Modelling of the time series digressions by the example of the UPS of the Ural

The article oversees forecasting model for deviations of the balancing market index and day-ahead market index according to the maximum similarity sample for different levels of approximation in the context of positive and negative time-series value. The model is being tested on the factual data of the Integrated Power system of the Ural, Wholesale market for electricity and power of the Russian Federation. The offered model is based on the sample of maximum similarity of the daily digressions by “Day-ahead” market from balancing market index in the history data of 2009–2014 that was acquired from an official web-site of the wholesale electric power market. Testing of the mathematical model gave the prediction error of 3,3%. The offered toolkit for forecasting of the main day-ahead and balancing market parameters is recommended to use for operational work of the industrial enterprise.