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Auto-correlation-based Islanding detection technique verified through hardware-in-loop testing

机译:通过硬件在环测试验证了基于自相关的孤岛检测技术

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摘要

This study describes a novel Islanding detection technique based on a discrimination factor (DF) which is derived from an auto-correlation factor (ACF) of the voltage signals acquired from the terminal of the distributed generator. The value of DF is calculated from the most affected lags of the ACF during various Islanding and non-Islanding conditions. Further, the validation of the presented scheme has been carried out by developing a hardware-in-loop laboratory setup. In this setup, a power distribution network has been modelled on a real-time digital simulator (RTDS/RSCAD) which is physically connected to the digital signal processor controller. Various non-Islanding and Islanding test scenarios have been generated. The proposed ACF-based technique is able to differentiate Islanding state with non-Islanding states even for perfect power equilibrium situation. The proposed approach can determine the Islanding state in a period of three cycles from the inception of Islanding. Finally, a relative assessment of the above algorithm with other existing methods shows its supremacy in terms of better stability during critical non-Islanding situations and lower non-detection zone in case of Islanding states.
机译:这项研究描述了一种基于判别因子(DF)的新颖孤岛检测技术,该判别因子是从分布式发电机终端获取的电压信号的自相关因子(ACF)得出的。 DF的值是根据在各种孤岛和非孤岛条件下受影响最大的ACF滞后计算得出的。此外,已通过开发硬件在环实验室设置对所提出的方案进行了验证。在此设置中,已在物理连接到数字信号处理器控制器的实时数字模拟器(RTDS / RSCAD)上对配电网络进行了建模。已经生成了各种非孤岛和孤岛测试方案。所提出的基于ACF的技术即使在完美的功率平衡情况下也能够区分孤岛状态与非孤岛状态。所提出的方法可以在从出现孤岛开始的三个周期内确定孤岛状态。最后,对上述算法与其他现有方法的相对评估显示,在关键的非孤岛情况下更好的稳定性和在孤岛状态下更低的非检测区域方面,它具有至高无上的地位。

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