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Humans in the loop: a stochastic predictive approach to building energy management in the presence of unpredictable users
Publikationstyp
Journal Article
Date Issued
2017-07
Sprache
English
Journal
Volume
50
Issue
1
Start Page
14471
End Page
14476
Citation
IFAC-PapersOnLine 50 (1): 14471-14476 (2017-07)
Contribution to Conference
Publisher DOI
Scopus ID
Publisher
Elsevier
Efficient building energy management has attracted a great deal of academic interest with significant potential energy savings to be envisaged. Social scientists strive to achieve these savings by employing behavior-based approaches, while engineers investigate control strategies for the efficient operation of the building devices. This work can be seen as a first step towards bridging these two approaches by proposing a control scheme that encapsulates building occupant behavior into the energy management system. In particular, the occupants willingness to tolerate comfort bound violations is modeled as a random measurable uncertainty and incorporated into the building energy management system through disturbance feedback control policies. The respective optimal control problem is formulated as a mixed-integer stochastic optimization problem, and a computationally tractable approximation of it is derived by restricting the disturbance feedback control policies to admit an affine structure. An extensive numerical study verifies that the proposed approach can significantly reduce the energy consumption of the buildings.
Subjects
building automation
computational social sciences
convex optimization
humans-in-the-loop
predictive control
robust control
DDC Class
004: Informatik
More Funding Information
This project is supported by the ETH Zurich Foundation, the Swiss Competence Centers for Energy Research under the project
FEEB&D and NanoTera.ch under the project HeatReserves.
FEEB&D and NanoTera.ch under the project HeatReserves.