Generalized model of adaptive forecasting of electricity consumption modes of production facilities

Abstract

The article examines the methods of forecasting the electrical load of production facilities. It is shown that it is best to focus on the methods of power consumption management, which are based on the study of forecast estimates, which are the initial information for making management decisions. It is shown that the main requirements for forecasting models are fairly high accuracy of forecasting and simplicity of algorithms. It is shown that in automated power consumption management systems, due to the lack of study of the nature of the forecasted process, insufficient reliability of the source information, the most appropriate is an adaptive approach to the construction of forecasting models. Adaptive forecasting methods and, first of all, the method of exponential smoothing should be put first in terms of ease of implementation and calculation time. In the work, a generalized model of operational forecasting of electricity consumption was obtained, which is easily transformed into an exponential smoothing model and can be extended to use other (except polynomial) functions. It is shown that in relation to processes with deterministic polynomial bases, the generalized model of operational forecasting gives the same result as exponential smoothing.