ANALYSIS OF ELECTRIC POWER GENERATION DATA IN A WIND-DIESEL COMPLEX USING THE SSA ALGORITHM BASED

Studies a model developed by the authors for analyzing data on the generation of electricity in a wind-diesel complex using the SSA algorithm, which allows decomposing a time series into simple components: trends, periodicals, and noise components. These transformations will make it possible to display the relationship between the generation of electricity by the power supply complex, which includes a wind turbine and diesel generators, with climatic factors. After analyzing the graphs obtained for the noise components, it was concluded that relatively stable power generation is observed in the summer period. However, there is interference in the data in the spring-autumn period, the amplitude of the noise components becomes larger, which characterizes the influence of sharp climatic changes on the operation of electrical equipment, and, accordingly, the unevenness of energy consumption. The results obtained make it possible to make adjustments in the control system for seasonality, and by analyzing the noise components, it is possible to take into account the influence of climatic conditions on the operation of electrical equipment. The obtained reconstructed time series correctly reflect the dynamics of the process. The coefficient of determination R2 for a series of generation from a wind turbine is 7 % higher compared to a series of generation from a diesel power plant. This indicates that the SSA model is correct and more preferable for analyzing the generation of electrical energy using wind turbines.

Authors: D. E. Batueva, Ya. E. Shklyarskiy, I. E. Revin

Direction: Electrical Engineering

Keywords: Principal component analysis, time series analysis, statistical analysis, machine learning, wind-diesel complex

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