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The article discusses the gas turbine electric power stations model creation on the converted aircraft engines basis. Simulation is necessary for the development and control algorithms computer testing for such electric power stations. For this, the developed control algorithms must be tested in various situations arising during the power stations operation. It is well known that it is difficult or impossible to reproduce the most critical modes in real operation and on test benches. Therefore, such studies are carried out on mathematical models, using various designs semi-natural stands, in which real control equipment is interfaced with a mathematical model that reproduces the electrical system behavior. The article discusses a possible solution to this problem: for individual characteristic modes, simplified, fast-solving models with a limited adequacy area, but with high performance, are built. The article proposes to assign the task of constructing such models to an artificial neural network. This opens up additional opportunities for reducing the time required to obtain such models, for example, by using neural networks that have already been trained for a different mode, which in the future will allow expanding the adequacy area of the created neural network models.

Modeling gas turbine electro power station typical operating modes using pre-trained artificial neural network