An Effective Method for the Characterisation of Smart Building Hot Water Provisioning Systems through Analysis of Loop Return Temperature at High Temporal Resolution

Most campus type building environments operate large boiler estates either centrally or individually within buildings, in the provisioning of Low Pressure Hot Water (LPHW) services to their sites. And despite the fact that boilers occupy one of the top significant energy users in any building estate listing, it is contended that in general the level of understanding within the Facilities Management communities around boiler operation and their control is less well understood than their electricity related energy user counterparts, due to a number of reasons. This paper presents a pragmatic efficient data driven approach to address this deficiency, through the presentation of a simplified data analysis approach, using high resolution sampling (periods of one minute) of a single control point, that of LPHW Loop Return temperature (Treturn) to adequately characterise hot water provisioning systems. A subsequent set of time series Treturnprofiles are presented and discussed that demonstrate the effectiveness and value of such an approach. Also one example of how this insight can be converted into an actual savings opportunity is presented where the leveraging of zero heating demand event signatures can achieve savings of the order of 100 MWh in one building alone during a summer season. The paper also contends that such an approach could become an important element of Smart Building hot water provisioning optimisation in the future, where the development and use a library of such time series Treturnprofiles could help identify realtime anomalous control behaviour, and allow for automatic dynamic demand response control strategies to be implemented.