Global Monitoring of the Development of Digital Energetics Based on the Technologies of Industry 4.0: IoT, Blockchain, Robots, and Artificial Intelligence

Introduction

The transition to Industry 4.0 contributed to the formation of digital energy, which is characterized by the active use of high technologies in various economic processes of the energy economy. Industry 4.0 technologies are defined in different ways in the national programs and strategies of the same name. For example, in Germany, which was the first to adopt a national strategy referred to as “Industrie 4.0,” Industry 4.0 technologies shall be understood to mean the entirety of technologies that form cyber-physical systems and make Germany a leader in terms of technology (European Commission, 2022).

In the United Kingdom, Industry 4.0 technologies shall be understood to mean “eight great technologies” (Government of UK, 2022). The most general (universal, international) list of Industry 4.0 technologies can be found in UNCTAD records (2022), where they are referred to as “Frontier technologies” and include Artificial Intelligence (AI), Internet of Things (IoT), Big Data, Blockchain, 5G, 3D printing, robots, drones, Gene Editing, nanotechnologies, and Solar Photovoltaic (Solar PV).

The studies by Haddouche and Ilinca (2022), Kanoun et al. (2021), Maggiore et al. (2021), Matsunaga et al. (2022), Morelli et al. (2022), Otoum et al. (2022), Wachnik et al. (2022) refer to IoT, Blockchain, robots, and AI as the most advanced and most common technologies of Industry 4.0 in the energy economy. The problem lies in the fact that despite the advantages of digital energetics disclosed in detail in the existing literature (Popkova, 2022), there is still much uncertainty as to whether these advantages are achieved in practice and how to maximize them.

Due to this problem, the development of digital energetics occurs spontaneously. The lack of scientific and methodological support prevents achieving full growth potential to increase the effectiveness of advanced technologies of Industry 4.0 in the energy economy. In the context of global competition in the field of high technologies, energy economies aim to strengthen their digital competitive advantages.

The disadvantage of the current approach to the development of the energy economy based on Industry 4.0 technologies is that its digital competitiveness is an objective in itself. This approach does not guarantee benefits in the form of energy sustainability, providing only its innovation and high-tech. This causes the low effectiveness of this approach due to limited results at high costs (investments in high technologies) and risks (relating to innovations). The hypothesis of this article is that, with the current approach, there is a weak connection between digitalization and energy sustainability.

Thus, to accelerate the development of digital energetics based on the technologies of Industry 4.0 aimed at achieving the Sustainable Development Goal 7 (SDG 7), a new (alternative) approach and scientific and methodological support for its implementation are required. The significance of SDG 7 is that it goes beyond the interests of particular categories of beneficiaries of the energy economy (e.g., affordability of energy for society, reduction in expenses for the development of the energy economy for the state, and increase in profits for energy companies) and forms a consistent idea of how to simultaneously and comprehensively maximize the benefits of the energy economy for all stakeholders (He et al., 2022; Yu et al., 2022).

In this regard, SDG 7 sets such priorities as sustainability (deficit-free energy, balance of global energy markets, stability of global and local energy prices to ensure its wide affordability, reliable and flawless operation of value chains in the energy economy), and environmental friendliness (mitigation of environmental risks of energy production and transportation, reduction/prevention of the depletion of natural resources for their conservation for succeeding generations, and the transition to “clean” energy) of the energy economy (Che et al., 2021; Firoiu et al., 2021; Madurai Elavarasan et al., 2021).

The purpose of this article is to conduct global monitoring of the development of digital energetics based on the technologies of Industry 4.0 and propose a new (alternative) approach to managing this development with a focus on supporting the practical implementation of SDG 7. The novelty of this study and its contribution to knowledge consist in forming a consistent scientific concept of the benefits of using Industry 4.0 technologies for the sustainable and environmentally friendly development of the energy economy.

Digital Energetics Based on the Technologies of Industry 4.0: IoT, Blockchain, Robots, and AI

This article is based on the theory of digital energetics. In the available literature, numerous benefits from advanced technologies of Industry 4.0 in the energy economy are noted as follows:

˗ The Internet of Things (IoT) makes it possible to integrate production and distribution networks and processes into a single cyber-physical system of Industry 4.0 in digital energetics (Krishnan and Jacob, 2022; Zhao et al., 2022).

˗ Blockchain increases the transparency and control of value chains in the energy economy (Gawusu et al., 2022; Mahmoudian Esfahani, 2022).

˗ Robots increase the productivity of energy companies (Huang et al., 2022).

˗ Artificial Intelligence (AI) increases the flexibility and efficiency (through intelligent management decision support) of value chains in the energy economy (Bezbakh and Frolova, 2022).

In the works of Amir et al. (2022), Chen et al. (2022), Favi et al. (2022), and Vlasov et al. (2019), the use of advanced Industry 4.0 technologies in the energy economy provides advantages in both production and distribution processes. Maggiore et al. (2021), Morelli et al. (2022), Wachnik et al. (2022), and Zaidan et al. (2022) indicated that, in order to fully take benefit of the advanced technologies of Industry 4.0 in the energy economy, it is advisable to actively use them by representatives of all interested parties: energy companies, state regulators of the energy economy, and energy consumers. Baxter (2012), Inshakov et al. (2019), Kabeyi and Olanrewaju (2022), Kapitonov et al. (2019), Kluczek et al. (2021), and Ratner et al. (2022) stated that the digitalization of the energy economy based on advanced technologies of Industry 4.0 is universal—it is suitable for all countries, regardless of their energy efficiency, role, and position in global energy markets.

