A Non-stationary Analysis Using Ensemble Empirical Mode Decomposition to Detect Anomalies in Building Energy Consumption
| Autor: | Hariharan Naganathan, Wai K. Chong, Zigang Huang, Ying Cheng |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Consumption (economics)
Engineering Scale (ratio) business.industry Supply-Demand Characteristics 020209 energy Real-time computing 02 engineering and technology General Medicine Dynamical system Instantaneous phase Commercial building Hilbert–Huang transform symbols.namesake 0202 electrical engineering electronic engineering information engineering symbols Anomaly Detection Anomaly detection Hilbert transform Empirical mode decomposition business Hilbert Transform Engineering(all) Simulation Thermal energy |
| Zdroj: | Procedia Engineering. 145:1059-1065 |
| ISSN: | 1877-7058 |
| DOI: | 10.1016/j.proeng.2016.04.137 |
| Popis: | Commercial buildings’ consumption is driven by multiple factors that include occupancy, system and equipment efficiency, thermal heat transfer, equipment plug loads, maintenance and operational procedures, and outdoor and indoor temperatures. A modern building energy system can be viewed as a complex dynamical system that is interconnected and influenced by external and internal factors. Modern large scale sensor measures some physical signals to monitor real-time system behaviors. Such data has the potentials to detect anomalies, identify consumption patterns, and analyze peak loads. The paper proposes a novel method to detect hidden anomalies in commercial building energy consumption system. The framework is based on Hilbert-Huang transform and instantaneous frequency analysis. The objectives are to develop an automated data pre-processing system that can detect anomalies and provide solutions with real-time consumption database using Ensemble Empirical Mode Decomposition(EEMD) method. The finding of this paper will also include the comparisons of Empirical mode decomposition and Ensemble empirical mode decomposition of three important type of institutional buildings. |
| Databáze: | OpenAIRE |
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