The topic of this paper is dictated by the necessity to improve the reliability of methods for determining a short circuit of rotor winding with the use of the stray magnetic field sensor installed at the turbogenerator end.The research objectives are to develop the signal identification models and algorithms based on stray magnetic field sensor data for the diagnostics of a short circuit of rotor winding of synchronous generator.Theoretical and practical developments in the areas of systems analysis, electrical machines modeling, optimization and linear algebra are used in the paper. The solution is based on theoretical and experimental data from magnetic field sensor installed at the synchronous generator end.A method of a signal identification and diagnostics from stray magnetic field sensor installed at the synchronous generator end is developed. This method is based on an integrated system of signal models with time-varying parameters and additional a priori information. The method allows for determining the signal local changes from the stray magnetic field sensor caused by the short circuit of rotor winding of the synchronous generator by comparing the original signal with model signal. Experimental data for loaded synchronous generator are considered. It is found that the proposed method provides reliable predictions of the rotor winding damage even for a small number of short circuited coils.

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Power system control requires verified models of all its elements: generators, transformers, transmission lines, and power system loads. To identify load model parameters, the measurement data are used. The paper discusses the possibility of using steady-state measurements instead staged field test data. This requires taking into account an unobvious effect-the network response. The network response is due to the probabilistic nature of the power and voltage changes and the correlation between them. The network response effect is demonstrated using a probabilistic load model and a simple power supply scheme.

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