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Smart Transition to Climate Management of the Green Energy Transmission Chain

Author

Listed:
  • Olena Borysiak

    (Education and Research Institute of Innovation, Environmental Management and Infrastructure, West Ukrainian National University, 46009 Ternopil, Ukraine)

  • Tomasz Wołowiec

    (Institute of Public Administration and Business, University of Economy and Innovation in Lublin, 20-209 Lublin, Poland)

  • Grzegorz Gliszczyński

    (Faculty of Management, Lublin University of Technology, 20-618 Lublin, Poland)

  • Vasyl Brych

    (Education and Research Institute of Innovation, Environmental Management and Infrastructure, West Ukrainian National University, 46009 Ternopil, Ukraine)

  • Oleksandr Dluhopolskyi

    (Institute of Public Administration and Business, University of Economy and Innovation in Lublin, 20-209 Lublin, Poland
    Faculty of Economics and Management, West Ukrainian National University, 46009 Ternopil, Ukraine)

Abstract

Climate challenges in recent decades have forced a change in attitude towards forms of environmental interaction. The International Climate Conference COP26 evidences the relevance of the climate issue at the global level in Glasgow (November 2021). A decrease in natural energy resources leads to a search for alternative energy sources. Given this, this article is devoted to studying the peculiarities of the transition to climate management of the green energy transmission chain based on the circular economy and smart technologies. This paper has used simulation modeling to develop an algorithm for applying a smart approach to climate management of the green energy transmission chain based on the work of Industry 4.0 technologies. The result of this modeling will be the importance of strengthening the ability to develop intersectoral partnerships to create climate-energy clusters based on a closed cycle of using energy resources and developing smart technologies. At the same time, it has been found that COVID-19 has changed the behaviour of energy consumers towards the transition to the use of energy from renewable sources that are carbon neutral. With this in mind, this article has assessed the climate capacity of industries to use green energy from renewable sources based on resource conservation (rational use of energy resources) and climate neutrality. The industries of Ukraine, which are the largest consumers of energy and, at the same time, significantly affected by climate change, were taken for the study: industry, transport, and agriculture. The methodology for determining the indicator of the climate capacity of sectors in the transition to green energy has been based on the correlation index (ratio) of the consumption indicator of various types of energy by industries (petroleum products; natural gas; biofuels and waste; electricity) and the indicator of gross value added of industries in pre-COVID-19 and COVID-19 conditions. The results have indicated that the use of energy from renewable sources (biofuels and waste) for the production of goods and services, as well as the economical nature of the provision of raw materials (biomass and faeces) are factors that ensure climate industry neutrality and enhance its climate capability. The prospects of such effects of assessing the climate capacity of sectors will be the basis for the rationale to develop intersectoral partnerships to create climate-energy clusters based on a closed cycle of using energy resources and developing smart technologies.

Suggested Citation

  • Olena Borysiak & Tomasz Wołowiec & Grzegorz Gliszczyński & Vasyl Brych & Oleksandr Dluhopolskyi, 2022. "Smart Transition to Climate Management of the Green Energy Transmission Chain," Sustainability, MDPI, vol. 14(18), pages 1-11, September.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:18:p:11449-:d:914104
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    References listed on IDEAS

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    1. Song, Jiancai & Zhang, Liyi & Jiang, Qingling & Ma, Yunpeng & Zhang, Xinxin & Xue, Guixiang & Shen, Xingliang & Wu, Xiangdong, 2022. "Estimate the daily consumption of natural gas in district heating system based on a hybrid seasonal decomposition and temporal convolutional network model," Applied Energy, Elsevier, vol. 309(C).
    2. Hlib Polianovskyi & Tetiana Zatonatska & Oleksandr Dluhopolskyi & Ihor Liutyi, 2021. "Digital and Technological Support of Distance Learning at Universities under COVID-19 (Case of Ukraine)," Revista romaneasca pentru educatie multidimensionala - Journal for Multidimensional Education, Editura Lumen, Department of Economics, vol. 13(4), pages 595-613, December.
    3. Sejkora, Christoph & Kühberger, Lisa & Radner, Fabian & Trattner, Alexander & Kienberger, Thomas, 2022. "Exergy as criteria for efficient energy systems – Maximising energy efficiency from resource to energy service, an Austrian case study," Energy, Elsevier, vol. 239(PC).
    4. Yin, Linfei & Qiu, Yao, 2022. "Long-term price guidance mechanism of flexible energy service providers based on stochastic differential methods," Energy, Elsevier, vol. 238(PB).
    5. Tomasz Rymarczyk & Krzysztof Król & Edward Kozłowski & Tomasz Wołowiec & Marta Cholewa-Wiktor & Piotr Bednarczuk, 2021. "Application of Electrical Tomography Imaging Using Machine Learning Methods for the Monitoring of Flood Embankments Leaks," Energies, MDPI, vol. 14(23), pages 1-35, December.
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    Cited by:

    1. Tomasz Wołowiec & Svitlana Kolosok & Tetiana Vasylieva & Artem Artyukhov & Łukasz Skowron & Oleksandr Dluhopolskyi & Larysa Sergiienko, 2022. "Sustainable Governance, Energy Security, and Energy Losses of Europe in Turbulent Times," Energies, MDPI, vol. 15(23), pages 1-15, November.
    2. Alina Vysochyna & Tetiana Vasylieva & Oleksandr Dluhopolskyi & Marcin Marczuk & Dymytrii Grytsyshen & Vitaliy Yunger & Agnieszka Sulimierska, 2023. "Impact of Coronavirus Disease COVID-19 on the Relationship between Healthcare Expenditures and Sustainable Economic Growth," IJERPH, MDPI, vol. 20(4), pages 1-18, February.
    3. Yaryna Samusevych & Serhiy Lyeonov & Artem Artyukhov & Volodymyr Martyniuk & Iryna Tenytska & Joanna Wyrwisz & Krystyna Wojciechowska, 2023. "Optimal Design of Transport Tax on the Way to National Security: Balancing Environmental Footprint, Energy Efficiency and Economic Growth," Sustainability, MDPI, vol. 15(1), pages 1-14, January.
    4. Olena Borysiak & Łukasz Skowron & Vasyl Brych & Volodymyr Manzhula & Oleksandr Dluhopolskyi & Monika Sak-Skowron & Tomasz Wołowiec, 2022. "Towards Climate Management of District Heating Enterprises’ Innovative Resources," Energies, MDPI, vol. 15(21), pages 1-16, October.
    5. Hamdy Abdelaty & Daniel Weiss & Delia Mangelkramer, 2023. "Climate Policy in Developing Countries: Analysis of Climate Mitigation and Adaptation Measures in Egypt," Sustainability, MDPI, vol. 15(11), pages 1-20, June.

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