The Contribution Of Occupancy Behavior To Energy Consumption In Low Income Residential Buildings

Abstract

Energy consumption in residential buildings consumes 22% of the total US energy each year and is highly impacted by the occupant behavior. In order to model domestic demand profiles more accurately, it is important to understand occupancy behavior profile. Four low income houses in Texas are used as the test beds. The occupancy sensors are installed in every room. The real-life occupancy data from the occupancy sensors were compared with the American Time Use Survey (ATUS) data. The study period is from July 1 to August 31. The preliminary result shows that there is a similarity between ATUS data and actual occupancy profile. In addition, simulations in EnergyPlus were conducted to test how much energy consumption can be saved based on the thermostat control of real-life occupancy behavior patterns. The results show that such control can save cooling energy by 7%

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