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文章摘要
基于GPU的电能表健康状态评估与预测
Assessment and Prediction of the Health Status of Electric Energy Meters Based on GPU
Received:January 25, 2019  Revised:January 25, 2019
DOI:10.19753/j.issn1001-1390.2020.11.021
中文关键词: 图形处理器  径向基神经网络  电能表健康状态评估  电能表健康状态预测
英文关键词: Graphics Processing Unit(GPU), RBF neural network,Assessment of Power Meter State, Forecasting of Power Meter State
基金项目:
Author NameAffiliationE-mail
luchunyan* NARI Group Corporation State Grid Electric Power Research Institute luchunyan111@163.com 
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中文摘要:
      随着智能电网快速发展,用电信息采集系统中智能电能表规模日渐庞大,给海量数据实时分析及电能表运维带来巨大挑战。近年来,图形处理器(Graphics Processing Unit,GPU)超高速并行计算及快速训练大规模神经网络特性已经成为国内外高性能计算领域一个新的研究热点。但是,到目前为止,还没有看到GPU在用电信息采集系统中的应用。本文着重研究如何在用电信息采集系统中运用GPU实现电能表健康状态在线评估及预测,以提升统计性能,为电能表精益化运维提供有力依据。
英文摘要:
      With the rapid development of the intelligent power grid, the scale of the intelligent energy meters in Eleco Energy Data Acquire System is increasing day by day. Real-time analysis of massive data and maintenance of electric energy meter is a big challenge for Eleco Energy Data Acquire System. Recently, the highly data-parallel computing and rapidly training large-scale neural network of Graphics Processing Unit(GPU) has been a new research hotspot in the field of high-performance parallel computing. However, until now, GPU has not been applied to Eleco Energy Data Acquire System. In order to improve the performance of statistical analysis and realize the prediction of meter health status, this paper do research on how to realize GPU in Eleco Energy Data Acquire System, to support the lean operation and maintenance of electric energy meter.
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