This study presents robust parametric methods for the detection and estimation of grid-connected issues such as islanding, harmonics, and interharmonics. The power system signals are time varying owing to the intermittent nature of renewable energy sources. IEEE and IEC consider signals as stationary, which are negated in a future scenario. Therefore, parametric methods need to be applied for the estimation of these signals. In this study, parametric methods such as estimation of signal parameters via rotational invariant technique (ESPRIT) and multiple signal classifier are implemented in a grid-connected quasi-Z-source inverter, for the mitigation of the aforementioned grid-connected issues. Additionally, a novel ESPRIT-aided support vector machine (ESPRIT-SVM) is proposed for harmonics estimation. A comparative study is also conducted on the different parametric methods using MATLAB/SIMULINK. The proposed method is verified for application in various scenarios such as power mismatch, load switching, and capacitor switching. The simulation results of the proposed ESPRIT-SVM are validated through real-time experiments.

中文翻译：

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基于鲁棒参数法的准Z源逆变器光伏发电系统并网问题的检测与评估

这项研究提出了用于检测和估计诸如孤岛，谐波和间谐波的并网问题的鲁棒参数方法。由于可再生能源的间歇性，电力系统信号随时间变化。IEEE和IEC认为信号是静止的，在将来的情况下会否定信号。因此，需要将参数方法应用于这些信号的估计。在这项研究中，参数化方法（例如，通过旋转不变技术（ESPRIT）估算信号参数和多信号分类器）在并网的准Z源逆变器中实现，目的是缓解上述并网问题。另外，提出了一种新型的ESPRIT辅助支持向量机（ESPRIT-SVM）用于谐波估计。还使用MATLAB / SIMULINK对不同的参数方法进行了比较研究。所提出的方法经过验证，可用于各种场合，例如功率失配，负载开关和电容器开关。通过实时实验验证了所提出的ESPRIT-SVM的仿真结果。