Problem statement: Reducing the accident rate of overhead power lines (OHL) is one of the priority areas for the development of the electrical power industry. The reliability of overhead power lines depends on a large number of various factors, among which, it is necessary to highlight extreme climatic loads, leading to frequent failures of OHL due to wire breakage. Prompt recognition of emergency line mode, fault localization, and isolation of the damaged area network are the basis for the prompt restoration of power supply. To successfully solve this problem, it is proposed to use a "smart" electromechanical system (SEMS), namely, it is a switching device mounted on the OHL tower and combined with a neurocomputer information processing unit. The neurocomputer, based on processing of information from sensors of current, voltage and meteorological parameters, and in the event of an accident, controls the switching of power lines. The difference between SEMS and a conventional vacuum switch with an electric drive with a constant setpoint is the automatic correction of the setpoint value, which depends on external factors. The purpose of the research: The development of an algorithm for functioning of a circuit breaker with a neurocomputer, ensuring a reliable operation of the circuit breaker to isolate the damaged section of the OHL. Results: The concept of SEMS is proposed in the form of an information-measuring and control system combined with a vacuum switching device and assuming the use of an information processing unit based on an artificial neural network. Practical significance: Modern switching devices implemented with a rigid logic and a constant setpoint value don't possess the ability of adaptation with the environmental conditions. The proposed smart electromechanical system lacks this disadvantage due to the use of a neurocomputer, which allows taking into account the

In this paper, an expert information system for assessing the technical condition of a power transformer is developed. The system will work on the basis of the fuzzy logic device, and provide operational information about the state of the power transformer. The paper uses fuzzy inference algorithms. The R programming language is used to write a program that uses fuzzy logic. We analyzed the data of chromatographic analysis of gases dissolved in oil, as well as the data of thermal imaging images, identifying the most heated points in power transformers. A database of fuzzy logic rules has been formed. Several examples of defuzzification of the results obtained by the center of gravity method are given. As a result of the program, a three-dimensional graph was obtained that characterizes the surface of the fuzzy output. The developed software package allows you to detect defects in working electrical equipment at an early stage of their development, which not only prevents a sudden shutdown of production as a result of an accident, but also significantly reduces the cost of repairing equipment and increases its service life

Nuclear power plants (NPP) are one of the main sources of electricity. The distribution of electricity generated by nuclear power plants, or backup power supply to individual consumers of the power plant's own needs, can be carried out via a 6-35 kV network. These networks operate with an isolated or compensated neutral. This causes the fact that the currents of single-phase ground faults (SPGF) in case of accidents on overhead power lines (OL) are quite small and SPGF are difficult to identify. The article deals with the issues of identifying the SPGF and the corresponding selective response of the overhead line protection system. The limitation of the functioning of relay protection against SPGF, built on the classical principle of operation "if-then", is proved. The error of the traditional protection system is explained by the lack of a mechanism for updating the setpoints in accordance with changes in environmental conditions that affect the capacitive component of the conductivity of overhead lines. As an example of similar an influence, the effect of icing of wires, as well as the triboelectric effect in the form of accumulation of a space charge in the air gap around the line, is described. In this regard, a method is described for correcting the protection setpoints due to periodic measurements of the capacitance of the lines by means of their location probing. Thus, it is proposed to improve the traditional current protection against SPGF by giving the system the ability to adapt, but within the framework of its response as an agent with a simple behavior. The construction of a more advanced system of protection against SPGF in the form of an intelligent agent of the electrical network is also considered. The essence of this system is to use an artificial neural network as a subagent processing information. The advantage of a neurocomputer system for protection against SPGF is proved, which forms an integral assessment of the state of power transmission lines and learns to detect SPGF on a digital shadow following the electrical network. It indicates the possibility of classifying the proposed system of protection against SPGF as an intelligent agent due to the ability to adapt, learn and develop.

В процессе эксплуатации опоры линий электропередачи (ЛЭП) подвергаются механическим деформациям вследствие воздействия ветра и оледенения проводов, это является причиной многочисленных аварий. Существующие методы контроля предаварийных режимов не получили широкого распространения. В связи с этим необходима разработка новых принципов действия устройств для контроля силовых нагрузок. Косвенным проявлением действующих механических нагрузок являются прогибы стоек линейных опор. Это явление наблюдается на "гибких" опорах ЛЭП с несимметричным расположением фаз. Метод высокоточного измерения прогибов позволяет оценить степень оледенения фазных проводов. Предложен вариант технической реализации этого метода диагностики с применением видеокамеры. Описывается процедура расчета отклонения вершины опоры под действием гололеда и ветра. Обоснована целесообразность диагностики состояния линии по информации о величине прогиба опоры.

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