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Title: Model Predictive Control-Based Hierarchical Control of a Multi-Zone Commercial HVAC System
Abstract This paper presents a novel architecture for model predictive control (MPC)-based indoor climate control of multi-zone buildings to provide energy efficiency. Unlike prior works, we do not assume the availability of a high-resolution multi-zone building model, which is challenging to obtain. Instead, the architecture uses a low-resolution model of the building that is divided into a small number of “meta-zones” that can be easily identified using existing data-driven modeling techniques. The proposed architecture is hierarchical. At the higher level, an MPC controller uses the low-resolution model to make decisions for the air handling unit (AHU) and the meta-zones. Since the meta-zones are fictitious, a lower level controller converts the high-level MPC decisions into commands for the individual zones by solving a projection problem that strikes a trade-off between two potentially conflicting goals: the AHU-level decisions made by the MPC are respected while the climate of the individual zones is maintained within the comfort bounds. The performance of the proposed controller is assessed via simulations in a high-fidelity simulation testbed and compared to that of a rule-based controller that is used in practice. Simulations in multiple weather conditions show the effectiveness of the proposed controller in terms of energy savings, climate control, and computational tractability.  more » « less
Award ID(s):
1934322
PAR ID:
10280372
Author(s) / Creator(s):
; ; ;
Date Published:
Journal Name:
ASME Journal of Engineering for Sustainable Buildings and Cities
Volume:
2
Issue:
2
ISSN:
2642-6641
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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