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

A survey of techniques applied to non-stationary waveforms in electrical power systems

The well-known and ever-present time-varying and non-stationary nature of waveforms in power systems requires a comprehensive and precise analytical basis that needs to be incorporated in the system studies and analyses. This time-varying behavior is due to continuous changes in system configurations, linear load levels and operating modes of nonlinear load / equipment and thus present conceptual and practical challenges. The objective of this paper is to provide a comprehensive bibliographical survey of the proposed techniques to deal with time-varying and non-stationary waveforms in power systems

An overview of measurement standards for power quality

Received: December 7th, 2020 ; Accepted: April 7th, 2021 ; Published: May 13th, 2021 ; Correspondence: [email protected] Quality (PQ) is a vital aspect of electrical power systems, which cannot be neglected anymore, as an ample PQ guarantees the essential compatibility between consumer equipment and the electricity network. The analysis of electrical parameters related to distributing electricity is recognized as a complex engineering problem. It remains a critical task to maintain and improve PQ in modern evolving networks as the overall system performance highly depends on it. Future smart grids will also require a further increase in PQ levels in terms of observability, affordability, data exchange, flexibility, and net metering, thus making the network much more complex as it will be featuring a large amount of variable renewable-based distributed generation. This will further require the need for the introduction of novel, efficient and intelligent monitoring, control, and communication systems with various demand manageable resources. In this paper, a review and comparisons have been made for different IEEE and IEC measurement standards that are used for PQ with a specific focus on harmonic distortion as it is one of the most important parameters in PQ and some guidelines have been suggested for future electricity networks

A new method for analysis of signal harmonic distortion byevaluation of power quality

Naučna rasprava izložena u ovoj tezi bavi se analizom kvaliteta električne energije. Visok nivo električne energije podrazumeva da su napon napajanja i struja potrošača idealne sinusoide sa tačno određenom amplitudom i učestanošću. Bilo kakva odstupanja od idealnog nazivaju se izobličenja i najčešće se karakterišu sa harmonicima. Poslednjih godina dolazi do naglog razvoja poluprovodničkih komponenata. Takve komponente su uticale na ubrzan razvoj snažnih uređaja energetske elektronike. Ti uređaji su nelinearnog karaktera, što dovodi do pojave harmonika u signalima napona i struja elektroenergetskog sistema. Prvi problem kojim se bavi ova teza je analiza talasnih oblika struja ispravljača. Metode primenjene za analizu su wavelet transformacija (VT) i modulated overlapped transformacija (MLT). MLT nadoknađuje nedostatak VT da dekomponuje signal u odgovarajuće podopsege koji mogu sadržati i više harmonika i daje tačnu informaciju o svakom harmoniku. Obe metode su pogodne za offline analizu. Za online analizu predložen je hibridni metod baziran na diskretnoj Furijeovoj transformaciji (DFT) i adaptivnom pojasnom filteru (EPLL). Hibridni metod je zadržao dinamički odziv DFT-a, dok je EPLL obezbedio sinhronizaciju sa osnovnom učestanošću sistema. Hibridni metod daje dovoljno tačnu informaciju o osnovnom i višim harmonicima samo ako su njihove učestanosti ceolobrojni umnožak učestanosti osnovnog harmonika. U slučaju pojave interharmonika, odnosno kada taj odnos više ne važi, hibridni metod ne daje tačne rezultate. Za analizu takvih signala predložen je novi metod, koji je baziran na adaptivnom diskretnom pojasnom filteru (ANF) t.j. metod koristi diskretni pojasni filter za modelovanje harmonijskih komponenata u ulaznom signalu, dok se prošireni Kalmanov filter (EKF) koristi kao adaptivni mehanizam. Novi metod je preuzeo osobinu ANF-a da može adaptivno da prati promene učestanosti i osobinu EKF-a da ima bolji dinamički odziv. Metode su implementirane na digitalnom procesoru za obradu signala i upoređene sa postojećim metodama. Metode pokazuju prednosti u odnosu na druge metode.Scientific research in this thesis discusses power quality analysis. High power quality assumes that both the voltage power supply and the load current are ideal sinusoidal signals with a precisely defined amplitude and frequency. Any deviations from this ideal vaweform are considered as distortion and are characterised by harmonics. Over the last few decades, there has been a rapid development of semiconductor components. Such components made an impact on the fast development of power electronics devices. These devices are nonlinear, introducing harmonics in both voltage and current of the power grid. The first issue researched in this thesis is the analysis of the rectifier voltage and current waveforms. Methods used for the analysis are the wavelet transform (WT) and the modulated overlapped transform (MLT). The MLT overcomes the drawback of the WT, which decomposes the signal into subbands that can contain more harmonics, and gives accurate information about every harmonic. Both methods are suitable for offline analysis. For online analysis, a hybrid method is proposed, based on the discrete Fourier transform (DFT) and the adaptive notch filter (EPLL). The hybrid method retains a good dynamic response of the DFT whereas the EPLL provides a synchronisation with the fundamental system frequency. The hybrid method provides accurate information on the fundamental and the higher harmonics only if their frequencies are integer multiples of the fundamental frequency. In the case of interharmonics, i.e. when this integer ratio is not valid, the hybrid method does not provide accurate results. In order to analyse such signals, a new method is proposed. It is based on discrete adaptive notch filter (ANF), i.e. the method uses a discrete notch filter for modeling the harmonic components in the input signal, whereas an Extended Kalman Filter (EKF) is used as an adaptation algorithm. The adaptive notch Kalman filter inherited the property of the ANF to adaptively track changes in the frequency and the property of the EKF to have a faster dynamic response. Methods have been implemented in a digital signal processor and compared with the existing ones. The methods show advantages compared to other methods

