Optimization of power consumption at concentration plants using statistical analysis

The article focuses on a relevant objective of the mining industry, namely, optimization of power consumption by mineral processing activities via statistical modeling. The problem connected with the electric energy consumption has become critical now and retards rates of production of mineral resources for industries. The research procedure involves estimation of power consumption at a concentration plant as function of quantity of production machines involved in simultaneous operation. An integrated analysis of duties of electric equipment at an ore concentration workshop is performed. An engineering forecast of the electric energy consumption in different modes of equipment at a concentration plane is conducted using the method of growth rates. The dynamics of power supplies is predicted using the regression models and the least square method. The economic evaluation of options of enhanced efficiency in utilization of electric energy is given with the determination of economic effect owing to optimized loading conditions of production equipment. It is shown that the relative error of power consumption from the experimental and theoretical distribution laws of initial data arrays is never higher than the allowable value. It is recommended to maintain an optimized productivity of a processing line on the basis of a rated capacity of a mill. It is justified that the source of the electric energy saving is the increase in the mill capacity up to a statistically valid value. The figures of power savings are given for individual workshops of a concentration plant. The research findings can be in demand when upgrading and constructing operating and new concentration plants, as well as in training specialists for the mining industry.

Klyuev R. V. Optimization of power consumption at concentration plants using statistical analysise. MIAB. Mining Inf. Anal. Bull. 2024;(12):150-161. [In Russ]. DOI: 10. 25018/0236_1493_2024_12_0_150.

R.V. Klyuev, Dr. Sci. (Eng.), Assistant Professor, Professor, Moscow Polytechnic University, 107023, Moscow, Russia, e-mail: kluev-roman@rambler.ru, ORCID ID: 0000-0003-3777-7203.

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