Event-driven online decoupling control mechanism for the variable flow rate HVAC system based on the medium response properties.

The decoupling control of the quality and quantity parameters in heating, ventilation, and air conditioning (HVAC) systems with variable flow rates is critical to system performance optimization. However, the conventional optimization mechanism often employs an empirical fixed time interval to optimize the system periodically, which is not sufficiently flexible to handle load variations (e.g., outdoor weather changes and occupant turnover). Consequently, untimely or unnecessary optimization actions would aggravate the parameter coupling relationships. Therefore, a new optimization mechanism that considers coupling relationships must be studied to improve flexibility. In this paper, an event-driven optimization mechanism with adaptive intervals is proposed to improve the optimization efficiency and overall performance. The proposed strategy can take necessary optimization for the system while considering delayed response characteristics, which is beneficial to the system decoupling optimization control. To ensure the online feasibility of the proposed strategy, an online application mechanism with a double-loop framework is presented herein. The performance of the proposed method was verified experimentally using a practical variable flow rate HVAC system. Compared to the conventional time-driven optimization strategy, the proposed strategy presents a superior performance in terms of both decoupling and control effects, as well as a certain potential for energy savings. This research is significant and referable to related personnel (e.g., engineers and operators) to promote online decoupling control and intelligent optimizations with variable intervals and demand-based approaches. Meanwhile, the combination of dynamic diffusion characteristics and the double-loop control framework also provides a new orientation for the online optimization of practical systems. • Propose the sequential event-driven optimization (SEDO) strategy. • Medium dynamic diffusion properties in pipeline network are considered. • Compared with the time-driven optimization (TDO) strategy experimentally. • Proposed method performs superior decoupling and control effects. • Energy reduction of 4.03% can be achieved compared to the TDO strategy. [ABSTRACT FROM AUTHOR]