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An improved algorithm for power system fault type classification based on least square phasor estimation

机译:基于最小二乘相量估计的电力系统故障类型分类改进算法

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Smart grids have urged a radical reappraisal of distribution networks and power quality requirements, which demand to continuously monitor grid conditions. This allows for early classification of power quality degeneration. In this context, this paper proposes an improved algorithm for phasor estimation and fault type classification in smart grid applications. The proposed algorithm is specifically composed of two steps: first, the phasor estimation from the input signals, which can be executed on the Phasor Measurement Unit (PMU). While step two concerns the fault type classification using the phasor estimation. Specifically, we propose to estimate the phasor parameters, (frequency, amplitude and initial phase) using least square method. Then, fault type classification is obtained using symmetrical component algorithm. The proposed algorithm can be used for the identification of power quality disturbances. It has been evaluated, compared, and studied with simulated data. Simulation results show accurate phasor estimations and accurate fault type classification in presence of noise.
机译:智能电网已敦促对配电网络和电能质量要求进行彻底的重新评估,这要求不断监测电网状况。这允许电能质量退化的早期分类。在此背景下,本文提出了一种改进的算法,用于智能电网应用中的相量估计和故障类型分类。所提出的算法具体包括两个步骤:第一,可以根据相量测量单元(PMU)执行输入信号中的相量估计。第二步涉及使用相量估计进行故障类型分类。具体来说,我们建议使用最小二乘法估算相量参数(频率,幅度和初始相位)。然后,使用对称分量算法获得故障类型分类。该算法可用于电能质量扰动的识别。已使用模拟数据对其进行了评估,比较和研究。仿真结果表明,在存在噪声的情况下,准确的相量估计和准确的故障类型分类。

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