Event-Space Establishment in Event-Driven Optimal Control of Central AC Systems
From eSociety, September 2018
In the latest edition of Science and Technology for the Built Environment, Junqi Wang; Qing-Shan Jia; Gongsheng Huang, Ph.D., Member ASHRAE; and Yongjun Sun, Ph.D., Member ASHRAE, present a knowledge-based method for establishing event space.
The article, “Event-Driven Optimal Control of Central Air-Conditioning Systems: Event-Space Establishment,” includes case studies that were carried out in a typical commercial air-conditioning system that is used to demonstrate the proposed method and its effectiveness, where real measured load and weather data were used.
The researchers explain the significance and the impact of the research.
1. What is the significance of this research?
Central air-conditioning systems experience significant aperiodic or stochastic changes in their operation conditions. A conventional time-driven optimal control faces a dilemma of balancing control efficiency (higher optimization frequency) and computational efficiency (lower optimization frequency)..
To solve the dilemma, a new optimal control paradigm is needed. We developed an event-driven optimal control, in which “event” is used to trigger the optimization actions instead of “time.”
The new optimal control paradigm can promptly react stochastic changes, so that delayed or unnecessary control actions can be prevented. Our studies show that compared with the TDO the EDO can achieve comparable energy performance with a significantly reduced computation load.
2. Why is it important to explore this topic now?
Real-time optimal control (RtOpt) has been considered as an efficient strategy to improve the energy efficiency of buildings, which nowadays consume over 40% of end-use energy worldwide. However, RtOpt always presents a large-scale mathematical programming challenge for practical applications due to its computational complexity.
To capture the random changes in the operation conditions of HVAC systems, a higher frequency is needed for RtOpt, which further increases the computation burden. This explains why nowadays very few building energy management systems (BEMS) have this function. The proposed EDO can significantly reduce the computational load, and therefore is able to promote the future implementation of RtOpt.
3. What lessons, facts, and/or guidance can an engineer working in the field take away from this research?
This paper presents a knowledge-based method for establishing event space for the EDO paradigm, which can help HVAC engineers to understand the common events (changes in the operation conditions, such as weather conditions and load conditions) that have significant influences on the energy efficiency of air-conditioning systems, and thus to identify the right moment to do the optimization.
4. How can this research further the industry's knowledge on this topic?
Currently the HVAC industry devotes efforts to upgrade building energy management systems by integrating more advanced control function to enhance building energy efficiency.
This research provides an alternative mechanism to carry out real-time optimal control of air-conditioning systems. The developed solution can be easily realized in modern building energy management systems, and thus improve building energy efficiency.
5. Were there any surprises or unforeseen challenges for you when preparing this research?
When we prepared this research, we expected generic events exists for different types of air-conditioning systems in the framework of EDO. However, we found that suitable thresholds for those events should vary with weather condition. An easy yet effective way to determine suitable event thresholds might be required.
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