti_2222075,
title = {HVAC control fine-grained occupancy pattern estimation},
author = {Lin, Shan and Munir, Sirajum},
abstractNote = {A thermal state of a plurality of zones of the building is updated according to a building thermal model and information received from temperature sensors of the building. Predicted occupant counts for an upcoming plurality of time slots for each of the plurality of zones are updated using actual occupancy counts for each of the plurality of zones. A misprediction type distribution for the upcoming plurality of time slots for each of the plurality of zones is updated, the misprediction type distribution indicating misprediction for true negatives, false positives, false negatives, and true positives. A total misprediction cost expectation is updated according to the predicted occupant counts and the misprediction type distribution. HVAC power for each of the plurality of zones is determined to optimize occupant thermal comfort weighted according to the predicted occupant counts while minimizing the total misprediction cost expectation. HVAC operation is controlled per the HVAC power.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2023},
month = {8}
}
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