Swarm intelligence algorithms for the problem of the optimal placement and operation control of reactive power sources into power grids

Deep reactive power compensation allows for reduction of active power losses in transmission lines of power supply systems. The efficiency of the compensation depends on the allocation of reactive power compensation units (RPCUs) at the nodes of a network. In general, investigations devoted to the study of optimal allocation of the compensation units have revealed that it is a static and deterministic optimization problem that can be solved by heuristic methods. However, in real systems, it is reasonable to consider such optimization problems, taking into account the dynamic and stochastic properties of the problems. These properties are the result of equipment failures and operational changes in technical systems. In addition, optimizing the allocation of the compensation units is the NP-hard multifactor problem. Under these circumstances, it is advisable to use the swarm intelligence algorithms. Swarm intelligence is a relatively new approach to solving the optimization problem, which takes inspiration from the behaviour of ants, birds, and other animals. Advantages of swarm algorithms are most evident if problems involve the dynamic or stochastic nature of the objective function and constraints. Contrary to a number of similar studies, this research considers the problem of the optimal allocation of compensation units as a dynamic problem, taking into account the possible random failures of the compensation equipment. The optimization problem has been solved by two Swarm Intelligence algorithms (the Particle Swarm optimization and the Artificial Bee Colony optimization) and Genetic algorithms. It has been aimed at comparing the effectiveness of the algorithms for solving such problems. It was found that swarm algorithms could be successfully applied in the operation control of compensation units in real-time. © 2017 WIT Press

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

Development of a smart electricity meter for households based on existing infrastructure.

Following the universal introduction of information technologies in the electric power industry, it became necessary to create a more perfect measuring infrastructure that would reduce theft of electricity and implement new concepts such as demand response and the P2P market. Existing meters are able to solve the problem of reducing theft, but they do not yet support the functions of P2P trading. This article proposes the development of a smart metering device based on ESP 8266 controller for detection and control of electrical energy and remote turning off or turning on the consumer supply. The meter will be able to exchange information with the cloud platform in real time and provide information about the decline in the quality of electrical energy. It is proposed to use Wi-Fi (main) and GSM (reserve) communication channels. © Published under licence by IOP Publishing Ltd

Multi-criteria analysis of fuzzy symptoms of electrical faults in power systems

The paper considers a possible method of technical diagnostics of electrical equipment of power supply systems and electrical substations based on the fuzzy sets and fuzzy logic. It is shown that, based on the matrix of fuzzy relationships, one can make a plausible enough prediction about possible malfunctions and causes of failures. The prerequisites for this analysis are the current condition (state) of the electrical equipment and expert assessments of diagnostic signs. The paper shows the comparison made using the features scale of Saaty, in accordance with nine degrees of preference. At the core of fuzzy expert assessments is an attempt to formalize linguistic information, namely linguistic variables whose meanings can be words or phrases. The paper presents a complete range of preconditioned defects consisting of m factors and their corresponding space conclusions as to the causes of these malfunctions (defects) of n symptoms. Fuzzy causal relations in the space of underlying factors are established between the assumptions and conclusions of the experts. The resulting system of equations is solved by the method based on the composition of fuzzy conclusions. Possible failures are ranked according to the experts’ preference, which reveals the most significant symptoms of malfunctioning and allows arriving at the conclusion as to the future operation of the facility. The validity of the provisions of the method presented is confirmed by appropriate calculations, which demonstrates the correct behavior of the model concerning the transformer equipment. It is shown that in case of the fuzzy symptoms occurrence and evaluation of these features by a scale of preferences, it is possible to conclude about the further operation of electrical equipment or its withdrawal for repair. Thus, the mathematical model based on the fuzzy relations of symptoms selected using the experts’ estimations contains elements of predicting the possible failures of power systems electrical equipment

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

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"

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"

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