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Research on Voltage Sag Disturbance Pattern Recognition Based on Deep Learning
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作者 WANG Zibing YANG Shunqing +2 位作者 XU Yingwen JI Yuqing BAO Kaitong 《外文科技期刊数据库(文摘版)工程技术》 2021年第12期818-822,共8页
The new power system with new energy as the main body has become a hot research direction at present. However, the volatility, randomness and unschedulability of grid-connected power generation of new energy will have... The new power system with new energy as the main body has become a hot research direction at present. However, the volatility, randomness and unschedulability of grid-connected power generation of new energy will have a great impact on power quality, thus posing a severe challenge to the reliability, stability and security of power grid operation. But at the same time, the diversified application of sensitive power electronic equipment in power load and the wide use of precision electronic instruments in industrial production require high transient stability of power quality. For voltage sag problems, this paper through the analysis of disturbance in pattern recognition, the single voltage sag and voltage sag disturbance reason, analyzed the characteristics of the harmonic disturbance, and is verified by the simulation of power quality disturbance pattern recognition methods, break through the complex power grid environment based on the physical properties of the limitations of modeling complex disturbance in pattern recognition. It effectively improves the timeliness of voltage disturbance pattern recognition. 展开更多
关键词 voltage sag disturbance pattern recognition characteristic analysis feature extraction
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