ITM Web Conf.
Volume 45, 20222021 3rd International Conference on Computer Science Communication and Network Security (CSCNS2021)
|Number of page(s)||11|
|Section||Computer Technology and System Design|
|Published online||19 May 2022|
Research on electrical power quality disturbance recognition method based on edge computing and LightGBM
State Grid Information & Telecommunication Co., Ltd., Changping District, Beijing 100031, China
2 State Grid Tianjin Electric Power Company, Hebei District, Tianjin 300010, China
* Corresponding author: email@example.com
In conventional cloud computing, method that data is transmitted and calculated on the cloud cannot satisfy the real-time demand for energy quality disturbance recognition. This paper proposed a power quality disturbance recognition method based on edge computing and LightGBM classification algorithm. Our main idea is that the feature of disturbance is extracted on the edge sides and used to classified on the cloud. Firstly, a multi-group feature set was extracted at the edge side intelligent fusion terminal by wavelet transform. Secondly, we used feature training accuracy to select the optimal feature collection. Finally, the optimal feature set was selected to determine the disturbance recognition method of this paper. Experiments had shown that the proposed method meets demand on data transmission by 99.5%, and achieves 97.53% recognition accuracy. Our method not only guarantees high accuracy of the power quality disturbance recognition but also alleviates the bandwidth load pressure brought by large amounts of data transmission.
Key words: Edge computing / Wavelet transform / LightGBM / Power quality disturbance recognition
© The Authors, published by EDP Sciences, 2022
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