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The wide bandwidth of phase-locked loop (PLL) will increase the negative real part of the output impedance of the grid-connected inverter (GCI), thus destroying the stability of the weak grids. This article proposes a novel method to improve the system stability through decoupling the PLL and grid impedance. Initially, the coupling relationship between PLL and grid impedance is revealed. It can explain why the choice of PLL bandwidth and the grid impedance magnitude is limited. Then, the decoupling method is proposed where the primary control structure of GCI does not need to change and uses the structured voltage, the product of PCC voltage and grid admittance, as the improved input of PLL. The proposed method can achieve the full-frequency passive of the output impedance of GCI even if the PLL has high bandwidth and the impedance measurement error is up to 60%, which means the adverse stability effect of PLL on the system is eliminated. The theoretical analysis is verified by simulations and experiments. [ABSTRACT FROM AUTHOR]

Arriving at an accurate and fast amplitude estimation of the sine-wave distorted by harmonics and noise is important for the control of voltage source inverters in grid-connected photovoltaic system. In this article, the three-point interpolation discrete Fourier transform method based on the maximum sidelobe decay windows is proposed for accurate amplitude estimation. The proposed amplitude estimator is speeded-up by using the guaranteed stable recursive method. The influence of noise on the proposed amplitude estimator is investigated, and the amplitude estimation error caused by the spectral interference is also analyzed. The accuracy and effectiveness of the proposed method are verified through simulation and experiments, where the state-of-art amplitude estimation methods and the boundaries specified in the Standard IEEE C37.118.1-2011 are considered. [ABSTRACT FROM AUTHOR]

Out-of-band interference (OOBI) test is a bench-mark test for M-class phasor measurement units (PMUs) in IEEE/IEC 60255–118-1-2018 and C37.118.1a-2014. Because of the spectral interference produced by interharmonic, it is difficult for dynamic phasor estimators to satisfy the OOBI test requirements with a short observation time. To this end, this article proposed a Taylor weighted least squares (TWLS) method based on the matrix pencil for the dynamic phasor estimation of the OOBI contaminated signal. The proposed method first applies the matrix pencil algorithm to obtain rough estimations for the frequencies of the fundamental component and other components (i.e., harmonics, subharmonics, and interharmonics) within a few cycles. Then, the TWLS method was adopted to acquire more accurate estimations of the dynamic phasor and frequencies. The effectiveness of the proposed method is validated by simulations under steady and dynamic conditions that follow the requirements of the IEEE standard. [ABSTRACT FROM AUTHOR]

Automatic seizure prediction promotes the development of closed-loop treatment system on intractable epilepsy. In this study, by considering the specific information exchange between EEG channels from the perspective of whole brain activities, the convolution neural network (CNN) and the directed transfer function (DTF) were merged to present a novel method for patient-specific seizure prediction. Firstly, the intracranial electroencephalogram (iEEG) signals were segmented and the information flow features of iEEG signals were calculated by using the DTF algorithm. Then, these features were reconstructed as the channel-frequency maps according to channel pairs and the frequency of information flow. Finally, these maps were fed into the CNN model and the outputs were post-processed by the moving average approach to predict the epileptic seizures. By the evaluation of cross-validation method, the proposed algorithm achieved the averaged sensitivity of 90.8%, the averaged false prediction rate of 0.08 per hour. Compared to the random predictor and other existing algorithms tested on the Freiburg EEG dataset, our proposed method achieved better performance for seizure prediction in all patients. These results demonstrated that the proposed algorithm could provide an robust seizure prediction solution by using deep learning to capture the brain network changes of iEEG signals from epileptic patients. [ABSTRACT FROM AUTHOR]

The estimations of amplitude and phase are of great importance in the synchronous phasor measurement for power systems. In addition to the off-nominal frequency, the amplitude and phase estimations accuracy level of the power system signal is affected by the inevitable noise. In this article, the effect of white noise on amplitude and phase estimations provided by DFT-based frequency shifting and filtering algorithm (FSF) is analyzed. With the help of the equivalent weighting filter’s merits, i.e., equivalent noise bandwidth and overlap correlation, the FSF-based amplitude and phase variance expressions are derived theoretically by considering the overlap of two processed samples. The effectiveness of the proposed amplitude and phase variance expressions are verified through computer simulations. [ABSTRACT FROM AUTHOR]

The frequency shifting and filtering (FSF) algorithm, a variant of DFT, has the merit of high efficiency for frequency analysis thanks to its simple implementation in the time domain. However, the inevitable white noise injected by various factors leads to inaccurate frequency estimation in practical measurement. This article investigates the influence of a stationary white noise on FSF-based frequency estimation of the power system. The variance expression of the frequency estimator is derived theoretically and compared to its unbiased Cramer–Rao lower bound (CRLB). The obtained results are validated by several computer simulations. [ABSTRACT FROM AUTHOR]

Different from the fast Fourier transform-based method, the frequency shifting and filtering (FSF) algorithm employs only a few simple operations in the time domain for harmonic analysis. However, the systematic error of FSF caused by the imperfect performance of the low-pass filter is ignored. In this paper, a novel smoothing frequency shifting and filtering (SFSF) algorithm is proposed. First, the systematic error of FSF is modeled. Then, the SFSF-based harmonic analysis with systematic error compensation is presented. Finally, the features of the SFSF are discussed. Simulation shows good agreement with the theoretical results. Results of simulations and experiment confirm that the SFSF method can perform harmonic analysis accurately. [ABSTRACT FROM AUTHOR]

The estimations of amplitude and phase are of great importance in the synchronous phasor measurement for power systems. In addition to the off-nominal frequency, the amplitude and phase estimations accuracy level of the power system signal is affected by the inevitable noise. In this article, the effect of white noise on amplitude and phase estimations provided by DFT-based frequency shifting and filtering algorithm (FSF) is analyzed. With the help of the equivalent weighting filter’s merits, i.e., equivalent noise bandwidth and overlap correlation, the FSF-based amplitude and phase variance expressions are derived theoretically by considering the overlap of two processed samples. The effectiveness of the proposed amplitude and phase variance expressions are verified through computer simulations. [ABSTRACT FROM AUTHOR]

Harmonic estimation plays an important part in harmonic suppression of power system. Due to the normal fluctuation of power frequency, it is difficult to realize synchronous sampling. Consequently, the unavoidable productions, i.e., spectral leakage and picket fence effect, will affect the accuracy of harmonic analysis significantly when using the Fourier transform. To overcome this problem, a novel algorithm for power system harmonic estimation called frequency shifting and filtering (FSF) algorithm is proposed in this paper. A reference signal is at first generated to shift the frequency of the sampled signal. Then the iterative averaging filter is adopted to eliminate the spectral interferences. Finally, accurate estimation of harmonics can be achieved because only interested components are retained. Furthermore, a simplified FSF with much less computational burden is presented by using an equivalent weighting filter. The salient features of the proposed algorithm are validated by the simulations and practical experiments. [ABSTRACT FROM AUTHOR]