Jacek Rezmer

Real-time determination of power system frequency

The main frequency is an important parameter of an electrical power system. The frequency can change over a small range due to generation-load mismatches. Some power system protection and control applications, e,g, frequency relay for load shedding, load-frequency controller, require accurate and fast estimation of the frequency. Most digital algorithms for measuring frequency have acceptable accuracy if voltage waveforms are not distorted. However, due to nonlinear devices, e,g, semiconductor rectifiers, electric arc furnaces, the voltage waveforms can include higher harmonics. The paper presents a new method of measurement of power system frequency, based on digital filtering and Pronys estimation method. Simulation results confirm, that the proposed method is more accurate than others, e,g, than the method based on the measurement of angular velocity of the rotating voltage phasor.

Measurement of IEC Groups and Subgroups using Advanced Spectrum Estimation Methods

The International Electrotechnical Commission (IEC) standards characterize the waveform distortions in power systems with the amplitudes of harmonic and interharmonic groups and subgroups. These groups/subgroups utilize the waveform spectral components obtained from a fixed frequency-resolution discrete Fourier transform (DFT). Using the IEC standards allows for a compromise among the different goals, such as the needs for accuracy, simplification, and unification. In some cases, however, the power-system waveforms are characterized by spectral components that the DFT cannot capture with enough accuracy due to the fixed frequency resolution and/or the spectral leakage phenomenon. This paper investigates the possibility of a group/subgroup evaluation using the following advanced spectrum estimation methods: adaptive Prony, estimation of signal parameters via rotational invariance techniques, and root multiple-signal classification (MUSIC). These adaptive methods use variable lengths of time windows of analysis to ensure the best fit of the waveforms; they are not characterized by the fixed frequency resolution and do not suffer from the spectral leakage phenomenon. This paper also presents the results of the applications of these methods to three test waveforms, to current and voltage waveforms obtained from simulations of a real DC arc-furnace plant, and to waveforms measured at the point of common coupling of the low-voltage network supplying a high-performance laser printer.

Analysis of power system transients using wavelets and Prony method

Transients resulting from switching of capacitor banks in electrical distribution systems affects power quality. The transient overvoltages can theoretically reach peak phase to earth values in the order of 2.0 p.u. High current transients can reach values to ten times the capacitor nominal current with duration of several milliseconds. Another severe operating condition is the switching on a second capacitor bank connected to the same bus. In the work, the characteristics of the transients are analyzed. The time of the beginning of a transient process is detected using a wavelet transform. The frequencies of transient components have been investigated applying the Fourier technique and the Prony model. The investigations show the advantages of the methods basing on the Prony model, over the Fourier technique. A distribution system was simulated using the EMTP software.

Computation of voltage sag initiation with Fourier based algorithm, Kalman filter and Wavelets

Dynamic Voltage Restorers (DVR) have been successfully applied for voltage dip mitigation in the last years. Especially in systems with nonlinear loads and wind turbine generation DVR units support the Power Quality enhancement. The reliability and quality of DVR operation depends mostly on fast and accurate voltage dip detection. Detection methodologies must be able to detect a voltage dip as fast as possible and be immune to other types of perturbations. In this paper we address the problem of voltage dip estimation using carefully selected advanced signal processing methods such as Fourier based algorithm, Kalman filtering and Wavelets. Additionally, the traditional and common technique of RMS value tracking has been mentioned. The algorithms have been tested under different conditions: voltage dip with phase jump, noise, frequency variations.

Application of advanced signal processing methods for accurate detection of voltage dips

Custom Power Devices like the dynamic voltage restorer have been applied for voltage dip mitigation in the last years. These electronic equipments need fast and reliable voltage dip detection algorithms. Such detection methodologies must be able to detect a voltage dip as fast as possible and be immune to other types of perturbations. In this paper we address the problem of voltage dip estimation by using different advanced signal processing methods such as Kalman filtering, Fourier based algorithms and Wavelet processing. The three algorithms have been tested under different conditions: voltage dip with phase jump, noise, frequency variations. The final implementation on a Texas Instrument DSP TMS320F2812DSP has been done.

Prony and nonlinear regression methods used for determination of transient parameters in wind energy conversion system

Wind converters impact on power quality is crucial for power system operation. This paper presents assessment of transients originating in a system with induction generator driven by wind turbine and compensated by capacitor bank. Prony algorithm and wavelets have been applied to determine signal parameters in different operation modes of wind generation unit. Detailed power quality studies on transients are helpful in better assessment of the phenomena.

Evolutionary algorithm for detection and localization of faults in HVDC systems

The aim of this work is to analyze evolutionary algorithms in point of application for detection and localization of faults in HVDC systems. Considered faults are localized at DC side. The initial condition for the algorithm is low sampling rate up to 5-100kHz. This condition eliminates application of traditional traveling wave technique due to not sufficient time resolution. It is proposed to base criterion of the fault location on relation between distance of the fault and amplitude of aperiodic decaying component in current during transient. In order to estimate the amplitude of the aperiodic component a genetic algorithm is proposed. Using benchmarking signals a reference function of distance of the fault in relation to the amplitude of aperiodic component is created. Having this function it is possible to calculate fault location using estimated by genetic algorithm amplitude during the fault. This paper presents advantages and disadvantages of proposed technique.

On some spectrum estimation methods for analysis of nonstationary signals in power systems. Part II. Numerical applications

This is a companion paper to a paper of the same title, Part I, in which the theoretical aspects of some spectrum estimation methods for analysis of nonstationary voltages and currents in power systems with nonlinear loads are analysed. In particular, the Prony model and rootMusic method are taken into account. In this work, numerical applications of the methods presented in Part I are discussed, in order to illustrate their implementation problems and practical applications. To investigate the methods, several experiments were performed using nonstationary voltage and current waveforms in a supply system of a DC arc furnace. For comparison, similar experiments were repeated using the short-time Fourier transform. The comparison proved the effectiveness of the new methods; however, their computational efforts can be much more complex. Conclusions and recommendations are made concerning the framework of each method.

Wide-area system of registration and processing of power quality data in power grid with distributed generation: Part I. System description, functional tests and synchronous recordings

This paper presents the developed and built comprehensive system of registration, archiving and data processing for the wide-area monitoring of power quality in a separated part of real power grid with distributed renewable generation. Real case studies related to localization of sources of voltage disturbances are presented.

Adaptation of SVD and Prony method for precise computation of current components in networks with wind generation

precise computation of current components is a key prerequisite for reliable assessment of power quality. Especially in networks with wind generation we may observe increased number of possible disturbing phenomena. This paper presents an approach to accurate computation of currents components with two similar parametric methods based on singular value decomposition (SVD) and Prony model. Those methods seem to be applicable for the detection of non integer multiples of the main frequency in decaying signals. Results of both methods have been compared and evaluated. with respect to traditional Fourier method.