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The results of testing the algorithms of the adaptive model of a synchronous generator using theoretical and real physical data are presented in this study. The adaptive model of a synchronous machine is an equations system, which describes both the static and transient operation of a generator. Parameters of the adaptive model are found using measurements of a generator’s operational parameters. The single-machine model was created in Matlab/Simulink software to test the theoretical data. This single-machine model consists of a synchronous generator, a step-up transformer, and a transmission line. The test model also includes models of the automatic voltage regulator and steam turbine governor. The real electrodynamic model was used to verify the adaptive model of a synchronous machine. It consisted of four synchronous generators, with values of power capacity of 5 kW and 15 kW. The data logger with a sampling rate of 57.8 kHz was developed and installed to measure the operating parameters of each generator. As a result of testing on both models, the following values were estimated: inertia moment, d-axis and q-axis reactance, and load angle. These values were compared with the reference values. The adaptive model of a synchronous machine can be used in systems of emergency control and assessment of generator state.

Seasonal fluctuations in electricity consumption, and uneven loading of supply lines reduce not only the energy efficiency of networks, but also contribute to a decrease in the service life of elements of power supply systems. To solve the problem of forecasting power consumption, it is proposed to use the theory of fuzzy sets to assess the effective development of the energy system of the Republic of Tajikistan. According to the statistical data of power consumption for the previous period, a fuzzy logic model with membership functions is proposed, which makes it possible to evaluate consumer satisfaction using the criteria unsatisfactory, satisfactory, conditionally satisfactory, and satisfactory, as well as the efficiency of the consumption mode of compliance using the criteria high, medium, and low, allowing the evaluation of the efficiency plan for the development of the energy system of the Republic of Tajikistan. To obtain and set more accurate data on electricity consumption, calculations were made for the winter period of the year. Based on the proposed calculation model of fuzzy logic, a quantitative component of electricity consumption, the corresponding satisfaction of the consumer, and the efficiency of the regime for nine cities of the Republic of Tajikistan were proposed in the form of diagrams of seasonal electricity consumption. The obtained seasonal power consumption makes it possible to improve the accuracy of estimating power consumption, thereby equalizing the balance of consumption and generation.

The study examines the development and testing of algorithms for disturbance inception time estimation in a power system using instantaneous values of current and voltage with a high sampling rate. The algorithms were tested on both modeled and physical data. The error of signal extremum forecast, the error of signal form forecast, and the signal value at the so-called joint point provided the basis for the suggested algorithms. The method of tuning for each algorithm was described. The time delay and accuracy of the algorithms were evaluated with varying tuning parameters. The algorithms were tested on the two-machine model of a power system in Matlab/Simulink. Signals from emergency event recorders installed on real power facilities were used in testing procedures. The results of this study indicated a possible and promising application of the suggested methods in the emergency control of power systems.