M.S. Antonenko1, S.V. Solodov2, O.L. Dudchenko3
1–3 National Research Technological University «MISIS» (Moscow, Russia)
1 antonenko.ms@misis.ru
With rising energy prices and increasing demands on energy and environmental efficiency, industrial enterprises need to move from passive metering systems to intelligent energy management. Traditional automated energy accounting systems only provide data collection and storage, but do not provide tools for deep analytics and optimization. The purpose of this work is to develop the concept of a digital energy management platform (EMS) capable of integrating production, technological, energy and other data in order to provide tools to support energy-saving solutions.
The implementation of the EMS analytical module allows not only real-time monitoring, but also automatically generates forecasts, identifies deviations, helps to distribute the load between points of electric energy consumption and optimizes energy purchases taking into account tariff zones.
The practical significance of the work is confirmed by a potential reduction in energy costs (up to 8–12%) and, at the next stage, a reduction in equipment downtime due to timely repair planning.
Antonenko M.S., Solodov S.V., Dudchenko O.L. Digital transformation of energy management in industrial enterprises: from accounting to intelligent management // Neurocomputers. 2026. V. 28. № 3. P. 76–84. DOI: https://doi.org/10.18127/j19998554-202603-09.
- Merker E.E., Karpenko G.A., Tynnikov I.M. Energosberezhenie v promyshlennosti i energeticheskij analiz tekhnologicheskikh protsessov. Tonkie naukoemkie tekhnologii. 2020. № 1. S. 45–84. (in Russian)
- Nikonorov N.V., Evstrop'ev S.K. Opticheskoe materialovedenie: osnovy prochnosti opticheskogo stekla. SPb.: SPbGU ITMO. 2009. (in Russian)
- Dzgoev A.E., Lagunova A.D., Karatsev S.T. i dr. Primenenie metodov mashinnogo obucheniya dlya prognozirovaniya elektropotrebleniya energosbytovoj kompanii. Izvestiya Tomskogo politekhnicheskogo universiteta. Inzhiniring georesursov. 2023. T. 334. № 4. S. 162–173. (in Russian)
- Tikhov M.S. Ekonometrika s tsenzurirovannymi dannymi: Ucheb. posobie. Nizhnij Novgorod: Nizhegorodskij gosuniversitet. 2021. (in Russian)
- Regressionnyj analiz [Elektronnyj resurs]. URL: https://habr.com/ru/articles/514818/ (data obrashcheniya: 29.03.2024). (in Russian)
- Printsip upravleniya zapasami [Elektronnyj resurs]. URL: https://planfact.io/blog/posts/upravlenie-zapasami-v-kompanii (data obrashcheniya: 01.03.2024). (in Russian)
- Aksel'rod L.M., Antonov G.I. Ogneupory dlya promyshlennykh agregatov i topok. M.: Intermet Inzhiniring. 2002. (in Russian)
- Siraev F.F., Khazieva R.T. PID-regulyator chastotno-reguliruemogo elektroprivoda magistral'nogo nasosnogo agregata. Vestnik Kazanskogo tekhnologicheskogo universiteta. 2014. T. 17. № 10. S. 245–248. (in Russian)
- Gur'yanov A.V., Zakoldaev D.A., Shukalov A.V. Tsifrovye dvojniki kak osnova podderzhki zhiznennogo tsikla promyshlennoj produktsii. Nauchno-tekhnicheskij vestnik informatsionnykh tekhnologij, mekhaniki i optiki. 2021. T. 21. № 3. S. 396–405. (in Russian)
- Levin V.M., Semenov S.S. Prognozirovanie ostatochnogo resursa tekhnologicheskogo oborudovaniya s ispol'zovaniem metodov analiza vyzhivaemosti. Kontrol'. Diagnostika. 2022. № 5. S. 24–31. (in Russian)
- Klyuev A.V., Klyuev S.A. Avtomatizirovannye sistemy upravleniya energoresursami promyshlennykh predpriyatij: sovremennoe sostoyanie i perspektivy razvitiya. Promyshlennaya energetika. 2020. № 8. S. 32–38. (in Russian)
- Borovkov A.I., Ryabov Yu.A., Shchurin K.V. Tsifrovye dvojniki v zadachakh energosberezheniya i povysheniya energoeffektivnosti. Energosberezhenie. 2021. № 3. S. 54–61. (in Russian)
- Savinykh V.V., Kryukov O.V. Otsenka ekonomicheskoj effektivnosti vnedreniya intellektual'nykh sistem energomenedzhmenta na promyshlennykh predpriyatiyakh. Ekonomika i upravlenie. 2022. T. 28. № 5. S. 478–487. (in Russian)
- Kunkel S., Matthess M., Xue B. et al. Industry 4.0 and energy efficiency: The role of digitalization in reducing energy intensity in the Chinese manufacturing sector. Journal of Cleaner Production. 2022. V. 374. P. 133857.
- Ghobakhloo M., Fathi M., Iranmanesh M. Industry 4.0 and opportunities for energy sustainability: A systematic review and future research directions. Journal of Cleaner Production. 2021. V. 295. P. 126392.
- Hasan M., Trianni A. The role of Industry 4.0 technologies in improving energy efficiency: An empirical investigation of manufacturing firms. Energy. 2022. V. 254. P. 124301.
- Introna V., Santolamazza A., Cesarotti V. Industry 4.0 and ISO 50001: a systematic literature review and research agenda. Energy Efficiency. 2022. V. 15. № 5. P. 32.
- Vance D., Jin M., Wenning T. et al. A framework for enterprise-level energy forecasting using machine learning. Energy and Buildings. 2022. V. 265. P. 112077.
- Parii D., Tang G., Kouzinopoulos C.S. et al. Remaining useful life estimation of printing heads: A comparative study. IFAC-PapersOnLine. 2022. V. 55. № 19. P. 133–138.
- Wang H., Li Y., Zhao X. A comprehensive review of machine learning for energy forecasting in smart grids. Renewable and Sustainable Energy Reviews. 2023. V. 178. P. 113246.

