TY - JOUR
T1 - Event-driven optimization of complex HVAC systems
AU - WANG, Junqi
AU - HUANG, Gongsheng
AU - SUN, Yongjun
AU - Liu, Xiaoping
PY - 2016/12/1
Y1 - 2016/12/1
N2 - Real-time optimization (RTO) has been developed to improve the cost and/or energy efficiency of complex heating, ventilation and air-conditioning (HVAC) systems. In current literature, almost all of the developed real-time optimization methods belong to the type of time-driven optimization, in which the action of optimization is triggered by “time”. As optimization should be done when the system operating conditions experience a change that is large enough to cause current operational setting not optimal any more, optimization strategies should recognize ‘significant’ changes and perform optimization when necessary. Since the time-driven optimization is a periodic mechanism in nature while those ‘significant’ changes may not be periodic, the time-driven optimization cannot capture ‘significant’ changes and do the optimization promptly. Therefore, this paper proposes an event-driven optimization (EDO) for complex HVAC systems, the key idea of which is to use “event” rather than “time” to trigger the action of optimization. A systematic event-driven optimization method is illustrated, where its main tasks, including event definition and event identification, will be discussed. The proposed method will be compared with a conventional time-driven method using case studies, through which the main advantages of the proposed method will be identified.
AB - Real-time optimization (RTO) has been developed to improve the cost and/or energy efficiency of complex heating, ventilation and air-conditioning (HVAC) systems. In current literature, almost all of the developed real-time optimization methods belong to the type of time-driven optimization, in which the action of optimization is triggered by “time”. As optimization should be done when the system operating conditions experience a change that is large enough to cause current operational setting not optimal any more, optimization strategies should recognize ‘significant’ changes and perform optimization when necessary. Since the time-driven optimization is a periodic mechanism in nature while those ‘significant’ changes may not be periodic, the time-driven optimization cannot capture ‘significant’ changes and do the optimization promptly. Therefore, this paper proposes an event-driven optimization (EDO) for complex HVAC systems, the key idea of which is to use “event” rather than “time” to trigger the action of optimization. A systematic event-driven optimization method is illustrated, where its main tasks, including event definition and event identification, will be discussed. The proposed method will be compared with a conventional time-driven method using case studies, through which the main advantages of the proposed method will be identified.
KW - Computational efficiency
KW - Energy efficiency
KW - Event-driven optimization
KW - HVAC systems
KW - Real-time optimization
UR - http://www.scopus.com/inward/record.url?scp=84989211576&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-84989211576&origin=recordpage
U2 - 10.1016/j.enbuild.2016.09.049
DO - 10.1016/j.enbuild.2016.09.049
M3 - RGC 21 - Publication in refereed journal
SN - 0378-7788
VL - 133
SP - 79
EP - 87
JO - Energy and Buildings
JF - Energy and Buildings
ER -