Development of a scheme for generating the predicted value of specific electricity consumption

Abstract

Abstract Accurate forecasting of electricity consumption determines the success of industrial enterprises. Each enterprise, having an accurate prediction of the amount of power consumed, strictly controls it, since deviations entail disruptions in work, is subject to fines. Power consumption forecasting for a certain period is the most urgent task in today’s electricity market. Existing forecasting methods have individual characteristics and have their advantages and disadvantages. The choice of forecasting methods depends on such major factors as the time for which the forecasting is performed, as well as the amount of information. When forecasting power consumption, it is necessary to take into account various factors related to the technological features of production, organization of equipment operation, etc. The present article describes the proposed method for determining the forecasted values of power consumption parameters in terms of total and specific power consumption, which differs from the existing methods in that it takes into account when forecasting power consumption parameters, the features of production that characterize the production process, the power consumption modes of process equipment, and the impact of technological and operational factors on energy performance that affect the forecast of readings. Accounting for the above factors can significantly simplify and improve the accuracy of forecasting calculations. When determining the forecast values, the components of electricity consumption for the main, auxiliary, and additional production are directly included in the calculation. Besides, the method allows to investigate and optimize the power consumption modes of both a separate production unit and the enterprise as a whole in conjunction with the indicators of processed products and components of the technological process used. The reliability of the method is justified by calculating the energy indicators of a specific section rolling shop of the steel industry.