Anomalous data detection methods for new power systems

doi:10.3969/j.issn.2097-0706.2024.05.002

Abstract

Abstract:

With the rapid development of new power systems， massive data with various types are generated from the power systems. The complicated data conditions bring new challenges to anomaly data detection for power systems. In a summary on commonly used methods for anomalous power data in detecting， traditional technology-based， machine learning-based and deep learning-based detection methods are introduces. The working principle， characteristics and shortcomings of the three types of detecting methods are analysed. In the end， the challenges and development trends of anomalous data detection in new power systems are looked forward.

Key words: new power system, abnormal data, machine learning, deep learning traditional technology, anomaly detection

CLC Number:

TK01：TM727

WANG Liang, DENG Song. Anomalous data detection methods for new power systems[J]. Integrated Intelligent Energy, 2024, 46(5): 12-19.

Figures/Tables 2

References 40

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