Short-term prediction of energy consumption at concentration factory

The article describes prediction of energy consumption at a concentration factory. In view of the energy intensity of the process flow at the test concentration factory, its power delivery system needs an improvement. One of the methods of making decisions on power delivery more effective is planning. The effectiveness of planning requires inclusion and comprehensive analysis of all production factors. The energy consumption forecast enables a systemic control of power intake at the factory, with the real-time inclusion of all data on a production process. For this reason, it seems to be scientifically relevant to develop and adapt energy consumption prediction techniques. The scope of this study also embraces the modern methods of the intelligent analysis of data. Using the actual data on daily energy consumption in 2021, a number of the machine learning models are constructed and their accuracy is compared. The best prediction is provided by the model using the Random Forest algorithm. The error of the forecast for a week ahead is less than 5% MAPE, which allows considering the obtained result as an accurate outcome.

Morgoeva A. D., Morgoev I. D., Klyuev R. V., Khetagurov V. N., Gavrina O. A. Short-term prediction of energy consumption at concentration factory. MIAB. Mining Inf. Anal. Bull. 2023;(5-1):157-169. [In Russ]. DOI: 10.25018/0236_1493_2023_51_0_157.

A.D. Morgoeva¹, Graduate Student, e-mail: m.angelika-m@yandex.ru, ORCID ID: 0000-0003-2949-1993,
I.D. Morgoev¹, Graduate Student, e-mail: m.irbek@yandex.ru, ORCID ID: 0000-0003-4390-5662,
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,
V.N. Khetagurov¹, Dr. Sci. (Eng.), Professor, e-mail:hetag@mail.ru, ORCID ID: 0000-0002-2151-9309,
O.A. Gavrina¹, Cand. Sci. (Eng.), Assistant Professor, e-mail: Gavrina-Oksana@yandex.ru, ORCID ID: 0000-0002-9712-9075,
¹ North Caucasian Institute of Mining and Metallurgy (State Technological University), 362021, Vladikavkaz, Russia.

A.D. Morgoeva, e-mail: m.angelika-m@yandex.ru.

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