FORECASTING ELECTRICITY CONSUMPTION BY INDUSTRIAL ENTERPRISES (REVIEW)

Abstract

Large consumers of electricity mainly purchase electricity on the wholesale electricity and capacity
market, for example, industrial enterprises of ferrous metallurgy. For the production of products, large
industrial enterprises daily order hourly volumes of electricity consumption for two days in advance, if
necessary, enterprises have the right to send adjusted values for the day preceding the day of consumption.
At the same time, for deviations from the planned hourly volumes, enterprises incur additional costs,
which are included in the electricity tariff. One of the most important factors that affect the forecasting of
hourly electricity consumption are: the variety of types of main and auxiliary equipment, the capacities of
electricity consumers carrying out the technological processes of the enterprise; the intensity of production
load and operating modes depending on the production of the product range; the frequent use of
hours of maximum electric power during the Days; energy-intensive production. To build forecast data for
time series, a model is built to predict hourly electricity consumption by an industrial enterprise and has a
large number of input data that have a probabilistic component. Consideration of various methods for
forecasting time series of electricity consumption of industrial enterprises seems to be an urgent scientific
and technical task. This is due to the requirements of minimization, firstly, of jumps and failures in the
operation of generating capacities of the energy system of the region in which the enterprise is located
(since the load, for example, of ferrous metallurgy enterprises can reach up to 10% of the total consumption
of the region), and secondly, additional costs associated with the purchase/sale of volumes of electricity
consumed in excess of the application/unused in case of inaccurate planning of hourly volumes of electricity
consumed, which are included in the electricity tariff.