Journal
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
Volume 15, Issue 4, Pages 1909-1919Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TASE.2018.2844258
Keywords
Discrete event dynamic systems; Markov decision processes (MDPs); event-based optimization; building energy saving; complexity
Categories
Funding
- National Key Research and Development Program of China [2016YFB0901900]
- National Natural Science Foundation of China [61673229, 61222302, 61174072, 91224008, 61221063, U1301254]
- 111 International Collaboration Project of China [B06002]
- Program for New Star of Science and Technology in Beijing [xx2014B056]
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The optimal control of the heating, ventilation, and air-conditioning (HVAC) system in buildings has a significant energy saving potential and therefore is of a great practical interest. An event-based HVAC control adjusts control actions when certain events occur, which may be faster and more scalable than state-based or time-driven control methods. However, events may capture either local or global changes in the rooms. The choice of events is a tradeoff between the computational efficiency and the control performance. This challenging problem remains open. We consider this as an important problem in this paper and make three major contributions. First, we define local and global events for the HVAC control problem. The complexity of these event-based control policies is defined. Second, based on hypothesis testing, we develop a method to select events that capture a sufficient state information and with a relatively small event space. Third, we demonstrate the performance of this method on two groups of examples, including one group of small-scale problems for the proof of concept and the other group of large-scale problems in the HVAC control. It is shown that our method outperforms the Levin search, which is a traditional complexity-based search method and finds event-based HVAC control policies with a good performance.
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