论文成果
A real-time detection method of abnormal building energy consumption data coupled POD-LSE and FCD
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- 论文类型：会议论文
- 发表时间：2017-01-01
- 收录刊物：EI、CPCI-S
- 文献类型：A
- 卷号：205
- 页面范围：1657-1664
- 关键字：Fractal correlation dimension; proper orthogonal decomposition; linear
stochastic estimation; energy consumption monitoring platform; internet
of building energy system; real-time
- 摘要：To understand the energy consumption characteristics of buildings, numerous building energy consumption monitoring platforms and internet of building energy systems have been established in the large public buildings, government office buildings, as well as colleges and universities. Although the platforms provide us with a large amount of energy consumption in-formation, there are serious problems. However, the validity of the energy consumption data is one of the most common problems. In this paper, a real-time detection method, which coupled fractal correlation dimension and proper orthogonal decomposition linear stochastic estimation, is presented to identify abnormal energy consumption data. The proper threshold is selected with varying operational conditions. The result shows that using this real-time meth-od yields a higher correctness rate than using traditional method in fault detection of data loss and outlier. It's worth pointing out that a hybrid method combining with other intelligent algorithms should be promising to identify and classify small bias abnormal data fault in further investigation. (c) 2017 The Authors. Published by Elsevier Ltd.
