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Sparse Voltage Measurement-Based Fault Location Using Intelligent Electronic Devices

机译:使用智能电子设备的基于稀疏电压测量的故障定位

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摘要

This paper proposes a fault-section location method based on sparse measurements, aimed at asymmetrical faults. A virtual current vector is defined to indicate the faulted section, which is sufficiently sparse except that the fault position corresponding entries are nonzero. To simplify the algorithm, the virtual vector is fixed by amplitudes of voltages and impedances and the feasibility is demonstrated. The Bayesian Compressive Sensing theory is introduced to reduce the number of required intelligent electronic devices (IEDs). In addition, the minimal number of IEDs and their allocation are discussed. The performance of the proposed method is validated in a 69-bus, 12.66-kV distribution system with six distributed generations (DGs) in response to various fault scenarios. The simulation results show that the method is robust for single-phase, double-phase, and double-phase to ground faults with high resistance under noisy condition. Furthermore, the method is applicable for networks with inverter interfaced DGs.
机译:针对非对称故障,提出了一种基于稀疏测量的断面定位方法。定义虚拟电流矢量以指示故障区域,该区域足够稀疏,除了故障位置对应的条目为非零。为了简化算法,通过电压和阻抗的幅度固定虚拟矢量,并证明了可行性。引入贝叶斯压缩感测理论以减少所需的智能电子设备(IED)的数量。此外,还讨论了最小数量的IED及其分配。该方法的性能在具有六种分布式发电(DG)的69总线,12.66 kV配电系统中得到了验证,以应对各种故障情况。仿真结果表明,该方法对于噪声环境下高阻的单相,双相,双相接地故障具有鲁棒性。此外,该方法适用于具有逆变器接口的DG的网络。

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