Profiling Energy and Built Environment Performance of A Smart Building in Singapore: A Case Study of Multi-Periods of Covid-19 Pandemic

This study proposes a specific view of profiling a smart building's energy consumption and built environment performance among multi-periods of Covid-19 pandemic. This case study leverages air-handling unit (AHU) as our specific observation among energy consumption and built environment, such as power meter (kW), carbon dioxide (CO
2
ppm), temperature (°C) and humidity (%) under a scope of typical one working week without any public holiday. This study proposes an approach to quantify the change significance and sign by performing relative normalization and statistical analysis on multi-periods' datasets. The results show that energy consumption has a largest change significance at negative 13.23% (during Covid-19 Resume Activity: Phase 3 period), compared with those in the period of pre Covid-19 as baseline. On the other hand, built environment has carbon dioxide, temperature and humidity as the largest change significance at positive 58.57% (post Covid-19 period), at positive 54.71% (during Covid-19 Resume Activity: Phase 1 period) and at negative 50.75% (during Covid-19 Resume Activity: Phase 1 period) respectively, compared with baseline. Moreover, the results also may be potentially useful and applicable to further use-cases, such as for modelling and optimization problems for occupancy and built environment monitoring with more explicit features like carbon dioxide, temperature and humidity. With the help of the proposed approach, feature selection and engineering techniques for AI/ML could be also adopted to enhance performance.