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학술대회 Smart Metering System Capable of Anomaly Detection by Bi-directional LSTM Autoencoder
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이상금, 진호준, Sarvar Hussain Nengroo, 도윤미, 이충호, 허태욱, 하동수
International Conference on Consumer Electronics (ICCE) 2022, pp.1-6
21PR6100, 가정 에너지 사용량 실시간 진단 및 지능형 자율제어/관리 시스템 원천기술 개발, 도윤미
Anomaly detection is concerned with a wide range of applications such as fault detection, system monitoring, and event detection. Identifying anomalies from metering data obtained from smart metering system is a critical task to enhance reliability, stability, and efficiency of the power system. This paper presents an anomaly detection process to find outliers observed in the smart metering system. In the proposed approach, bi-directional long short-term memory (BiLSTM) based autoencoder is used and finds the anomalous data point. It calculates the reconstruction error through autoencoder with the non-anomalous data, and the outliers to be classified as anomalies are separated from the non-anomalous data by predefined threshold. Anomaly detection method based on the BiLSTM autoencoder is tested with the metering data corresponding to 4 types of energy sources electricity/water/heating/hot water collected from 985 households.
KSP 제안 키워드
Bi-directional, Critical task, Detection Method, Energy sources, Event detection, Long-short term memory(LSTM), Metering data, Power system, Reconstruction Error(RE), Smart Metering System, System monitoring