基于模糊聚类分析的电能质量扰动模式识别方法
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TM76

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国家重点研发计划(2018YFF0212900)


Disturbance pattern recognition method of power quality based on the fuzzy clustering analysis
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    摘要:

    为了提高电能质量扰动识别的准确性,弥补基于传统单一特征量模式识别方法易受干扰、精度低的缺陷,提出基于模糊聚类分析的电能质量扰动模式识别方法。该方法利用HHT变换从多种不同类型的电能质量扰动信号中提取出相应的扰动特征量,再将提取的特征量进行模糊聚类分析,准确地把这些电能质量扰动信号一一归类至光伏扰动与公共电网扰动两大类别,同时建立基于模糊聚类分析的电能质量扰动识别流程。仿真结果表明,该方法克服了传统单一特征量模式识别方法的局限性,优化了扰动信号的识别效果,提高了识别效率,识别精度高,抗噪能力强。

    Abstract:

    In order to improve the accuracy of power quality disturbance recognition and make up for the shortcomings of traditional single feature quantity pattern recognition methods that are easily disturbed and have low precision, a power quality disturbance pattern recognition method based on fuzzy cluster analysis is proposed. The method uses Hilbert-Huang transformation (HHT) to extract corresponding disturbance feature quantities from various types of power quality disturbance signals, and then performs fuzzy clustering analysis on the extracted feature quantities to accurately classify these power quality disturbance signals into photovoltaic disturbances and public grid disturbances one by one. At the same time, a power quality disturbance identification process based on fuzzy cluster analysis is established. Simulation results show that this method overcomes the limitations of the traditional single-feature pattern recognition method, optimizes the recognition effect of disturbance signals, improves the recognition efficiency, and has high recognition accuracy and strong anti-noise ability.

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陈向群,杨茂涛,刘谋海,黄瑞,余敏琪,王智.基于模糊聚类分析的电能质量扰动模式识别方法[J].电力科学与技术学报,2022,(2):79-85. CHEN Xiangqun, YANG Maotao, LIU Mouhai, HUANG Rui, YU Minqi, WANG Zhi. Disturbance pattern recognition method of power quality based on the fuzzy clustering analysis[J]. Journal of Electric Power Science and Technology,2022,(2):79-85.

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  • 在线发布日期: 2022-05-26
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