Identification of control regularity of heating stations based on cross-correlation function dynamic time delay method. (1st May 2022) - Sun, Chunhua; Liu, Yiting; Cao, Shanshan; Chen, Jiali; Xia, Guoqiang; Wu, Xiangdong
Abstract: Efficient operation and fine control are the keys of heating stations (HSs) to reduce energy consumption and carbon emission. Identifying control regularity of HSs is significant to realize fine control. This paper firstly defines control regularity, regulation time step (RTS) and regulation time node (RTN) of HSs. Then identify HSs' type based on insulation performance of buildings. Secondary loop supply and return temperature are chosen as characteristic parameters to determine pipe network thermal delay, while indoor temperature and the comprehensive outdoor temperature are used to determine building thermal inertia delay. Cross-correlation function dynamic time delay method is used to identify the delay time, and RTS of HS is determined. The regression model of RTS is obtained to decide daily RTNs. It is found that RTS of buildings with floor heating are larger than that with radiators, energy-saving buildings are larger than non-energy-saving buildings, and the high cold period is greater than the early and last cold period. The proposed method is applied to three HSs. Results show that average indoor temperature is maintained within the target range of 20 ± 1 °C, varies within a narrow range. Indoor temperature unevenness coefficient reduction indicates that indoor thermal comfort has been improved. Highlights: A data driven method to identify control regularity of heating substations (HSs). HSs are classified according to building's thermal insulation performance. CCF method to dynamically identify delay time of network and buildings. Regulation time step is decided upon the identified delay time. The strategy makes indoor temperature more stable and thermal comfort improved.