Modeling prices of wholesale market of electric energy and power by the example of the UPS of the Ural

Abstract

Abstract. The article oversees forecasting model for deviations of the balancing market index and dayahead 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 was being tested on the factual data of the Integrated Power system of the Ural, Wholesale market for electricity and power of Russian Federation. Describes the price formation on the day-ahead market and the balancing market index. The necessity to use accurate forecasting methods consumption and prices of electrical energy and power to reduce penalties when the electric power industry entities on the energy exchange. The testing of mathematical models to predict the balancing market index deviations and day-ahead market based on a sample of maximum similarity with certain approximation equations for positive and negative values gave the prediction error of 3.3%.