Market electricity prices and peak load hours forecasting for a region of the russian federation

The article considers the use of a digital model of an electricity consumer for the analysis and forecasting of market electricity prices and peak load hours for the Yaroslavl region of the Russian Federation. To build a digital model of an electricity consumer, the apparatus of artificial neural networks was used. This apparatus has a wide range of forecasting capabilities and allows researchers to obtain the required forecasting accuracy hourly values of market electricity prices. The results of numerical experiments on forecasting market electricity prices using the application developed by the authors are presented. In the course of numerical experiments, the quality of the forecast was studied depending on the type of artificial neural network and its structure. To forecast peak load hours, we used an indirect method based on forecasting of the total electricity consumption of the region. The results of numerical experiments on forecasting the total energy consumption of the region and peak load hours for the month ahead are presented. The article shows how the data obtained from the analysis of peak load hours for previous years can be used to improve the reliability of the forecasts made. Forecasting market electricity prices and peak load hours creates opportunities for solving problems of optimal energy scheduling.