A Tuned Whitening-Based Taylor-Kalman Filter for P Class Phasor Measurement Units

Bashian, Amir; Macii, David; Fontanelli, Daniele; Petri, Dario

doi:10.1109/tim.2022.3162274

Cited by 13 publications

(4 citation statements)

References 42 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…KF solutions are based on a set of statespace equations. These filters are widely used in power quality applications, such as realtime tracking harmonics [105][106][107][108], signal parameters estimation of transients [109,110]. The Kalman filter is a linear filter that can be applied to a linear system.…”

Section: Kalman Filtersmentioning

confidence: 99%

Power Quality Disturbances Characterization Using Signal Processing and Pattern Recognition Techniques: A Comprehensive Review

2023

View full text Add to dashboard Cite

Several factors affect existing electric power systems and negatively impact power quality (PQ): the high penetration of renewable and distributed sources that are based on power converters with or without energy storage, non-linear and unbalanced loads, and the deployment of electric vehicles. In addition, the power grid needs more improvement in the performances of real-time PQ monitoring, fault diagnosis, information technology, and advanced control and communication techniques. To overcome these challenges, it is imperative to re-evaluate power quality and requirements to build a smart, self-healing power grid. This will enable early detection of power system disturbances, maximize productivity, and minimize power system downtime. This paper provides an overview of the state-of-the-art signal processing- (SP) and pattern recognition-based power quality disturbances (PQDs) characterization techniques for monitoring purposes.

show abstract

Section: Kalman Filtersmentioning

confidence: 99%

Power Quality Disturbances Characterization Using Signal Processing and Pattern Recognition Techniques: A Comprehensive Review

2023

View full text Add to dashboard Cite

show abstract

Section: Introductionmentioning

confidence: 99%

“…To improve the accuracy of parameter estimation under dynamic signal changes, the Taylor series and its improved algorithm are further proposed in references [14][15][16][17][18][19]. The algorithms based on the Taylor series are Taylor Extended Kalman Filtering [14,15], adaptive algorithm [15], Maximally Fla Differentiators [17], Taylor weighted least squares (TWLS) [18], symmetric Taylor weighted least square (STWLS) [19], and so on. Based on Taylor series expansion, Bai et al [16] proposed an estimation algorithm to solve out-of-band interference based on Taylor series expansion, and the complexity of the proposed algorithm needs to be further reduced.…”

Section: Introductionmentioning

confidence: 99%

Design of a Multifrequency Signal Parameter Estimation Method for the Distribution Network Based on HIpST

Liu,

Liang,

Ding

et al. 2024

ENERGY

View full text Add to dashboard Cite

The application of traditional synchronous measurement methods is limited by frequent fluctuations of electrical signals and complex frequency components in distribution networks. Therefore, it is critical to find solutions to the issues of multifrequency parameter estimation and synchronous measurement estimation accuracy in the complex environment of distribution networks. By utilizing the multifrequency sensing capabilities of discrete Fourier transform signals and Taylor series for dynamic signal processing, a multifrequency signal estimation approach based on HT-IpDFT-STWLS (HIpST) for distribution networks is provided. First, by introducing the Hilbert transform (HT), the influence of noise on the estimation algorithm is reduced. Second, signal frequency components are obtained on the basis of the calculated signal envelope spectrum, and the interpolated discrete Fourier transform (IpDFT) frequency coarse estimation results are used as the initial values of symmetric Taylor weighted least squares (STWLS) to achieve high-precision parameter estimation under the dynamic changes of the signal, and the method increases the number of discrete Fourier. Third, the accuracy of this proposed method is verified by simulation analysis. Data show that this proposed method can accurately achieve the parameter estimation of multifrequency signals in distribution networks. This approach provides a solution for the application of phasor measurement units in distribution networks.

show abstract

“…To design efficient filters in order to mitigate the adverse effects of harmonics in the power waveforms, these harmonics are required to be accurately measured and estimated. Bashian et al proposed a Taylor Kalman filter (TKF) and tuned whitening-based TKF (TW-TKF) to filter the harmonics present in power system and also to mitigate abrupt changes in amplitudes and phases of AC current and voltage of AC signals expected to occur frequently in power grids [10][11][12]. Harmonic estimation is the first and foremost step that forms the basis for harmonic elimination.…”

Section: Introductionmentioning

confidence: 99%

Hybrid Weighted Least Square Multi-Verse Optimizer (WLS–MVO) Framework for Real-Time Estimation of Harmonics in Non-Linear Loads

et al. 2023

View full text Add to dashboard Cite

The electric power quality has become a serious concern for electric utilities and end users owing to its undesirable effects on system capabilities and performance. Harmonic levels on power systems have been pronounced to a greater extent with the continuous growth in the application of solid-state and reactive power compensatory devices. Harmonics are the key constituents that are mainly responsible for power quality deterioration. Power system harmonics need to be correctly estimated and filtered to increase power quality. This research work focuses on accurate estimation of power system harmonics with the proposed hybrid weighted least-square multi-verse optimizer (WLS–MVO) based framework. Multi-verse optimizer replicates the phenomenon of the formation of new universes as described by multi-verse theory to solve complex real-world optimization problems. The proposed WLS–MVO framework is tested and validated by estimating the harmonics present in multiple test signals with different noise levels. Amplitudes and phases of harmonics present in the polluted signal were estimated, and the framework computational time was compared with the previously developed technique’s results which are reported in the literature. There was 80% reduction in computational time and 82% improvement in terms of accuracy in estimating harmonics using WLS–MVO as compared to previously developed techniques. The performance of the developed framework is further validated by estimating the harmonics present in the real-time voltage and current waveforms obtained from axial flux permanent magnet generator (AFPMSG), uninterruptible power supply (UPS), and light-emitting diode (LED). The purposed technique technique outperforms the already-developed techniques, in terms of accuracy and computational time.

show abstract

A Tuned Whitening-Based Taylor-Kalman Filter for P Class Phasor Measurement Units

Cited by 13 publications

References 42 publications

Power Quality Disturbances Characterization Using Signal Processing and Pattern Recognition Techniques: A Comprehensive Review

Power Quality Disturbances Characterization Using Signal Processing and Pattern Recognition Techniques: A Comprehensive Review

Design of a Multifrequency Signal Parameter Estimation Method for the Distribution Network Based on HIpST

Hybrid Weighted Least Square Multi-Verse Optimizer (WLS–MVO) Framework for Real-Time Estimation of Harmonics in Non-Linear Loads

Contact Info

Product

Resources

About