| 引用本文: | 张逸,张良羽,陈锦涛,姚文旭,陈敏.基于电能质量监测数据的电压暂降敏感负荷识别[J].电力自动化设备,2025,45(2):176-184. |
| ZHANG Yi,ZHANG Liangyu,CHEN Jintao,YAO Wenxu,CHEN Min.Voltage sag-sensitive load identification based on power quality monitoring data[J].Electric Power Automation Equipment,2025,45(2):176-184. |
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| 摘要: |
| 为了解决现有方法无法适用于已投运负荷或需要已知敏感负荷类型等问题，提出一种基于电能质量监测数据的敏感负荷识别方法，以有功功率有效值监测数据为切入点，采用Hodrick-Prescott滤波、滑动均值分段进行电压暂降事件时段划分；利用电压暂降事件前、后的电能质量监测数据变化量构建待处理稳态数据集，通过动态聚类来有效划分各次电压暂降事件；对各暂降事件集进行边界拟合，得到多个拟合拐点，并与预设拐点行比较，完成对用户所含敏感负荷的类型识别。通过MATLAB/Simulink仿真算例和实际敏感用户电能质量监测数据对所提方法进行验证，结果表明所提方法可准确识别交流接触器、变频调速系统、可编程逻辑控制器、个人计算机这4种典型敏感负荷，能有效利用稳态电能质量监测数据与电压暂降事件数据进行综合分析，具有成本低、可实施性强的优点。 |
| 关键词: 敏感负荷识别 电能质量监测数据 电压暂降 动态K-means聚类 VTC拐点拟合 |
| DOI：10.16081/j.epae.202411008 |
| 分类号:TM714 |
| 基金项目:福建省自然科学基金资助项目(2020J01123)；福建省科技引导性项目(2020H0009) |
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| Voltage sag-sensitive load identification based on power quality monitoring data |
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ZHANG Yi1, ZHANG Liangyu1, CHEN Jintao1, YAO Wenxu2, CHEN Min1
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1.College of Electrical Engineering and Automation, Fuzhou University, Fuzhou 350108, China;2.Electric Power Research Institute of State Grid Fujian Electric Power Co.,Ltd.,Fuzhou 350007, China
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| Abstract: |
| In order to address issues such as the existing methods are not applicable to operational loads or require knowledge of sensitive load types, a sensitive load identification method based on power quality monitoring data is proposed. Taking the monitoring data of active power root-mean-square value as the entry point, the Hodrick-Prescott filtering and sliding mean segmentation are used to divide the period of transient voltage sag events. The steady-state dataset is constructed based on the variation of power quality monitoring data before and after the transient voltage sag events, and dynamic clustering is used to effectively divide various transient voltage sag events. Finally, the voltage tolerance curves of each action area are fitted and compared with the preset curves to complete the type of identification of the sensitive load contained by the user. Through MATLAB/Simulink simulation examples and actual sensitive user power quality monitoring data, it is proved that the proposed method can accurately identify four typical sensitive loads such as AC contactor, adjustable speed drive, programable logic controller and personal computer, and can effectively use steady-state power quality monitoring data and voltage sag event data for comprehensive analysis, which has the advantages of low cost and strong implementation. |
| Key words: sensitive load identification power quality monitoring data voltage sag dynamic K-means cluste-ring VTC inflection point fitting |
