Abstract
Nowadays, the collection of electrical energy measurement data is mainly completed by smart meters, electrical energy data monitoring equipment and electrical energy data management equipment. Due to system defects, equipment failures and human factors, it is prone to abnormal data collection. The design concept of online early warning system for extracting abnormal features of electrical energy data based on multi- node real-time computing framework is proposed in the paper to analyze the hardware and software of the online early warning system for extracting abnormal features of electrical energy data.
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