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Fedotov Vladimir V.

Master’s Student, Electromechanical Systems Department, Branch of the National Research University “MPEI” in Smolensk
Smolensk, Russia

Simulation of the saturation process of a current transformer with a load

The article deals with the mathematical basis and simulation of the saturation processes of current transformers with aperiodic components of short-circuit currents. Saturation processes of current transformers can affect the correct operation of the protections. At power plants, in particular atomic ones, the number of current transformers is several hundred with different loads, lengths of supply cables and the implementation of relay protection. At the same time, the determination of the time to saturation is essential for the construction of circuits and principles of construction of relay protection systems and automation of power plants. The dynamic processes in the primary and secondary circuits of current transformers in dynamics are considered in detail. A mathematical description of the dynamic processes of a current transformer in the nominal mode and during a short circuit in its primary circuit is given. The substantiation of the expediency of using the hypothesis of a rectangular magnetization characteristic in simplified calculations of saturation processes is given. The possibility of using the characteristics of magnetization in the test protocols available in practice in the no-load mode to simulate saturation processes has been demonstrated. Simulation of current transformers for the no-load experiment and power supply of the current transformer from the secondary side, as well as during its operation under conditions of a short circuit on the primary side and a known load on the secondary side is carried out. Thus, with the help of a computer experiment, it is possible to take the current- voltage characteristics and transfer them to the model with the saturation of current transformers already in the short-circuit mode. The efficiency of dynamic simulation of current transformers is shown. The software implementation of the model is performed by means of structural simulation in the MatLab package, based on the solution of equations of matrix structures and emulation of parallel computations. It was found that with the adequacy of the model and the real current transformer with the involvement of information from the no-load mode, the determination of the magnetization time from the aperiodic current components from the model is much easier than the analysis by other existing methods. They require detailed design details of the current transformer and the magnetic properties of the steel. Read more...

Modeling the process of self-starting of electric motors for auxiliary needs of a nuclear power plant to accelerate it and minimize various disturbances

The article proposes a solution to the problem of accelerating the processes of self-starting of asynchronous electric motors of pumping equipment with the help of simulation computer modeling tools to reduce the negative impact on the power supply circuit of the auxiliary needs of a nuclear power plant. The features of the run-down transient processes and the interaction of machines of various capacities in the autonomous circuit that occurs after they are turned off, the subsequent transition to a backup power source, and the emerging effects during self-start are considered. It is shown that the most severe mode of such a transition occurs as a result of the operation of automatic switching on of the reserve and disconnection of working power sources by technological protections or actions of operational personnel at the operational level of operating voltage and nominal or close to it load sections. The analysis of emerging modes is carried out using models developed in the MatLab computer mathematics system with a built-in electrical application. The features of the processes of run-down and subsequent self-starting at various favorable and unfavorable moments of time and the magnitude of the mismatch between the voltages of the network and the resulting autonomous circuit are demonstrated. The models make it possible to obtain a reliable mathematical description of the electromagnetic and mechanical processes of motors in a complex electromechanical system of several motors, to measure the instantaneous voltage differences between the network and the run-down circuit, and to predict the optimal time to turn on the backup power source. The results of the studies carried out on the models are the development of recommendations on the technology for monitoring voltage and circuit mismatches for the same phases, the assessment of the root-mean-square deviation of these mismatches and the effective search for the moment of re-enabling the backup source to improve the technological modes of nuclear power plants. Read more...

Neural network analysis method of heat treatment processes of pelletized phosphate ore raw materials

Currently, there is an acute problem of waste disposal of mining and processing plants, which accumulate in significant volumes in the territories adjacent to them and pose a serious threat to the environment. In this regard, the creation of technological systems for processing ore waste and the improvement of their information support represent an urgent area of research. An example of such a system is a complex chemical and energy technology system for the production of yellow phosphorus from waste apatite-nepheline ores. The purpose of the study was to develop a model for collecting data on the parameters of the processes of heat treatment of pelletized phosphate ore raw materials in such a system, as well as a method for identifying dependencies between these parameters. The identification of dependencies in the information support of the yellow phosphorus production system will improve the quality of its functioning in terms of management criteria, energy and resource efficiency. To achieve this goal, the tasks of choosing a mathematical concept for the basis of the method being developed, constructing an algorithm and creating software implementing this method, conducting model experiments were solved. The method is based on the use of deep recurrent neural networks of long-term short-term memory, which have a high generalizing ability and are used in solving problems of regression and classification of multidimensional time sequences, in the form of which, as a rule, the parameters of a chemical and energy technology system are presented. The method is implemented as an application created in the MatLab 2021 environment. The application interface allows you to interactively conduct experiments with various sets of input and output parameters to identify the relationship between them, as well as change the hyperparameters of neural networks. As a result of the application, a repository of trained neural networks is created that simulate the relationships found between the specified parameters of the technological system and can be applied in decision support systems, management and engineering. Read more...