Fuzzy neural networks' application for substation integral state assessment

This paper addresses the problems connected with fuzzy neural networks' application in equipment technical state assessment problems at electrical substations. This paper discusses the main principles of fuzzy neural network formation and its construction algorithm. Also, the case study for the determination of fuzzy neural network synaptic weights for the unit "disconnector" on the basis of technical diagnostic statistical data and tests is presented. © 2014 WIT Press.International Journal of Safety and Security Engineering;International Journal of Sustainable Development and Planning;WIT Transactions on Ecology and the Environmen

Determining Optimal Breakpoints in Urban Power Networks with Genetic Algorithm

Abstract. The article deals with the issues of optimizing the operating modes of 6-10 kV distribution networks constituted by the large-sized complicated meshed systems. In real time, such networks operate with breaking the circuit to eliminate equalizing currents. The goal of optimizing the networks' operating modes is to minimize the active power loss. Determining the optimal breakpoints is a complicated discrete task, for which the method of genetic algorithm becomes the most suitable solution

Determining Optimal Breakpoints in Urban Power Networks with Genetic Algorithm

The article deals with the issues of optimizing the operating modes of 6-10 kV distribution networks constituted by the large-sized complicated meshed systems. In real time, such networks operate with breaking the circuit to eliminate equalizing currents. The goal of optimizing the networks’ operating modes is to minimize the active power loss. Determining the optimal breakpoints is a complicated discrete task, for which the method of genetic algorithm becomes the most suitable solution. © 2012, European Association for the Development of Renewable Energy, Environment and Power Quality (EA4EPQ). All rights reserved

Effect of Mn2+ ions on the magnetic microstructure of hexaferrites

Effect of Mn2+ ions on the magnetic microstructure of substituted hexaferrites SrFe12 - 2xMnxTixO19 was studied using the Mössbauer spectroscopy data. A new method is developed for estimating the hyperfine interaction parameters in substituted ferrites, and is based on a quasicontinuous description of their Mössbauer spectra. It is shown that a single substitution of manganese for iron in the second coordination shell of Fe3+ changes the local magnetic field strength at this ion by approximately 20 kOe, this value being independent of the concentration of substituted ions. © 2000 MAIK "Nauka/Interperiodica"

Synthesis of the aluminum-substituted hexaferrite SrFe 9.5Al 2.5O 19

The phase-formation processes involved in the synthesis of the hexagonal ferrite SrFe 9.5Al 2.5O 19 by solid-state reaction at 900°C for 5 min to 8 h were studied by x-ray diffraction and Mössbauer spectroscopy. The formation of the hexagonal ferrite at this temperature was found to take 3 h. The resultant material also contained SrAl 2O 4 and SrFeO 3-x, which suggests that, for the synthesis to reach completion, the heat-treatment temperature should be higher. The aluminum cations in the hexaferrite phase were shown to occupy, for the most part, positions 12k and 4f 1. © 1999 MAHK "Hayka/Interperiodica"

Nuclear magnetic resonance spectrum of 31P donors in silicon quantum computer

The influence of the electric field created by a gate potential of the silicon quantum computer on the hyperfine interaction constant (HIC) is obtained. The errors due to technological inaccuracy of location of donor atoms under a gate are evaluated. The energy spectra of electron-nuclear spin system of two interacting donor atoms with various values of HIC are calculated. The presence of two pairs of anticrossing levels in the ground electronic state is shown. Parameters of the structure at which errors rate can be greatly minimized are found.Comment: 12 pages,, 3 figure

Medium-Term Load Forecasting in Isolated Power Systems Based on Ensemble Machine Learning Models

Over the past decades, power companies have been implementing load forecasting to determine trends in the electric power system (EPS); therefore, load forecasting is applied to solve the problems of management and development of power systems. This paper considers the issue of building a model of medium-term forecasting of load graphs for EPS with specific properties, based on the use of ensemble machine learning methods. This paper implements the approach of identification of the most significant features to apply machine learning models for medium-term load forecasting in an isolated power system. A comparative study of the following models was carried out: linear regression, support vector regression (SVR), decision tree regression, random forest (Random Forest), gradient boosting over decision trees (XGBoost), adaptive boosting over decision trees (AdaBoost), AdaBoost over linear regression. Isolation of features from a time series allows for the implementation of simpler and more overfitting-resistant models. All the above makes it possible to increase the reliability of forecasts and expand the use of information technologies in the planning, management, and operation of isolated EPSs. Calculations of the total forecast error have proved that the characteristics of the proposed models are high quality and accurate, and thus they can be used to forecast the real load of a power system. © 2021 The Author(s).The reported study was funded by RFBR, Sirius University of Science and Technology, JSC Russian Railways and Educational Fund “Talent and success”, project number 20-38-51007

Diagnostics of the technical condition of electric network equipment based on fuzzy expert estimates

The paper describes a new possible method of diagnostics of the current technical condition of equipment using a mathematical model based on fuzzy expert estimates and the theory of fuzzy sets. The specifics of the task is determined mainly by the type of the obtained estimates, namely: causal relationships between the controlled parameters of the transformer equipment and defects that could entail their change and the possibility of further operation of the facility. At the same time, attention is paid to the problem of the degree of consistency of expert opinions that affects the quality of the assessment of the current technical condition of the studied object. The paper provides a comparative analysis of the arithmetic mean estimates and median estimates of the consistency of expert opinions. It is shown that the significant drawback of the arithmetic mean approach is its instability towards outliers of individual opinions moving the resulting value under the influence of the “dissident expert opinions”. On the other hand, the median estimate is free of such shortage; it is more outlier-resistant and simply discards a part of radically outlying expert opinions. For the first time, the Kemeny median has been used for technical diagnostics. Kemeny median is based on the introduction of a metric to the set of expert opinions, and axiomatic introduction of the distance between them. Also, the paper formulates a criterion on how to determine the optimal number of experts in the group. © 202

Analysis of Transient Recovery Voltage and Secondary arc Current in Transposed Extra-High Voltage Lines in a Two-Phase Auto-Reclosing

Extra-high voltage (EHV) lines of 500–750 kV, providing transmission of electricity over long distances and at the same time performing the functions of intersystem communication at the level of the national power system, play an important role not only in normal modes, but also in emergency modes, ensuring the dynamic stability of the power system as a whole. In these lines, the overwhelming proportion of power cuts are caused by single-phase short circuits (90%), a significant part of which, being unstable arc faults, are successfully eliminated in the single-phase auto-reclosing cycle. Also, about 5%–10% of failures can be constituted by two-phase short circuits, which can be eliminated in a two-phase auto-reclosing cycle (TPhAR). The purpose of this paper is to study two-phase auto-reclosing in transposed EHV lines equipped with four-radial shunt reactors (ShR). The paper analyzes the efficiency of using a two-phase auto-reclosing to eliminate two-phase short-circuits in the lines connecting the power systems of Kyrgyzstan and Tajikistan. An algorithm is proposed for calculating the transient recovering voltages (TRV) and secondary arc currents (SAC) in the real transposed line Datka–Khujand–Dushanbe. The obtained results of TRV and SAC, which are within the permissible limits for the Dushanbe–Khujand line section, make it possible to have a dead time of TPhAR of no more than 0.6 s, in order to maintain the dynamic stability of the power system. For lines with a length of about 500 km (Datka–Khujand), equipped with three reactors, a successful TPhAR is impossible due to the appearance of resonant TRV in the circuit. The paper proposes the use of banks of capacitors connected in series in the phases of the ShR for the implementation of a successful TPhAR with the duration of the required pause of about 0.6 s. © 2021 The Authors