首页> 外国专利> MACHINE LEARNING BASED METHOD AND DEVICE FOR DISTURBANCE CLASSIFICATION IN A POWER TRASMISSION LINE

MACHINE LEARNING BASED METHOD AND DEVICE FOR DISTURBANCE CLASSIFICATION IN A POWER TRASMISSION LINE

机译:基于机器学习的动力传输线路干扰分类方法和装置

摘要

The present specification provides a method and device for determining a disturbance condition in a power transmission line. The method includes obtaining (302) a plurality of sample values corresponding to an electrical parameter measured in each phase. The method further includes determining (304) a plurality of magnitudes of the electrical parameter corresponding to each phase based on the corresponding plurality of sample values and determining (306) a plurality of difference values for each phase based on the corresponding plurality of magnitudes. The method includes processing (308) the plurality of difference values using a machine learning technique to determine the disturbance condition. The disturbance condition is one of a load change condition, a power swing condition and an electrical fault condition. The method also includes performing (310) at least one of a protection function and a control function based on the disturbance condition.
机译:本说明书提供了一种用于确定电力传输线中的干扰条件的方法和装置。该方法包括获得(302)与在每个阶段中测量的电气参数相对应的多个样本值。该方法还包括基于相应的多个采样值确定(304)对应于每个相位对应于每个相位的多个电气参数,并基于相应的多个大小确定每个相位的多个差值。该方法包括处理(308)使用机器学习技术的多个差值来确定干扰条件。干扰条件是负载变化条件,动力摆动条件和电故障状况之一。该方法还包括基于干扰条件执行(310)保护功能和控制功能中的至少一个。

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