For non-sinusoidal single-phase systems, the classical apparent power has been divided into various components using different techniques. These power resolutions generally aim at to provide a tool for the accurate determination of the maximum power factor achievable with a passive compensator and to measure the load.s nonlinearity degree. This paper presents a current decomposition-based methodology that can be employed for computationally efficient implementation of the widely recognized non-sinusoidal power resolutions. The proposed measurement method and the original expressions of the power resolutions are comparatively evaluated by considering their computational complexity. The results show that the proposed method has a significant advantage in terms of computational efficiency for the simultaneous measurements of the powers when compared with the original expressions. Finally, in this paper, a PC-based power meter is developed using the proposed measurement method via the LabVIEW programme.
In this paper, a discrete wavelet transform (DWT) based approach is proposed for power system frequency estimation. Unlike the existing frequency estimators mainly used for power system monitoring and control, the proposed approach is developed for fundamental frequency estimation in the field of energy metering of nonlinear loads. The characteristics of a nonlinear load is that the power signal is heavily distorted, composed of harmonics, inter-harmonics and corrupted by noise. The main idea is to predetermine a series of frequency points, and the mean value of two frequency points nearest to the power system frequency is accepted as the approximate solution. Firstly the input signal is modulated with a series of modulating signals, whose frequencies are those frequency points. Then the modulated signals are decomposed into individual frequency bands using DWT, and differences between the maximum and minimum wavelet coefficients in the lowest frequency band are calculated. Similarities among power system frequency and those frequency points are judged by the differences. Simulation results have proven high immunity to noise, harmonic and inter-harmonic interferences. The proposed method is applicable for real-time power system frequency estimation for electric energy measurement of nonlinear loads.
In this paper an artificial neural network, which realizes a nonlinear adaptive control algorithm, has been applied in a control system of variable speed generating system. The speed is adjusted automatically as a function of load power demand. The controller employs a single layer neural network to estimate the unknown plant nonlinearities online. Optimization of the controller is difficult because the plant is nonlinear and no stationary. Furthermore, it deals with the situation where the plant becomes uncontrollable without any restrictive assumptions. In contrast to previous work  on the same subject, the number of neural networks has been reduced to only one network. The number of the neurons in a network structure as well as choosing certain design parameters was specified a priori. The computer test results have been presented to show performance of proposed neural controller.
Verification of electrical safety in low-voltage power systems includes the measurement of earth fault loop impedance. This measurement is performed to verify the effectiveness of protection against indirect contact. The widespread classic methods and meters use a relatively high value of the measuring current (5#4;20) A, so that they are a source of nuisance tripping of residual current devices (RCDs). The meters dedicated to circuits with RCDs usually use an extremely low value of current (lower than 15 mA), which in many cases it is not acceptable in terms of the measurement accuracy. This paper presents a method of earth fault loop impedance measurement in 3-phase circuits, without nuisance tripping of RCDs – the concept of measurement, the meter structure and the experimental validation. The nuisance tripping is avoided in spite of the use of measuring current value many times higher than that of the rated residual current of RCDs. The main advantage of the proposed method is the possibility of creating values of measuring current in a very wide range, what is very important with regard to accuracy of the measurement.
Power system state estimation is a process of real-time online modeling of an electric power system. The estimation is performed with the application of a static model of the system and current measurements of electrical quantities that are encumbered with an error. Usually, a model of the estimated system is also encumbered with an uncertainty, especially power line resistances that depend on the temperature of conductors. At present, a considerable development of technologies for dynamic power line rating can be observed. Typically, devices for dynamic line rating are installed directly on the conductors and measure basic electric parameters such as the current and voltage as well as non-electric ones as the surface temperature of conductors, their expansion, stress or the conductor sag angle relative to the plumb line. The objective of this paper is to present a method for power system state estimation that uses temperature measurements of overhead line conductors as supplementary measurements that enhance the model quality and thereby the estimation accuracy. Power system state estimation is presented together with a method of using the temperature measurements of power line conductors for updating the static power system model in the state estimation process. The results obtained with that method have been analyzed based on the estimation calculations performed for an example system - with and without taking into account the conductor temperature measurements. The final part of the article includes conclusions and suggestions for the further research.
Random nature of corona processes in UHV power lines and the accompanying noise is the reason that in practice the best determination of acoustic parameters, necessary for the noise evaluation, is obtained from the continuous monitoring procedure. However because of considerable fluctuations (both the useful signal part and the interfering components), careful selection of monitored parameters is necessary to enable a possibility of automatic determination of the parameters that are required for long-term evaluation of corona noise. In the present work a practical realization is shown for estimation of corona noise parameters, based on the data obtained from continuous monitoring stations, making use of the statistical spectra measurement and characteristic features of corona process acoustic signal. Selected results are presented from continuous monitoring of corona noise generated at a 400 kV power line, with special attention focused on definitions of the measured quantities, which enable automatic estimation of the basic factors required for noise evaluation. Accompanying monitoring of environmental conditions, including humidity, precipitation intensity and fog density, that are well correlated with the corona process intensity, which might definitely increase the filtration efficiency of environmental disturbances and on the other hand, it enables verification of calculation methods applied to corona noise. The paper also contains a description of practical approach to selection signal parameters of corona noise in continuous monitoring stations.
The small number of available complete modern pump characteristics makes the safety analysis of nuclear and conventional power plants based on the characteristics made over half a century ago of specific speeds n_q=24.6, 147.1 and 261.4. The aim of the paper is to check sensitivity of the power plant system response for different complete pump characteristics - modern and available from older tests for n_q=24.6, 147.1 and 261.4. It has been shown that Suter's characteristics for modern pumps give a different response to the pumping system of a power plant in breakdown than those used so far.
The Bulletin of the Polish Academy of Sciences: Technical Sciences (Bull.Pol. Ac.: Tech.) is published bimonthly by the Division IV Engineering Sciences of the Polish Academy of Sciences, since the beginning of the existence of the PAS in 1952. The journal is peer‐reviewed and is published both in printed and electronic form. It is established for the publication of original high quality papers from multidisciplinary Engineering sciences with the following topics preferred: Artificial and Computational Intelligence, Biomedical Engineering and Biotechnology, Civil Engineering, Control, Informatics and Robotics, Electronics, Telecommunication and Optoelectronics, Mechanical and Aeronautical Engineering, Thermodynamics, Material Science and Nanotechnology, Power Systems and Power Electronics. Journal Metrics: JCR Impact Factor 2018: 1.361, 5 Year Impact Factor: 1.323, SCImago Journal Rank (SJR) 2017: 0.319, Source Normalized Impact per Paper (SNIP) 2017: 1.005, CiteScore 2017: 1.27, The Polish Ministry of Science and Higher Education 2017: 25 points. Abbreviations/Acronym: Journal citation: Bull. Pol. Ac.: Tech., ISO: Bull. Pol. Acad. Sci.-Tech. Sci., JCR Abbrev: B POL ACAD SCI-TECH Acronym in the Editorial System: BPASTS.