An Advanced Frequency Adaptive PLL for Grid Connected Inverters Under Abnormal Grid Conditions

The necessity to expand the use of distributed renewable energy sources (DERS) with grid-connected inverters has emphasized the critical role of phase-locked loop (PLL) controllers in swiftly and accurately acquiring grid voltage phase angles, particularly under abnormal grid conditions. Frequency adaptive PLL has gained popularity due to its low computational burden, fast phase angle detection, and excellent harmonic rejection at nominal grid frequency. Unfortunately, due to spectral leakage at abnormal frequencies, conventional frequency adaptive PLLs bears inaccuracies in both magnitude and phase angle estimation. To resolve this situation, this study proposes an advanced frequency-adaptive PLL (AFA-PLL), which can work under abnormal grid frequencies or harmonics and avoid spectral leakage by implementing a variable window length phase detector. To achieve frequency adaptivity, the AFA-PLL innovatively employs a Fourier transformation-based sliding-mode controller (FTSMC). FTSMC utilizes a recursive interpretation of Fourier transform method by filtering the double frequency oscillations of the abnormal grid. Therefore, making the AFA-PLL highly capable of coping with abnormalities rapidly and effectively. Through extensive simulations and experiments under various abnormal grid conditions, the superior performance of the AFA-PLL is validated, which shows a 56 ms transient response, ±0.03 Hz oscillations and 3.23%. harmonics. Moreover, comprehensive comparison studies with recently proposed PLLs are conducted to further verify its effectiveness.

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Publication Details

Journal
IEEE Transactions on Industry Applications
Published
2024-12-31
DOI
https://doi.org/10.1109/tia.2024.3524481
Citations
3
Primary Topic
Microgrid Control and Optimization
Type
article
Field-Weighted Citation Impact
0.98

Funders

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article

An Advanced Frequency Adaptive PLL for Grid Connected Inverters Under Abnormal Grid Conditions

Sheikh Tanzim Meraj, Kamrul Hasan, Hieu Trinh, Peng Shi et al.
3 citations
IEEE Transactions on Industry Applications
Microgrid Control and Optimization
0.98
article

An Advanced Frequency Adaptive PLL for Grid Connected Inverters Under Abnormal Grid Conditions

Sheikh Tanzim Meraj, Kamrul Hasan, Hieu Trinh, Peng Shi, Samson S. Yu
article en
3 citations

Abstract

The necessity to expand the use of distributed renewable energy sources (DERS) with grid-connected inverters has emphasized the critical role of phase-locked loop (PLL) controllers in swiftly and accurately acquiring grid voltage phase angles, particularly under abnormal grid conditions. Frequency adaptive PLL has gained popularity due to its low computational burden, fast phase angle detection, and excellent harmonic rejection at nominal grid frequency. Unfortunately, due to spectral leakage at abnormal frequencies, conventional frequency adaptive PLLs bears inaccuracies in both magnitude and phase angle estimation. To resolve this situation, this study proposes an advanced frequency-adaptive PLL (AFA-PLL), which can work under abnormal grid frequencies or harmonics and avoid spectral leakage by implementing a variable window length phase detector. To achieve frequency adaptivity, the AFA-PLL innovatively employs a Fourier transformation-based sliding-mode controller (FTSMC). FTSMC utilizes a recursive interpretation of Fourier transform method by filtering the double frequency oscillations of the abnormal grid. Therefore, making the AFA-PLL highly capable of coping with abnormalities rapidly and effectively. Through extensive simulations and experiments under various abnormal grid conditions, the superior performance of the AFA-PLL is validated, which shows a 56 ms transient response, ±0.03 Hz oscillations and 3.23%. harmonics. Moreover, comprehensive comparison studies with recently proposed PLLs are conducted to further verify its effectiveness.

IEEE Transactions on Industry ApplicationsVol. 61(2)
Deakin University (AU), The University of Adelaide (AU)
Australian Research Council
Affordable and clean energy
Openalex Percentile: Top 22%
Microgrid Control and Optimization
0.98
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