scholarly journals Assessment of the factors influencing on the formation of energy-oriented modes of electric power consumption by water-drainage installations of the mines

2021 ◽  
Vol 15 (4) ◽  
pp. 25-33
Author(s):  
Oleg Sinchuk ◽  
Igor Sinchuk ◽  
Tetyana Beridze ◽  
Yulii Filipp ◽  
Kyrylo Budnikov ◽  
...  

Purpose. Performing the analysis to determine energy-efficient modes and assess the characteristics of the main indicators of electric power consumption by mine water-drainage installations based on the developed research mathematical model. Methods. To achieve the purpose set, a methodology is used to develop the multiple multifactor correlation-regression modeling with respect to the modes of electric power consumption by electrical and mechanical complexes of mine water-drainage installations. The amount of consumed electric power is found as an effective feature. The expediency of using the nonlinear multiple regression analytical ratios has been substantiated during the model development. A comparative analysis of a multiple multifactor regression model, presented in the form of a power and linear function, has been performed. Findings. The research results make it possible to determine that the greatest influence on the electric power consumption is made by water inflow, and the smallest influence – by the depth of water pumping from underground horizons. The expediency of using a multiple multifactor regression model in the form of a power function has been substantiated. The elaborated quantitative values of the factors of electric power consumption by electrical and mechanical complexes of mine water-drainage installations have become the basis for the introduction of innovative technological solutions at the relevant iron ore enterprises to optimize the cost characteristics of the electric power consumption. Originality. For the first time for the analysis and assessment of the operating modes of the main water-drainage installations of mines, the use of mathematical modeling based on the multiple correlation-regression method is proposed. The developed model takes into account a complex of technological parameters of influence on the water-pumping process. The analysis of the proposed model makes it possible to identify significant factors influencing the modes of electric power consumption by electrical and mechanical complexes of water-drainage installations in the mines and to conduct water-drainage assessment for constructing an algorithm for optimal control of this process in the cost-target direction. Practical implications. The research tactics are proposed for determining the energy-efficient operating modes of the main water-drainage installations of the mines by the method of mathematical modeling. The analysis of the obtained results of mathematical and statistical modeling makes it possible to take into account the complex of technological parameters of the influence on the water-pumping process, to identify and assess the modes of electric power consumption by the main water-drainage installations, as well as to obtain the initial data for the development of the structure of the control algorithm for mine stationary installations of this type in the cost-target aspect.

2011 ◽  
Vol 8 (1) ◽  
pp. 233-238
Author(s):  
R.M. Bogdanov ◽  
S.V. Lukin

Oil and petroleum products transportation is characterized by a significant cost of electric power. Correct oil and petroleum products accounting and forecasting requires knowledge of many factors. The software for norms of electric power consumption analysis for the planned period was developed at the Ufa Scientific Center of the Russian Academy of Sciences. Based on the principles of the relational data model, a schematic diagram/arrangement for the main oil transportation objects was developed, which allows to hold the initial data and calculated parameters in a structured manner.


1985 ◽  
Vol 19 (9) ◽  
pp. 478-483
Author(s):  
S. B. Elakhovskii ◽  
S. I. Sorokina ◽  
E. N. Smirnova

2015 ◽  
Vol 23 (01) ◽  
pp. 1550002
Author(s):  
Sunhee Oh ◽  
Yong Cho ◽  
Rin Yun

The optimum operation conditions of a raw water source heat pump for a vertical water treatment building were derived by changing operation parameters, such as temperature of thermal storage tank, temperature and inlet air flow rate of the conditioned spaces, and circulating water flow rate between thermal storage tank and air handling unit (AHU) through dynamic simulator of a transient system simulation program (TRNSYS). Minimum electric power consumption was found at temperature of thermal storage tank, which was ranged 18–23°C for cooling season. In heating season, temperature 40–45°C brings the highest coefficient of performance (COP) and temperature range of 30–35°C brings the lowest power consumption. When the temperature of the conditioned spaces was controlled between 27–28°C for cooling season, and 18–20°C for heating season the minimum electric power consumption was obtained. Inlet air flow rate of 1.1 m3/h for the conditioned spaces shows the highest performance of the present system, and effects of circulating water flow rate between thermal storage tank and AHU on minimum electric power consumption of the system were negligible.


Author(s):  
А. Voloshko ◽  
Ya. Bederak ◽  
T. Dzheria

Aims of this research are development of a complex statistical analysis algorithm for active electric power consumption data, consumption of energy resources and manufacturing products, implementation of statistical analysis in practice. Proposed parameters and criteria, which can help to technical staff in factories, to provide optimal and economical operating of supply and distribution systems as electricity, water, gas, heat, compressed air, etc. for production facilities, based on the collected active electric power consumption data for previous periods, information about consumption dynamic. It is concluded that the statistical analysis of the data, obtained for each type of engineering equipments (water supply and sewage, supply systems of compressed air, gas, electricity and steam) and various consumables coefficients (in the proposed algorithm) make possible to identify "weak areas" and to determine the most rational ways to optimize energy usage.


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