Abstract

In this work, we determine the control efficiency of grids with distributed generation and the possibility of eliminating flicker therein using group predictive voltage and frequency regulators. A small-size thermal power plant with the transformer connection to a power grid and consisting of three turbogenerators with a capacity of 2.5 MV·A each and a voltage of 6 kV was considered as a distributed generation plant. An isolated power supply system with three 2.5 MV·A gas turbine units each operating on static and motor loads was also considered. Automation control methods were used. Studies were conducted in the MatLab environment using the Simulink and SimPowerSystems simulation packages. The obtained results demonstrate that, upon temporarily activating the power load in the point of connecting a distributed generation unit and using inconsistent regulators, fluctuations occurring in the rotor speed and turbogenerator voltage indicate the presence of flicker effects. A similar situation can be caused by a sudden change in the forecast time for individual predictive speed controllers. Following the disconnection of a 0.4 s short circuit, a voltage flicker was found to occur in the vicinity of the gas turbine plant. However, local or group predictive regulators allow the problem of flicker emergence to be solved. The use of group predictive regulators allows flicker to be eliminated more effectively: the transient time is reduced by 1.7 and 2.7 times for the generator rotor speed and voltage, respectively. Moreover, for voltage, over-regulation is practically eliminated. The conducted computer simulation confirmed that flicker can be eliminated by applying group control of turbine generators using predictive speed controllers. Similarly, for a grid with gas turbine units, the use of predictive control algorithms made it possible to eliminate flicker without solving the problem of adjusting regulators. At the same time, group predictive regulators eliminate flicker more effectively, thereby improving the quality indicators of the control process.

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