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

机译:占用行为对低收入住宅建筑能耗的贡献

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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%.
机译:住宅建筑的能源消耗每年消耗美国总能量总量的22%,受占用行为受到高度影响。 为了更准确地模拟国内需求概况,了解占用行为概况非常重要。 德克萨斯州的四栋低收入房屋用作试验台。 占用传感器安装在每个房间。 与美国时间使用调查(ATU)数据进行比较来自占用传感器的现实占用数据。 研究期为7月1日至8月31日。初步结果表明,ATU数据与实际占用概况之间存在相似性。 此外,对EnergyPlus进行了模拟,以测试基于现实占用行为模式的恒温器控制可以节省多少能耗。 结果表明,这种控制可以将冷却能量节省7%。

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