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Configurations of model predictive control to exploit energy flexibility in building thermal loads

Author
Péan, T.; Salom, J.; Costa-Castelló, R.
Type of activity
Presentation of work at congresses
Name of edition
57th IEEE Conference on Decision and Control
Date of publication
2018
Presentation's date
2018
Book of congress proceedings
2018 IEEE Conference on Decision and Control (CDC)
First page
3177
Last page
3182
Publisher
IEEE Press
DOI
https://doi.org/10.1109/CDC.2018.8619452 Open in new window
Project funding
Innovative controls for renewable sources Integration into smart energy systems
Repository
http://hdl.handle.net/2117/127600 Open in new window
URL
https://ieeexplore.ieee.org/document/8619452 Open in new window
Abstract
A model predictive control (MPC) framework is developed in the present study, with the final objective to improve the energy flexibility of building thermal loads through demand-side management. Three different configurations are tested and tuned, with the following objective functions: minimizing the delivered energy to the building, the electrical energy used by the HVAC system (heat pump) or the cost of this electricity use. To validate these MPC configurations, a Matlab-Trnsys co-simulator i...
Citation
Péan, T.; Salom, J.; Costa-Castelló, R. Configurations of model predictive control to exploit energy flexibility in building thermal loads. A: IEEE Conference on Decision and Control. "2018 IEEE Conference on Decision and Control (CDC)". IEEE Press, 2018, p. 3177-3182.
Keywords
control theory, optimal control
Group of research
CS2AC-UPC - Supervision, Safety and Automatic Control
SAC - Advanced Control Systems

Participants

  • Péan, Thibaut  (author and speaker )
  • Salom Tormo, Jaume  (author and speaker )
  • Costa Castelló, Ramon  (author and speaker )