Jili Zhang
Professor

Gender:Male

Alma Mater:Herbin Architectural and Civil Engineering Univers

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MOBILE Version

Paper Publications

A real-time detection method of abnormal building energy consumption data coupled POD-LSE and FCD

Release time:2019-03-11 Hits:

Indexed by:会议论文

Date of Publication:2017-01-01

Included Journals:EI、CPCI-S

Volume:205

Page Number:1657-1664

Key Words:Fractal correlation dimension; proper orthogonal decomposition; linear stochastic estimation; energy consumption monitoring platform; internet of building energy system; real-time

Abstract: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.

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