Wenjiang Pei

A Complex Least Squares Enhanced Smart DFT Technique for Power System Frequency Estimation

A complex-valued least-squares (CLS) framework is proposed in order to enhance the accuracy of the smart discrete Fourier transform (SDFT) algorithms for power system frequency estimation in the presence of noise and harmonic pollution. It is first established that the underlying time-series relationship among the consecutive DFT fundamental components employed by the original SDFT algorithms does not hold when noises or unexpected higher order harmonics are present, resulting in suboptimal estimation performances. To eliminate these adverse effects on the frequency estimation, the degree of the relationship breakdown is next quantified via a model mismatch error vector. The CLS technique is then employed to minimize the mean-square model deviation when the SDFT voltage modelling is suboptimal. The proposed CLS-enhanced SDFT (CLS-SDFT) methods are shown to be more accurate than the original ones in heavily noisy and harmonic-distorted environments, typical scenarios in online frequency estimation. The benefits of the SDFT framework are verified by simulations for various power system conditions, as well as for real-world measurements.

A least squares enhanced smart DFT technique for frequency estimation of unbalanced three-phase power systems

The problem of off-nominal frequency estimation in unbalanced three-phase power systems is addressed from the frequency domain perspective. It is first established that the original Smart discrete Fourier transform (SDFT) technique designed for real-valued single-phase voltage can be extended to deal with complex-valued αβ transformed voltage. By observing that the underlying time series relationship among the consecutive DFT fundamental components employed by SDFT technique does not hold when noise or unexpected higher order harmonics are present, resulting in suboptimal estimation performances, the least squares framework is then built upon the underlying relationship among the consecutive DFT fundamental components to minimise the mean square model error. The benefits of the proposed LS-SDFT over the time-domain widely linear least squares (WL-LS) frequency estimator are verified by simulations for unbalanced power system conditions in the presence of noise and higher order harmonic pollution, as well as for real-world measurements.

Initial Phase Estimation of Single-Tone Signal Based on Fast Filter Bank

In this paper, an initial phase estimation of single-tone signal is proposed based on the Fast Filter Bank (FFB). With the help of characteristics of FFB such as narrower transition width and higher stopband attenuation and low complexity, the proposed initial phase estimation based on FFB is more accurate than that of based on FFT, and the phase estimation can be also estimated without correction regardless of whether there is deviation of frequency. Simulation explains the better performance of estimating initial phase based on FFB and the method can be extended to estimate other parameters such as magnitude of the single-tone signal in a similar way.

A balancing voltage transformation for robust frequency estimation in unbalanced power systems

This paper addresses the detection of the fundamental frequency of power systems under unbalanced and distorted conditions. By using the second order information, both the autocorrelation and pseudo-autocorrelation, within the Clarkes transformed voltage, a novel balancing voltage transformation (BVT) is proposed to accurately detect the underlying phase angle evolution of the positive sequence component. This removes the biggest obstacle in current power systems and makes possible to use any frequency estimator for single-tone exponential on unbalanced power systems. The robustness of the proposed phase angle detection technique is illustrated for two well-known and efficient frequency estimators, that is, a discrete Fourier transform (DFT) coefficient interpolation method [1] and the weighted linear predictor (WLP) [2]. A window technique is used to cater for the fast and computationally affordable frequency estimation purposes. Simulations over a range of unbalanced conditions, including voltage dips and swells, frequency deviations and the presence of higher order harmonics support the analysis.

Widely linear adaptive frequency estimation for unbalanced three-phase power systems with multiple noisy measurements

We address the problem of adaptive frequency estimation of unbalanced three-phase power systems in practical situations when the voltage samples are contaminated with measurement noise. The complex-valued-transformed voltages are used in order to utilise all the available information in the three-phase reference channels, at the expense of modest addition in computational complexity. A widely linear predictive model is established over multiple noisy voltage measurements to cater for the system unbalance conditions, which are manifested in noncircular empirical distributions. To obtain frequency estimates in an adaptive manner, the total least-squares fitting and gradient descent optimisation techniques are adopted based on the augmented complex statistics. The so introduced augmented complex total least mean square (ACTLMS) algorithm is shown to enable, by design, more reliable frequency estimates over its augmented complex least mean square (ACLMS) counterpart. The ACTLMS is also shown to provide the user with a choice in the degrees of freedom to control the trade-off between tracking speed and estimation accuracy. Simulations on both synthetic and real-world noisy unbalanced power systems support the analysis.

Baseband signal processing of digital phosphor technology with high accuracy

A high-accuracy baseband signal processing system of digital phosphor technology for real-time spectrum analysis is proposed based on fast filter bank (FFB). The modular instruments based platform is utilized to verify the performance of the proposed scheme implemented with fieldprogrammable gate array (FPGA) module. With the single-tone signal as a test signal, the experimental results show that the proposed scheme can improve the accuracy of the real-time spectrum analysis at the cost of slightly higher complexity than that of fast Fourier transform (FFT) based scheme.