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Conference Paper Error Distribution-based Anomaly Score for Forecasting-based Anomaly Detection of PV Systems
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Authors
HyunYong Lee, Nac-Woo Kim, Jun-Gi Lee, Byung-Tak Lee
Issue Date
2021-10
Citation
International Conference on Information and Communication Technology Convergence (ICTC) 2021, pp.1144-1146
Publisher
IEEE
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1109/ICTC52510.2021.9620808
Abstract
For forecasting-based anomaly detection for PV systems, in this paper, we propose a way for calculating anomaly scores. The basic idea of our approach is to utilize the distribution of forecasting errors of normal data to derive relative anomaly score, which is limited to from 0 to 100. To further improve the anomaly score, we apply our basic idea to each month separately because the distribution of forecasting errors changes over time. Through experiments using the real data, we examine some aspects of our approach preliminarily.
KSP Keywords
Forecasting error, Over time, PV system, Real data, anomaly detection, anomaly score, error distribution