BUILDING PREDICTIVE ELECTRICITY CONSUMPTION MODELS FOR TRADITIONAL AND SMART GRID POWER SUPPLY SCHEMES FOR IRON ORE MINES

Abstract

The paper studies the peculiarities of building predictive models of electricity consumption according to the traditional and considered schemes built on the concept of Smart Grid, as well as the rapidity of changes in the mode of electricity consumption, chaotic - avalanche-like and forms a corresponding series of problematic issues. Need to be solved today: first of all - systematization of electricity consumption volumes at the iron ore mine. This problem is relevant not only in terms of reducing the irregularity in the amount of electricity consumed by the iron ore mine, but also will increase the efficiency of energy consumption, which in turn will increase the volume of products (iron ore raw materials).

Predictability of electricity consumption models is carried out by isolating these relationships between these variables by statistical - mathematical method of multiple correlation, as the predicted model of electricity consumption is influenced by a large number of factors. The basis for the construction of predictive consumption models for traditional power supply schemes and their subsequent transformation are "smart technologies" of power industry development. The introduction of "smart technologies" including Smart Grid will allow to stabilize and predict the schedules for the volume of consumed electricity of iron ore mine, in contrast to the traditional schemes of its power supply. The purpose of this work is to investigate the issues of construction of mathematical predictive models of electricity consumption developed for traditional and built according to the concept of Smart Grid power supply schemes and contributing to increase the volume of production (iron ore raw materials) and reduce the cost of their production to compete in quality and price. with foreign producers of raw materials of Ukrainian iron ore mines