E3S Web Conf.
Volume 280, 2021Second International Conference on Sustainable Futures: Environmental, Technological, Social and Economic Matters (ICSF 2021)
|Number of page(s)||6|
|Published online||30 June 2021|
Model investigations into assessing optimal power consumption modes for major pump stations of iron ore underground mines
1 Kryvyi Rih National University, Department of Automated Electrical-Mechanical Systems in Industry and Transport, 11 Vitalii Matusevych Str., Kryvyi Rih, 50027, Ukraine
2 Gdańsk University of Technology, Department of Power Electronics and Electrical Machines, 11/12, Gabriela Narutowicza 80-233 Gdańsk, Poland
* Corresponding author: firstname.lastname@example.org
The article investigates into the level of energy efficiency of main water pump stations of iron ore underground mines in case of time-of-day electricity rate. There are developed and suggested methods of analyzing the influence of pump electric capacity on electricity cost based on multifactor regressive models. The data on power consumption of iron ore mines indicates a complex character of analyzing the results obtained. However, application of information technologies enables using static materials in a new way including indices of power consumption, costs, water intake, mining depth, the number of pumps and their capacity by synthesizing mathematical models as complicated objects through in-depth procession of static materials and substantiation of the obtained results. For the first time, there are used multifactor regressive models considering multicollinearity and non-linearity of pump capacity in order to study its influence on power costs by using the elasticity factor. Analysis of mathematical simulation results relevant to static materials and applying the algorithm of studying dependency of the consumed power costs on pumps’ capacity reveals some critical values resulting in corresponding effects. The authors recommend to apply the elaborated algorithm to conducting corresponding calculations by for mining enterprises to monitor formation of the strategy of providing energy efficiency under time-of-day electricity rates.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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