Feature Extraction of Anomaly Electricity Usage Behavior in Residence Using Autoencoder

• Published in: Electronics (Basel) Vol. 11; no. 9; p. 1450
• Main Authors: Tsai, Chia-Wei, Chiang, Kuei-Chun, Hsieh, Hsin-Yuan, Yang, Chun-Wei, Lin, Jason, Chang, Yao-Chung
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.05.2022
• Subjects: Accuracy; Advanced metering infrastructure; Anomalies; Artificial intelligence; Behavior; Carbon; Data acquisition; Deep learning; Electricity; Electricity consumption; Electricity meters; Energy conservation; Energy consumption; Energy management; Feature extraction; Internet of Things; Load; Machine learning; Residential energy; Taiwan

Due to the climate crisis, energy-saving issues and carbon reduction have become the top priority for all countries. Owing to the increasing popularity of advanced metering infrastructure and smart meters, the cost of acquiring data on residential electricity consumption has substantially dropped. T...