Przemyslaw Janik

Automated classification of power-quality disturbances using SVM and RBF networks

The authors propose a new method of power-quality classification using support vector machine (SVM) neural networks. Classifiers based on radial basis function (RBF) networks was, in parallel, applied to enable proper performance comparison. Both RBF and SVM networks are introduced and are considered to be an appropriate tool for classification problems. Space phasor is used for feature extraction from three-phase signals to build distinguished patterns for classifiers. In order to create training and testing vectors, different disturbance classes were simulated (e.g., sags, voltage fluctuations, transients) in Matlab. Finally, the investigation results of the novel approach are shown and interpreted.

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.

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.

Heuristic Storage System Sizing for Optimal Operation of Electric Vehicles Powered by Photovoltaic Charging Station

This paper discusses the utilisation of PV systems for electric vehicles charging for transportation requirements of smart cities. The gap between PV power output and vehicles charging demand is highly variable. Therefore, there is a need for additional support from a public distribution grid or a storage device in order to handle the residual power. Long term measurement data retrieved from a charging station for 15 vehicles equipped with a PV system were used in the research. Low and high irradiation seasons influenced the PV output. The charging demand of electric vehicles varied over the course of a year and was correlated to weather conditions. Therefore, the sizing and performance of a supportive storage device should be evaluated in a statistical manner using long period observations.

Effective approach to analogue filter design dedicated to current harmonics reduction in nonlinear circuits

Modern lightning system are energetically efficient, but highly nonlinear, drawing non-sinusoidal currents and deteriorating power quality. The best way to reduce harmonics is to install filters. In practice, filters are installed without exact and precise design for every installation site. In some cases the filtration is not optimal, costs do not justify the effect. The authors propose an efficient and theoretically fully justified approach to filter design for circuit with high harmonic content. Using the proposed approach the filter can be easily triggered to handle harmonics in a way desired by user, even for interharmonics. Efficiency increase and const reduction of filters is expected.)

Time-Frequency Analysis of Power Distortion under Fault Conditions for Grid Connected Wind Turbine

This paper serves the idea of designing appropriate method for complex investigations of transient states in wind power plants. Proposed algorithms belong to two-dimensional time-frequency representations. Additional dimension allows to obtain simultaneous information about frequency of distortion components as well as its duration time. Two algorithms were proposed: short-time Fourier transform (STFT) and Choi-Williams Distribution (CWD). In order to explore advantages and disadvantages of the method in application for wind power plants area, several experiments were performed using model of squirrel-cage induction machine connected directly to the grid. Investigated phenomena concerned power distortion caused by different kind of faults as well as influence of wind speed on instantaneous character of the transient states.

Optimal sizing of renewable energy plant-storage system for network support

The quest to meet the ever increasing demand for energy coupled with the need to curtail the emission of CO2 has led to the deployment of renewable energy sources into the electrical network over the past decades. This development, although very desirable, comes with the known downside of fluctuating production, especially when dealing with wind and solar power sources. This introduces variations in voltage and frequency along with harmonic pollution that need to be constantly controlled. System operators are required to balance demand and supply and are sometimes forced to cut out supply from renewable energy sources in order to maintain network stability, resulting in losses. This paper shows an approach to sizing of renewable energy plant and storage system using particle-swarm optimization. The background aim is to support the hosting capacity of the network where the unit is connected.

Potentials of microgrids - RES infeed, stationary storage and controllable loads modelling

The general possibility of combining electric vehicles, PV systems and storage devices is useful for the reliability and quality of electricity distribution. It contributes to optimal operation of distribution networks and minimization of transmission losses. The potential of a microgrid concept can be evaluated using a reliable and reality oriented simulation allowing various case studies and resizing of microgrid elements. This paper presents an attempt to develop and simulate and robust system based on long time collection of real data.