The increasing trend towards renewable energy sources requires higher power quality (PQ) at the generation, transmission and distribution systems. The PQ disturbances are produced due to the nonlinear loads, power electronic converters, system faults and switching events. The utilities and consumers of electric power are expected to acquire ideal voltage and current waveforms at rated power frequency. The development of new techniques for the automatic classification of PQ events is at present a major concern. This paper presents a comprehensive literature review on the applications of digital signal processing, artificial intelligence and optimization techniques in the classification of PQ disturbances. Various signal processing techniques used for the feature extraction such as Fourier transform, wavelet transform, S-transform, Hilbert transform, Gabor transform and their hybrids have been reviewed. The artificial intelligent techniques used for the pattern recognition such as artificial neural network, fuzzy logic, support vector machine are reviewed in detail. The optimization techniques used for the optimal feature selection such as genetic algorithm, particle swarm optimization and ant colony optimization are also reviewed. A comparison of various classification systems is presented in tabular form which highlights the important techniques used in the field of PQ disturbance monitoring. The comparison of research works carried out on the classification of PQ disturbances points out that many researchers have focussed on the feature extraction and classification techniques. Only few authors have used the feature selection techniques for selecting the best suitable features. This review may be considered a valuable source for researchers as a reference point to explore the opportunities for further improvement in the field of PQ classification.

A comprehensive overview on signal processing and artificial intelligence techniques applications in classification of power quality disturbances

Harmonics estimation in emerging power system: Key issues and challenges

The interharmonics, which are the same as integer harmonics, have serious impacts on the design of harmonics compensation equipment. Therefore, it is important to measure interharmonics accurately. The interharmonics cannot be obtained accurately by using fast Fourier transform (FFT) for an unsynchronized sample sequence analysis because of large errors in such cases. To reduce the errors caused by using FFT for an unsynchronized sample sequence analysis and to improve the measuring precision of interharmonics in electric power systems, an interharmonics estimation method based on the interpolation FFT algorithm is proposed. An algorithm for estimating interharmonics parameters based on the Blackman-Harris window, Rife-Vincent (I) window, and Rife-Vincent (III) window is given. Simulation results demonstrate that by using the proposed algorithm for the unsynchronized sample sequence analysis, the estimated interharmonics frequency, amplitude, and phase are highly accurate

Interharmonics Analysis Based on Interpolating Windowed FFT Algorithm

Harmonic estimation is an important topic in power system signal processing. Windowed interpolation fast Fourier transformation (WIFFT) is an efficient algorithm for power system harmonic estimation, which can eliminate the errors caused by spectral leakage and picket fence effect. However, the fitting polynomial in the interpolation procedure contains both even and odd terms, and this increases the computational burden. This paper proposes a simple symmetrical interpolation FFT algorithm, where the even terms are removed from the fitting polynomial based on the triangular self-convolution windows (TSCW). The polynomials for frequency and amplitude computations are provided. Considerable leakage errors and harmonic interferences can be suppressed by the TSCW. Accurate estimations of harmonic parameters can be obtained via the fitting polynomial and the TSCW, both with adjustable order to fulfill different accuracy and speed requirements of practical power harmonic measurement. Simulation results and measurements have validated the proposed method.

Harmonic Estimation Using Symmetrical Interpolation FFT Based on Triangular Self-Convolution Window

Centralized control, which can overcome the ill interactional effects among decentralized controllers, impels a real need for fast and reliable computational algorithms to improve the accuracy of phasor and power measurements. This paper deals with discrete Fourier transform (DFT)-based measurement techniques. Based on the practical frequency tracking method proposed by the same authors in another paper, this paper develops practical compensation method to improve the phasor and power measurement accuracy of the DFT algorithm. The method proposed by this paper takes full advantage of the DFT algorithm. It simply modifies the DFT results. With notable accuracy improvement, the calculation burden of the proposed method is little more than the DFT algorithm. The method can be used for on-line purposes. Though the analog signal studied in this paper is sinusoidal signal, the method proposed by this paper has good performance in the presence of harmonics. Some examples are given to demonstrate the feasibility, simpleness and robustness of the proposed method.

A practical method to improve phasor and power measurement accuracy of DFT algorithm

The fast Fourier transform (FFT) cannot be directly used in the harmonic analysis of an electric power system because of its higher errors, especially the phase error. This paper discusses the leakage phenomenon of FFT and presents a new amending algorithm, poly-item cosine window interpolation, which is based on the interpolating algorithm proposed by V. Jain and T Grandke. This new algorithm improves the accuracy of the FFT, so it can be applied to the precision analysis for electrical harmonics. The simulation result shows that applying different windows has different effects on the accuracy, and the Blackman-Harris window has the highest accuracy.

Zhongxing Geng

Papers

The algorithm of interpolating windowed FFT for harmonic analysis of electric power system