There have been many efforts to extract the impact of human behaviors from building-related data in the domain of Building Science. Recent studies use the information from power suppliers to estimate the impact of occupants, and the energy use level and variation. However, those studies are heavily relying on monthly energy bills collected from residential sectors or a whole building context[JC1] , and have limitedly investigated the sensitivity of occupants on energy-end use type, which contributes to the overall building energy performance independently.
With the advancement of sub-metering and cloud storage technology, energy consumption data can now be broken down into end-use categories in a commercial setting and occupant’s impact can be more refined. Sensors are placed for sub-metering energy use at the circuit level, weather data is collected from a weather station located on the site, and indoor conditions is gathered from data loggers, occupants are counted using a bi-directional occupancy counter. This study aims for understanding the impact of occupants on end-use categories and also the order of influencing factors on energy consumption. Results of this study show occupants’ effects on energy use of Computer, office equipment, lighting, AHU, kitchen equipment and refrigeration. It was also found that climate precedes occupancy in affecting total energy use. the result ofthis study give a deeper insight into how energy is used and potential refinement of schedules in energy simulation.