Big Data Detection System of Electric Meter Based on LSTM Technology
1. Business School, Hong Kong University of Science and Technology, Hongkong 999077,
2. Suzhou Haoxing Haizhou Science and Technology Co., Ltd, Suzhou 215164, China
| Abstract: | With the sustained development of power plant of China, the installed base of electric meter grows gradually. It is more and more important to monitor smart meters with their mature use. In order to avoid huge resource wasting and solve the issue because of physical testing of smart meter when smart meter service life time arriving (maximum 8 years), LSTM method related to time series model (TSM) is firstly used to do research on smart meter. Smart meter testing without physical disassembling is realized successfully. Eventually testing abnormity and failure recognition can be obtained through prediction research based on deep learning time series model. Based on electric meter running big data analysis, the electric meter situation including normal and abnormal (error or electricity stealing) and relevant position can be obtained so as to take further action. The research and application of the testing system can avoid physical testing to electric meter. The service time of normal meter can be prolonged by abnormal meters testing. This will lead to saving a lot of resources. The LSTM research method on deep learning is the innovative application in electric power domain. |
| Keywords: | Smart Meter; Data Analysis; Deep Learning Time Series Model; LSTM |
| DOI: | 10.57237/j.cst.2022.01.005 |
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Received: 2 October 2022
Accepted: 26 December 2022
Published Online: 5 January 2023
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