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Stochastic Frontier-Based Analysis of Energy Efficiency in Russian Open-Pit Mining Enterprises

Author

Listed:
  • Ulvi Rzazade

    (ACS Department, National University of Science and Technology MISIS, 119049 Moscow, Russia)

  • Sergey Deryabin

    (ACS Department, National University of Science and Technology MISIS, 119049 Moscow, Russia)

  • Igor Temkin

    (ACS Department, National University of Science and Technology MISIS, 119049 Moscow, Russia)

  • Aslan Agabubaev

    (ACS Department, National University of Science and Technology MISIS, 119049 Moscow, Russia)

Abstract

This article is devoted to the study of the possibilities for improvAzing the quality of energy management systems adopted at open-pit mining enterprises in the Russian Federation. The main idea of the work is to apply stochastic boundary value analysis methods using the production function for individual and integral estimates of the performance of energy-consuming objects when performing various types of technological work. It is shown that mining enterprises are experiencing problems in the field of rational energy consumption due to the lack of strictly formalized ways to determine the frontiers of the efficiency value of the parameter of specific energy consumption (SEC). A justification is given for the need to apply stochastic frontier analysis (SFA) methods and use the Cobb–Douglas production function to account for the nonlinearity and stochasticity of the operating conditions of energy-consuming mining objects. The results of a statistical analysis of the data on the operation of EKG-10 excavators at operating enterprises in Siberia are presented, as well as an assessment of their energy efficiency using the adopted approach based on planning the target value of SEC. The results of computational experiments on constructing an energy efficiency model using the SFA/Cobb–Douglas function for various data segmentation options are presented. Computational experiments have been conducted to compare variants based on the Cobb–Douglas production function and translog function with semi-normal and exponential distribution forms for the same data set. A comparative assessment is given of the approaches to the complex analysis of activities adopted at enterprises and proposed in this study, characterizing potential hidden energy losses in the range from 4.53% to 20.73%.

Suggested Citation

  • Ulvi Rzazade & Sergey Deryabin & Igor Temkin & Aslan Agabubaev, 2025. "Stochastic Frontier-Based Analysis of Energy Efficiency in Russian Open-Pit Mining Enterprises," Energies, MDPI, vol. 18(13), pages 1-27, June.
  • Handle: RePEc:gam:jeners:v:18:y:2025:i:13:p:3257-:d:1684481
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    References listed on IDEAS

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