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- W3089490090 abstract "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." @default.
- W3089490090 created "2020-10-08" @default.
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- W3089490090 date "2020-12-01" @default.
- W3089490090 modified "2023-09-25" @default.
- W3089490090 title "Detection and estimation of grid‐connected issues in quasi‐Z‐source inverter based photovoltaic system using robust parametric methods" @default.
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- W3089490090 doi "https://doi.org/10.1049/iet-pel.2019.1582" @default.
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