Abstract Today, every new building is constructed with the ambition of it having a very low energy demand or even being completely neutral with regard to supply and demand over a year. In modern low energy or nearly zero energy residential buildings like these, the behaviour of the occupants becomes increasingly more significant in terms of the energy performance of the building. Occupants who are present and using appliances reduce the amount of heat needed to be supplied by the heating system. Knowledge about occupant behaviour is, consequently, of great importance. As occupants’ presence, absence and behaviour are hard to measure without being intrusive, the level of occupancy is often derived from statistics gathered from questionnaire surveys or from measurements of other variables connected to occupancy, such as household electricity use. This study investigates such measurement data with regard to the use of household electricity, domestic hot water and domestic cold water gathered at hourly intervals over a whole year in over 1,000 Swedish apartments. A method is proposed whereby an apartment is regarded as being empty if no water (hot or cold) is used during an entire day. Using this method, 50% of the apartments were found to have 10 days of absence or more, and for apartments in the interquartile range, i.e. the 50% closest to the median, the periods of absence varied between 1 and 31 days. The validation showed an increase of absence during national holidays by about 300%, and by about 100% during weekends. The outcome of estimating absence using only one of the variables was evaluated and it was shown that domestic cold water use would be a good substitute method with 98% precision.

中文翻译：

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一种基于生活用水估计公寓缺水的方法

摘要 今天，每座新建筑的建造都以能源需求非常低，甚至在一年内的供需方面完全中立为目标。在像这样的现代低能耗或接近零能耗的住宅建筑中，就建筑的能源性能而言，居住者的行为变得越来越重要。在场和使用电器的居住者减少了供暖系统需要提供的热量。因此，了解乘员行为非常重要。由于居住者的存在、缺席和行为很难在不被打扰的情况下进行衡量，因此入住率通常来自问卷调查收集的统计数据或与入住率相关的其他变量的测量值，例如家庭用电量。本研究调查了瑞典 1,000 多套公寓全年每小时收集的有关家庭用电、生活热水和生活冷水使用情况的此类测量数据。提出了一种方法，如果一整天没有使用水（热或冷），则公寓被认为是空的。使用这种方法，发现 50% 的公寓有 10 天或更多的缺勤天数，而对于四分位数范围内的公寓，即最接近中位数的 50%，缺勤时间在 1 到 31 天之间变化。验证表明，国定假日期间缺勤人数增加了约 300%，周末增加了约 100%。