Please use this identifier to cite or link to this item:
Title: A state-space thermal model incorporating humidity and thermal comfort for model predictive control in buildings
Authors: Yang, Shiyu
Wan, Man Pun
Ng, Bing Feng
Zhang, Tian
Babu, Sushanth
Zhang, Zhe
Chen, Wanyu
Dubey, Swapnil
Keywords: Model Predictive Control
State-space Model
DRNTU::Engineering::Mechanical engineering
Issue Date: 2018
Source: Yang, S., Wan, M. P., Ng, B. F., Zhang, T., Babu, S., Zhang, Z., . . . Dubey, S. (2018). A state-space thermal model incorporating humidity and thermal comfort for model predictive control in buildings. Energy and Buildings, 170, 25-39. doi:10.1016/j.enbuild.2018.03.082
Series/Report no.: Energy and Buildings
Abstract: A major challenge in applying Model Predictive Control (MPC) to building automation and control (BAC) is the development of a simplified mathematical model of the building for real-time control with fast response times. However, building models are highly complex due to nonlinearities in heat and mass transfer processes of the building itself and the accompanying air-conditioning and mechanical ventilation systems. This paper proposes a method to develop an integrated state-space model (SSM) for indoor air temperature, radiant temperature, humidity and Predicted Mean Vote (PMV) index suitable for fast real-time multiple objectives optimization. Using the model, a multi-objective MPC controller is developed and its performance is evaluated through a case study on the BCA SkyLab test bed facility in Singapore. The runtime of the MPC controller is less than 0.1 s per optimization, which is suitable for real-time BAC applications. Compared to the conventional ON/OFF control, the MPC controller can achieve up to 19.4% energy savings while keeping the PMV index within the acceptable comfort range. When the MPC controller is adjusted to be thermal-comfort-dominant that achieves a neutral PMV index at most office hours, the system can still bring about 6% in energy savings as compared to the conventional ON/OFF control.
ISSN: 0378-7788
DOI: 10.1016/j.enbuild.2018.03.082
Rights: © 2018 Elsevier B.V. All rights reserved. This paper was published in Energy and Buildings and is made available with permission of Elsevier B.V.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:ERI@N Journal Articles
MAE Journal Articles

Google ScholarTM



Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.