Experimental Demonstration of Frequency Regulation by Commercial Buildings - Part I: Modeling and Hierarchical Control Design
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Abstract (arXiv)
This paper is the first part of a two-part series in which we present results from an experimental demonstration of frequency regulation in a commercial building test facility. In Part I, we introduce the test facility and develop relevant building models. Furthermore, we design a hierarchical controller that consists of three levels: a reserve scheduler, a building climate controller, and a fan speed controller for frequency regulation. We formulate the reserve scheduler as a robust optimization problem and introduce several approximations to reduce its complexity. The building climate controller is comprised of a robust model predictive controller and a Kalman filter. The frequency regulation controller consists of a feedback and a feedforward loop, provides fast responses, and is stable. Part I presents building model identification and controller tuning results, whereas Part II reports results from the operation of the hierarchical controller under frequency regulation.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 19 May 2016.
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Citing papers per year: 2021: 1; 2022: 1; 2023: 2.
4 papers.
- 2021Physics Informed Neural Networks for Control Oriented Thermal Modeling of Buildingscited by 24
- 2023A Survey on Physics Informed Reinforcement Learning: Review and Open Problemscited by 24
- 2023Demand response for residential building heating: Effective Monte Carlo Tree Search control based on physics-informed neural networkscited by 4
- 2022Uncertainty-Cognizant Model Predictive Control for Energy Management of Residential Buildings with PVT and Thermal Energy Storagecited by 0
- 2023Demand response for residential building heating: Effective Monte Carlo Tree Search control based on physics-informed neural networks6 Dec 2023
- 2023A Survey on Physics Informed Reinforcement Learning: Review and Open Problems5 Sep 2023
- 2022Uncertainty-Cognizant Model Predictive Control for Energy Management of Residential Buildings with PVT and Thermal Energy Storage21 Jan 2022
- 2021Physics Informed Neural Networks for Control Oriented Thermal Modeling of Buildings23 Nov 2021