A study of the effects of time aggregation and overlapping within the framework of IEC standards for the measurement of harmonics and interharmonics

Producción CientíficaThe increasing incorporation of power electronics and other non-linear loads, in addition to their energy advantages, also implies a poor power quality, especially as regards harmonic pollution. Different solutions have been proposed to measure harmonic content, taking the International Electrotechnical Commission (IEC) standards as a reference. However, there are still some issues related to the measurement of the harmonic, and especially, interharmonic content. Some of those questions are addressed in this work, such as the problem derived from the instability of the values obtained by applying the discrete Fourier transform to each sampling window, or the appearance of local peaks when there are tones separated by multiples of the resolution. Solutions were proposed based on time aggregation and the overlapping of windows. The results demonstrate that aggregation time, window type, and overlapping can improve the accuracy in harmonic measurement using Fourier transform-based methods, as defined in the standards. The paper shows the need to consider spectral and time groupings together, improving results by using an appropriate percentage of overlap and an adaptation of the aggregation time to the harmonic content

Recursive Parametric Frequency/Spectrum Estimation for Nonstationary Signals With Impulsive Components Using Variable Forgetting Factor

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Fault Detection of Wind Turbine Induction Generators through Current Signals and Various Signal Processing Techniques

Producción CientíficaIn the wind industry (WI), a robust and effective maintenance system is essential. To minimize the maintenance cost, a large number of methodologies and mathematical models for predictive maintenance have been developed. Fault detection and diagnosis are carried out by processing and analyzing various types of signals, with the vibration signal predominating. In addition, most of the published proposals for wind turbine (WT) fault detection and diagnosis have used simulations and test benches. Based on previous work, this research report focuses on fault diagnosis, in this case using the electrical signal from an operating WT electric generator and applying various signal analysis and processing techniques to compare the effectiveness of each. The WT used for this research is 20 years old and works with a squirrel-cage induction generator (SCIG) which, according to the wind farm control systems, was fault-free. As a result, it has been possible to verify the feasibility of using the current signal to detect and diagnose faults through spectral analysis (SA) using a fast Fourier transform (FFT), periodogram, spectrogram, and scalogram