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Abstract
The article describes the concept of a digital twin of a distributed generator (DG) implemented on the basis of a salient-pole synchronous generator. The structure of the digital twin is presented in the form of a hierarchical fuzzy model built on the experimental data. For building fuzzy models of individual elements and links of a generator, software algorithms for optimization of the membership functions of term sets and the numbers of knowledge base rules are proposed. The results of experiments on obtaining an optimized neuro-fuzzy model for regulating the rotation speed of the generator rotor are presented. A comparative analysis of the oscillograms of the output signal of the optimized fuzzy model showed a sufficiently high accuracy when using the subtractive clustering method to build a fuzzy logic system. This approach made it possible to significantly reduce the number of term sets and the amount of the fuzzy model rules. The proposed algorithms can be used in further research aimed at industrial implementation of DG digital twins, as well as for solving the problem of tuning automatic regulators of low-power synchronous generators
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