Increasing efficiency of control of excitation of brushless synchronous generator in autonomous power supply systems

Author(s):  
V.V. Karagodin ◽  
◽  
V.A. Gorin ◽  
N.V. Ryzhiy ◽  
◽  
...  
Author(s):  
Yuri Bulatov ◽  
◽  
Andrey Kryukov ◽  
◽  

The power industry is currently actively developing the field related to the use of distributed generation plants located near the power receiving devices of consumers. At the same time, the introduction of distributed generation plants causes a lot of engineering problems which need solutions. One of them is the optimization of the settings of automatic voltage regulators (AVR) and speed regulators (ASR) of synchronous generators in all possible operating modes. This requires the use of complex models of power supply systems, distributed generation plants and their regulators, as well as labor-intensive calculations that take into account a large number of interrelated parameters. However, there is another approach based on the use of predictive controllers. In this case only one parameter is needed for linear predictive models.The article describes a method for constructing and tuning the proposed predictive ASR synchronous generator, as well as computer models of distributed generation plants used in research. The purpose of the research was to determine cyber security of power supply systems equipped with various distributed generation plants with predictive speed controllers that can be implemented on the basis of the microprocessor technology. The studies were carried out in the MATLAB system using the Simulink and SymPowerSystems simulation packages on computer models of distributed generation plants with one turbine generator operating at a dedicated load, as well as a group of hydrogenerators connected to a high-power electric power system. The simulation results showed the effectiveness of the proposed predictive control algorithms, as well as the fact that their cyber security can be increased by introducing hardware restrictions on the range of changes in the time constant of the predictive link.


2018 ◽  
pp. 19-27
Author(s):  
BAGAUDIN Kh. GAITOV ◽  
◽  
Yakov M. KASHIN ◽  
Lev E. KOPELEVICH ◽  
Aleksandr V. SAMORODOV ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document