A conceptual framework for the real-time monitoring and diagnostic system for the optimal operation of smart building: A case study in Hotel ICON of Hong Kong

Wenzhuo Li, Choongwan Koo, Seung Hyun Cha, Joseph H.K. Lai, Jinsoo Lee
2019 Energy Procedia  
District heating networks are commonly addressed in the literature as one of the most effective solutions for decreasing the greenhouse gas emissions from the building sector. These systems require high investments which are returned through the heat sales. Due to the changed climate conditions and building renovation policies, heat demand in the future could decrease, prolonging the investment return period. The main scope of this paper is to assess the feasibility of using the heat demand
more » ... door temperature function for heat demand forecast. The district of Alvalade, located in Lisbon (Portugal), was used as a case study. The district is consisted of 665 buildings that vary in both construction period and typology. Three weather scenarios (low, medium, high) and three district renovation scenarios were developed (shallow, intermediate, deep). To estimate the error, obtained heat demand values were compared with results from a dynamic heat demand model, previously developed and validated by the authors. The results showed that when only weather change is considered, the margin of error could be acceptable for some applications (the error in annual demand was lower than 20% for all weather scenarios considered). However, after introducing renovation scenarios, the error value increased up to 59.5% (depending on the weather and renovation scenarios combination considered). The value of slope coefficient increased on average within the range of 3.8% up to 8% per decade, that corresponds to the decrease in the number of heating hours of 22-139h during the heating season (depending on the combination of weather and renovation scenarios considered). On the other hand, function intercept increased for 7.8-12.7% per decade (depending on the coupled scenarios). The values suggested could be used to modify the function parameters for the scenarios considered, and improve the accuracy of heat demand estimations. Abstract This study proposes a conceptual framework for the real-time monitoring and diagnostic system for the optimal operation of smart building, focusing on the energy-efficient, occupant-oriented, and comfortable indoor environment. The proposed framework aims to improve the energy efficiency in a room of building while achieving the healthy and comfortable indoor environmental quality and occupants' satisfaction. The proposed framework consists of a three-phase cyclic process (i.e. monitoring, diagnostic, and intervention), and it can be simply replicated and extensively applied to the different levels of physical entities (spatial scalability) in the different time resolutions in the whole life cycle processes (temporal scalability). To elaborate the feasibility of the proposed framework, the Hotel ICON in Hong Kong are chosen as a case study. For three rooms in the Hotel ICON, several sensors are installed for monitoring the energy efficiency and indoor environmental quality in real time. With the collected dataset, it is planned to carry out the diagnostic process (e.g. anomaly detection, time-series analysis, and occupancy schedule pattern analysis) and the intervention process (e.g. automatic control, occupant behaviour change, and optimal operation). The conceptual framework provides a standardized and systematic research approach toward a big picture of an intelligent building systems for the energy-efficient, occupant-oriented, and comfortable indoor environment.
doi:10.1016/j.egypro.2019.01.1005 fatcat:ukwaz2esene7llrm2pgiwkpewu