Abstract
In a central heating, ventilation, and air conditioning (HVAC) system, the set-points for several local control loops have a significant influence on the overall energy performance of the system. Real-time optimization (RtOpt) of those set-points has therefore been widely studied. However, due to the nonlinear dynamics of the HVAC system as well as the constraints associated with the system operation, real-time optimization always suffers from a heavy on-line computational load when those set-points are optimized simultaneously. To overcome this problem, multiplexed real-time optimization (MRtOpt) has been developed, which optimizes only one set-point at a time but with a faster optimization frequency. Because frequently resetting the set-points introduces artificial disturbances into the local control loops and may deteriorate the system stability, this paper presents a study to enhance the system stability of the multiplexed real-time optimization by integrating a degree of freedom (DOF) based set-point reset to renew the set-points instead of the conventional step-change set-point reset. The control performance of the integrated strategy was investigated using case studies. The results showed that around 10% of the energy saving was achieved by the proposed method compared with a method without real-time optimization. When compared with the conventional real-time optimization method, the proposed method resulted in around 70% computational load reduction, and over 26% reduction in the tracking errors of the local control loops.
| Original language | English |
|---|---|
| Pages (from-to) | 640-651 |
| Journal | Applied Energy |
| Volume | 187 |
| Online published | 2 Dec 2016 |
| DOIs | |
| Publication status | Published - 1 Feb 2017 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Research Keywords
- Air conditioning
- Building energy efficiency
- Control stability
- Degree of freedom based set-point reset
- Heating
- Real-time optimization
- Ventilation
RGC Funding Information
- RGC-funded
Fingerprint
Dive into the research topics of 'Multiplexed real-time optimization of HVAC systems with enhanced control stability'. Together they form a unique fingerprint.Projects
- 2 Finished
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GRF: Multiplexed Real-time Optimal Control of Overall Heating, Ventilation, and Air-Conditioning Systems
HUANG, G. (Principal Investigator / Project Coordinator), LI, Z. (Co-Investigator) & SUN, Y. (Co-Investigator)
1/01/16 → 18/12/19
Project: Research
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GRF: Fire Risk Analysis Based on Artificial Neural Network Modelling Techniques
YUEN, K. K. R. (Principal Investigator / Project Coordinator) & LEE, W. M. (Co-Investigator)
1/01/15 → 21/12/18
Project: Research
Student theses
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Multiplexed Real-Time Optimization of HVAC Systems
HUSSAIN, S. A. (Author), YUEN, K. K. R. (Supervisor), 3 Aug 2017Student thesis: Doctoral Thesis
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