Subsurface Resources Management Department, Central Federal District, Moscow, Russia:

S. S. Lomaev, Head of Department

Sergo Ordzhonikidze Russian State University for Geological Prospecting, Moscow, Russia:
S. V. Golovin, Associate Professor, Candidate of Engineering Sciences, sgolowin@yandex.ru
M. V. Merkulov, Professor, Doctor of Engineering Sciences

Institute of Mineralogy, Geochemistry and Crystal Chemistry of Rare Elements, Moscow, Russia:

V. A. Kosyanov, Counselor to CEO, Professor, Doctor of Engineering Sciences

The analysis of the deterministic and probabilistic methods to design electrical loads of core drilling rigs is presented. It is found to be advisable to design the load of a drilling rig using the method of ordered diagrams, which requires the exact value of the most popular design coefficient—the utilization factor commonly included in various dependencies in most methods discussed. Although the utilization factor-based method is recommended for the power supply design in all industries, it has the drawback the most of the other methods have, namely, the value of the utilization factor is taken from lookup tables, which leads to ambiguity of the results. It has been experimentally found that the reasons for such ambiguity are the variable conditionsof geological exploration, which govern the irregular change in the loads of drilling rigs. Such change is random and leads to heterogeneity of operating modes of power receivers, which creates prerequisites for the probabilistic methods to determine the rated power using statistical data which reflect the actual pattern energy parameters of drilling rigs. The power measurements and plotting of loads on drilling rigs in production conditions show that the drilling depth has the greatest effect on the energy consumption. This makes it necessary to correlate the calculated coefficients with the process variable of drilling, and necessitates mathematical modeling to adequately describe the design energy parameters of drilling rigs SKB-4 and ZIF-650 with regard to the influence of the drilling depth.

1. Samarbekov E. S. Graphics of electrical loads, their purpose and classification. Nauka i innovatsionnye tekhnologii. 2020. No. 3(16). pp. 117–123.
2. Feng Ye, Yi Qian, Rose Qingyang Hu. Smart Grid Communication Infrastructures: Big Data, Cloud Computing, and Security. Hoboken : John Wiley & Sons, Inc., 2018. 304 p.
3. Gracheva E. I., Naumov O. V. Design accuracy of electric loads in industry. Vesti vysshikh uchebnykh zavedeniy Chernozemya. 2018. No. 3(53). pp. 3–12.
4. Vasin G. Ya. Causes for overestimated design heat loads. Promyshlennaya energetika. 1980. No. 3. p. 28.
5. Kosyanov V. A., Limitovskiy A. M., Merkulov M. V., Golovin S. V. Increasing of effectiveness in combination energy-supply of decentralized geological objects in Arctic and utmost north environment. Izvestiya vuzov. Geologiya i razvedka. 2014. No. 4. pp. 81–85.
6. Golovin S. V., Merkulov M. V., Kosyanov V. A. Improvement of exploration drilling energy efficiency by automatic operation control of heat recovery units. Gornyi Zhurnal. 2018. No. 11. pp. 51–55. DOI: 10.17580/gzh.2018.11.09
7. Kazantsev A. A., Soldusova E. O., Pronichev A. V. Analysis of operating conditions in design of innovation power supply systems. Evraziyskiy soyuz uchenykh. 2018. No. 3-2(48). pp. 64–69.
8. Mani Vadari. Electric System Operations: Evolving to the Modern Grid. 2^nd ed. Boston : Artech House, 2020. 290 p.
9. Fereidoon Sioshansi. Behind and Beyond the Meter: Digitalization, Aggregation, Optimization, Monetization. London : Academic Press, 2020. 457 p.
10. Limitovskiy A. M., Kosyanov V. A. Electric Equipment and Power Supply in Geologic Exploration. 4^th enlarged and revised edition. Moscow : RUDN, 2009. 384 p.
11. Babokin G. I. Influence of process flow diagram and longwall length on specific energy consumption of shearers. GIAB. 2021. No. 2. pp. 139–149.
12. Naderi Y., Hosseini S. H., Ghassem Zadeh S., Mohammadi-Ivatloo B., Vasquez J. C. et al. An overview of power quality enhancement techniques applied to distributed generation in electrical distribution networks. Renewable and Sustainable Energy Reviews. 2018. Vol. 93. pp. 201–214.