DFT-based recursive group-harmonic energy distribution approach for power interharmonic identification

AbstractThe Discrete Fourier Transform (DFT) is still a widely used tool for analyzing and measuring both stationary and transient signals in power system harmonics. However, the misapplications of DFT can lead to incorrect results caused by some problems such as the aliasing effect, spectral leakage and picket-fence effect. The strategy of a DFT-based recursive Group-harmonic Energy Distribution (GED) algorithm is developed for system-wide harmonic/interharmonic evaluation in power systems. The proposed algorithm can restore individual dispersing spectral leakage energy caused by the DFT, and thus retrieve respective real harmonic/interharmonic value. Every distribution of energy minimizing iteration procedure for harmonic/interharmonic evaluation can be convergent fast, and therefore guarantee each harmonic/interharmonic magnitude and respective frequency approaches its actual value. Consequently, not only can high precision in integer harmonic measurement be retained, but also the interharmonics can be identified accurately, particularly under system frequency drift. A numerical example is presented to verify the proposed algorithm in terms of robust, fast and precise performance

Effects of modulation techniques on the input current interharmonics of Adjustable Speed Drives

Adjustable speed drives (ASDs) based on a three-phase front-end diode rectifier connected to a rearend inverter may generate interharmonic distortion in the grid. The interharmonic components can create power quality problems in the distribution networks such as interference with the ripple control signals, and consequently they can hamper the normal operation of the grid. This paper presents the effect of the symmetrical regularly sampled space vector modulation and discontinuous pulse width modulation-30° lag (DPWM2) techniques, as the most popular modulation methods in the ASD applications, on the drive's input current interharmonic magnitudes. Further investigations are also devoted to the cases where the random modulation technique is applied to the selected modulation strategies. The comparative results show how different modulation techniques can influence the ASD's input current interharmonics and consequently may not be a suitable choice of modulation from an interharmonics perspective. Finally, the theoretical analysis and simulation studies are validated with obtained experimental results on a 7.5-kW motor drive system

Online Detection of Fundamental and Inter-harmonics in AC Mains for Parallel Operation of Multiple Grid-Connected Power Converters

Parallel operation of multiple grid-connected power converters through LCL filters is known to have the potential problem of triggering oscillations in the ac mains. Such oscillatory frequencies are not integral multiples of the fundamental frequency and hence form a new source of interharmonics. Early detection of such oscillations is essential for the parallel power converters to move out of the unstable zone. This paper presents an online observer-based algorithm that can perform fast detection of interharmonics within a specified frequency band. The algorithm has been adopted in a specific and reduced form from an integral observer algorithm for detection of fundamental and interharmonic voltage components in the ac mains. A new method based on the kernel signal for fast interharmonic detection is proposed and practically verified. It has been implemented in a digital controller to detect oscillations such as those occurring between two grid-connected power converters. The practical results indicate that the algorithm can locate such frequency within the specific frequency band within 1 mains cycle

Spectral kurtosis based methodology for the identification of stationary load signatures in electrical signals from a sustainable building

Producción CientíficaThe increasing use of nonlinear loads in the power grid introduces some unwanted effects, such as harmonic and interharmonic contamination. Since the existence of spectral contamination causes waveform distortion that may be harmful to the loads that are connected to the grid, it is important to identify the frequency components that are related to specific loads in order to determine how relevant their contribution is to the waveform distortion levels. Due to the diversity of frequency components that are merged in an electrical signal, it is a challenging task to discriminate the relevant frequencies from those that are not. Therefore, it is necessary to develop techniques that allow performing this selection in an efficient way. This paper proposes the use of spectral kurtosis for the identification of stationary frequency components in electrical signals along the day in a sustainable building. Then, the behavior of the identified frequencies is analyzed to determine which of the loads connected to the grid are introducing them. Experimentation is performed in a sustainable building where, besides the loads associated with the normal operation of the building, there are several power electronics equipment that is used for the electric generation process from renewable sources. Results prove that using the proposed methodology it is possible to detect the behavior of specific loads, such as office equipment and air conditioning.Universidad de Valladolid y Consejo Mexicano de Ciencia y Tecnología (CONACYT) - (grant 743842)Universidad Autónoma de Querétaro, Fondo para el Desarrollo del Conocimiento (FONDEC-UAQ 2020) - (project FIN202011

Harmonic Estimation Of Distorted Power Signals Using PSO – Adaline

In recent times, power system harmonics has got a great deal of interest by many Power system Engineers. It is primarily due to the fact that non-linear loads comprise an increasing portion of the total load for a typical industrial plant. This increase in proportion of non-linear load and due to increased use of semi-conductor based power processors by utility companies has detoriated the Power Quality. Harmonics are a mathematical way of describing distortion in voltage or current waveform. The term harmonic refers to a component of a waveform occurs at an integer multiple of the fundamental frequency. Several methods had been proposed, such as discrete Fourier transforms, least square error technique, Kalman filtering, adaptive notch filters etc; Unlike above techniques, which treat harmonic estimation as completely non-linear problem there are some other hybrid techniques like Genetic Algorithm (GA), LS-Adaline, LS-PSOPC which decompose the problem of harmonic estimation into linear and non-linear problem. The results of LS-PSOPC and LS-Adaline has most attractive features of compactness and fastness. . Our new proposed technique tries to reduce the pitfalls in the LS-PSOPC, LS-Adaline techniques. With new technique we tried to estimate the Amplitudes by Least square estimator, frequency of the signal by PSOPC and phases of the harmonics by Adaline technique using MATLAB program. Harmonic signals were estimated by using LS-PSOPC, PSOPC-Adaline. Errors in estimating the signal by both the techniques are calculated and compared with each other

Selection of the Most Suitable Decomposition Filter for the Measurement of Fluctuating Harmonics

The proliferation of nonlinear loads in both industrial and residential distribution grids leads to undesirable nonsinusoidal and fluctuating harmonic pollution on voltage and current waveforms. New analysis tools, such as wavelets, are being used to overcome the problems posed by the use of the Fourier transform when analyzing complex waveforms. Nevertheless, the selection of the wavelet basis must be done carefully to minimize spectral leakage due to the nonexact frequency discrimination. In this context, this paper proposes an objective method for comparing different wavelet families for the measurement of harmonic contents. This methodology is applicable for determining the best filter among the 53 preselected structures according to the following requirements: frequency selectivity, computational complexity, convolution results, and observed spectral leakage. With all these considerations, the Butterworth infinite-impulse response filter of order 29 was found to be the best wavelet decomposition structure to achieve an effective harmonic analysis up to the 50th order