Abnormality detection by model-based estimation of power consumption
Abnormality detection by model-based estimation of power consumption
复制标题
通过基于模型的功耗估计进行异常检测
DOI：
--
复制
发表时间：
2012
期刊：
影响因子：
--
通讯作者：
Jane Yung
中科院分区：
文献类型：
--
作者：
Chiao;Yi;Jane Yung
采暖、通风和空调（HVAC）系统在建筑物中占据大量的电力消耗。本文介绍了2012年7月在国立台湾大学研究与教学大楼进行的一项耗电案例研究。收集功率消耗、HVAC系统的参数、占用者的数量和气候信息以用于功率相关分析。我们提出了一个近似的最低冷却需求，以观察功耗的适当性。结果表明，真实的冷却供应远高于最小冷却需求，这将是一个机会，以减轻功耗。此外，我们还研究检测事件以防止潜在的错误。通过对事件的分析，这对于提高电力使用的效率是有用的。结果表明，我们的方法可以检测到一些事件，但一些事件是难以解释的。我们将改进异常检测方法，并在未来收集更多具有变异事件的数据。
Heating, ventilation, and air conditioning (HVAC) systems occupy a large amount of power consumption in buildings. We introduce a case study of power consumption in the research and teaching building at National Taiwan University in July, 2012. Power consumption, the parameters of the HVAC system, the number of occupants, and the climate information are collected for power related analysis. We proposed an approximation for minimum cooling demands to observe the appropriateness of power consumption. The results show that the real cooling supply is much higher than the minimum cooling demands which would be a chance to mitigate the power consumption. In addition, we also investigate to detect events for preventing the potential errors. It is useful for promoting efficiency for power usage through the analysis of events. The results show that some of events could be detected by our methods, but several events are difficult to explain. We will improve the methods for abnormal detection and collect more data with variant events in the future.