An Application of Spectral Kurtosis to Separate Hybrid Power Quality Events

Abstract

For the development of the future smart grid, the detection of power quality events is a key issue for the power system monitoring. Voltage sags, swells, harmonics (variations) and interruptions, which produce large losses for commercial and industrial consumers, are the main events to be considered due to the sensitivity of equipment to these electrical anomalies. The steady-state events are even more frequently accompanied by transients, the discrimination and localization being far more exigent and requiring advanced signal separating tools to be incorporated in the measurement equipment. This paper shows the event detection performance of the spectral kurtosis as a signal separating tool in the frequency domain. The disturbances under test are hybrid signals resulting from the coupling between amplitude defects and non-desired higher frequencies. Being a fourth-order spectrum, the kurtosis is confirmed as a noise-resistant tool that enhances impulsiveness, therefore characterizing the electrical anomalies. In the beginning of the analysis, the voltage sag is established as a reference; then, the disturbances (oscillatory transients and harmonics) are coupled at the starting and ending instants of the sag, resulting in complex hybrid events. The results show that the spectral kurtosis enhances the detection Energies 2015, 8 9778 of both types of events (steady state and transients), which are outlined in a bump shape in the fourth-order frequency pattern and centered in the main carrier frequency. Indeed, while the oscillatory transients are associated with softer and lower-amplitude peaks, the harmonics correspond to crisper and higher ones. As these mixed electrical faults are very common in the actual power grid, the article postulates the higher-order spectra to be implemented in prospective online measurement instruments.

An Embedded Sensor Node for the Surveillance of Power Quality

“…This does not exclude the possibility to apply higher-order statistics (HOS) and Kurtosis procedures. However, the HOS evaluation is more oriented to harmonic analysis (spectral kurtosis) [5][6][7]. Basically, the arithmetic average value per cycle and the previous average calculated during many cycles provide information about the voltage waveform integrity and the supply continuity (interruptions).…”

“…As discussed in Section 2.2.1., the minimized Kalman filter to estimate simply amplitude A of the sinusoid A sin(ω•t), leads to the implementation of Equations (4) and (5), implementing the following pseudocode sequence:…”

“…As discussed in Section 2.2.1., the minimized Kalman filter to estimate simply amplitude A of the sinusoid A sin(ω•t), leads to the implementation of Equations (4) and (5), implementing the following pseudocode sequence: Three arrays are required: one to contain the instantaneous samples input voltage (256 words) and two more to the consecutive previous periods (512 words); two fixed-point multiplications are required too.…”

Power Quality Disturbances Assessment during Unintentional Islanding Scenarios. A Contribution to Voltage Sag Studies

“…Furthermore, other research has been focused on how to identify the different type of disturbances from occurring events; for instance, in References [6][7][8][9][10][11]. Once PQ disturbances are detected, classifying them and compressing them into separate events is a challenging task and requires advanced tools; see References [12][13][14][15]. Some authors have considered fuzzy logic or neural networks to classify them [16][17][18][19], some others proceed based on clustering the data depending on its origin from offline and prescribed events [20,21], and lastly, certain studies have focused on real-time classification, which results in a successful classification; for instance, see References [22][23][24].…”

Application of Spectral Kurtosis to Characterize Amplitude Variability in Power Systems’ Harmonics

“…Therefore, DFT will be compared with Spectral Kurtosis (SK), a fourth-order technique (HOS), which shows a very good capacity for different stationary signals [15,16]. It has been previously used in PQ evaluation in [17][18][19] (in addition to other fields, such as insect detection based on vibration [20] or the main application up to now, which is fault detection in rotatory machines [21]), where SK was used for the detection of PQ events, as well as their characterization. In this work, the best configuration for DFT and SK will be studied, for the detection of frequency components with a constant amplitude trend.…”