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PMU based line outage identification using comparison of current phasor measurement technique

机译:使用电流相量测量技术的基于PMU的线路中断识别

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摘要

In this paper, a novel algorithm for identification of multiple line outage based on comparison of current phasor measurement (CCPM) technique is presented. A least square norm minimization model has been developed considering bad data due to faulty phasor measurement unit (PMU). In this proposed algorithm, the line current phasors obtained from load flow simulation for several outage cases are stored. On occurrence of actual outage, PMU provided current phasors are compared with the stored simulated current phasors using least square norm minimization approach. Moreover, random Gaussian noise with zero mean and standard deviation from 1% to 5% is introduced in the proposed model to check the feasibility in real power network. The performance of the proposed algorithm is evaluated by introducing two novel indices i.e., estimation accuracy including critical cases (EAICC) and estimation accuracy excluding critical cases (EAECC). Moreover, another new performance index i.e., success rate with repeated trial (SRWRT) is proposed to verify the noise independency of the test results with repeated number of trials. Performance of the algorithm is tested on IEEE 5-bus, 14-bus, 30-bus, 57-bus, and 118-bus systems. Numerical results show the reliability and viability of the proposed methodology for identification of multiple line outages.
机译:本文提出了一种基于电流相量测量(CCPM)技术比较的多线路中断识别新算法。考虑到由于相量测量单元(PMU)故障而产生的不良数据,已开发出最小二乘范数最小化模型。在该算法中,存储了从潮流模拟中获得的几种断电情况下的线电流相量。在发生实际中断时,使用最小二乘规范最小化方法将PMU提供的电流相量与存储的模拟电流相量进行比较。此外,在该模型中引入了均值为零且标准偏差为1%至5%的随机高斯噪声,以检验在实际电网中的可行性。通过引入两个新颖的指标来评估所提出算法的性能,即,包括关键案例的估计精度(EAICC)和不包括关键案例的估计精度(EAECC)。此外,提出了另一个新的性能指标,即重复试验的成功率(SRWRT),以通过重复试验次数来验证测试结果的噪声独立性。该算法的性能在IEEE 5总线,14总线,30总线,57总线和118总线系统上进行了测试。数值结果表明,该方法可用于多线路故障的识别。

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