Based on the above publications, it can be concluded that the existing approach to the development of the energy economy based on Industry 4.0 technologies recognizes digitalization as a priority of this development with the secondary sustainability of energy (it is assumed that digitalization provides it). However, the relationship between digitalization and energy sustainability is poorly studied and not confirmed, which is a research gap. The identified gap is filled in this study by clarifying the relationship between the use of advanced Industry 4.0 technologies and energy sustainability.

Digital Competitiveness of Energy Economies and Analysis of Its Differences Among Categories of Countries

In order to achieve this goal and verify the hypothesis put forward, this article conducts global monitoring of the development of digital energetics based on the technologies of Industry 4.0. Monitoring is aimed at accurately quantifying the level of development of digital energetics as a vector of growth and sustainable development of the energy economy.

The study is based on the experience of the top four countries with the highest energy efficiency of the economy (according to the criterion of GDP per unit of energy use, constant 2017 PPP $ per kg of oil equivalent), the top four countries with the largest energy imports, net (% of energy use), and the top four countries with the largest fuel exports (% of merchandise exports) according to the materials of the World Bank (2022). The sample of countries formed for this study made it possible to comprehensively highlight the modern experience of digital energy development, which is considered from the standpoint of two groups of indicators.

The first group: Industry 4.0 technology development indicators: 1) “AI Readiness Index 2020” Oxford Insights (2022), designated AIR; 2) Readiness for Frontier Technologies Index 2021, presented in the UNCTAD report (2022) and designated RFT. The second group: the “World Energy Trilemma Index 2020 Report” World Energy Council (2022) as an indicator of sustainability and environmental friendliness of the energy economy, designated by ETI.

Based on the systematization of the data of both groups, the digital competitiveness of the energy economy [DCEE = (ETI, RFT, and AIR) is estimated/3] and its efficiency [DEEF = ETI/(RFT + AIR)/2]. The classical concepts of economic efficiency as the ratio of results (in our case: sustainability and environmental friendliness of the energy economy) to costs (in our case: technologies of Industry 4.0) (Akram et al., 2022; Gorus and Karagol, 2022) and competitiveness in terms of achieved results compared to other competing countries (in our case, identified by means of rankings) (Nagel et al., 2022; Shuai et al., 2022) served as the prerequisites and the basis for the calculation methods. The study is conducted according to data for 2021. The initial data and the results of their analysis are presented in Table 1.

TABLE 1

TABLE 1. Global monitoring of the development of digital energy based on Industry 4.0 technologies in 2021.

The global monitoring of the development of digital energetics based on the technologies of Industry 4.0 in 2021, presented in Table 1, led to the following results:

˗ The digital competitiveness of the energy economy as a whole is high in all the categories of countries considered. It is highest in the top countries by energy imports (76.97 points) and in the top countries by GDP per unit of energy use (76.24 points), and in the top countries by fuel exports, it is estimated at 61.80 points.

˗ The efficiency of digitalization of the energy economy is low in all categories of countries (it has not reached 1.5). The digital energy economy is inefficient in the top countries by energy imports (0.94—costs exceed benefits, less than 1) and low-efficient (benefits slightly exceed costs) in the top countries by GDP per unit of energy use (1.07) and in the top countries by fuel exports (1.19).

˗ This leads us to the conclusion that the introduction, expansion, and use of technologies of Industry 4.0 (i.e., the transition to the digital energy economy) guarantees an increase in the digital competitiveness of the energy economy but does not indicate an increase in its efficiency (from the perspective of contribution to the sustainability and environmental friendliness of the energy economy).

˗ Hence, this calls for more complex management of the development of the digital energy economy, which will ensure not only an increase in the level of its high technologies (the use of Industry 4.0 technologies—IoT, blockchain, robots, and AI) but also improved results from the perspective of increasing the sustainability and environmental friendliness of the energy economy. The contribution of the suggested methodology to the more intensive acquisition of new knowledge is that the methodological guidelines of the authors allow improving the accuracy and reliability of the quantitative measurement of the efficiency and competitiveness of the digital energy economy.

˗ The authors’ methodology allows obtaining highly detailed evaluation results and, thus, identifying the cause-and-effect relationship between changes in the efficiency and competitiveness of the digital energy economy and their weaknesses and strengths. As a result, it is possible and recommended to develop a national economic policy to manage the development of the digital energy economy, aimed at increasing the efficiency and competitiveness of the digital energy economy.

The Level of the Development of Digital Energetics as a Vector of Growth and Sustainable Development of the Energy Economy: A New Management Approach

In order to determine the contribution of digital energy to the sustainable development of the energy economy based on empirical data from Table 1, the following regression model was obtained by regression analysis:

$\mathrm{ETI}=67.9697+0.2240\mathrm{\ast }\mathrm{RFT}\mathrm{-}0.1678\mathrm{\ast AIR}.(1)$

According to model (1), energy sustainability increases by 0.2240 points when the readiness for Frontier technologies index increases by one point but does not demonstrate a positive dependence on the government AI Readiness Index. The significance of F for model (1) was 0.0628. The multiple R in model (1) was 0.6778. The advantage of the regression analysis method that has been chosen for the pursuance of the research in this study is its high accuracy—this is one of the most reliable methods of statistical economics (econometrics).

The existing concepts of the potential relationship between these indicators (Ghobakhloo and Fathi, 2021; Kluczek et al., 2021) and the successful identification of individual manifestations of this relationship in previous works by Hidayatno et al. (2019), Knez et al. (2022), and Koyuncu et al. (2021) served as the prerequisites and the basis for the calculation methods for obtaining the regression model that is presented to determine the contribution of the digital energy economy to the sustainable development of the energy economy. Also, by the method of correlation analysis, the following was found:

˗ Readiness for Frontier Technologies Index is positively associated with energy sustainability only in the top countries by GDP per unit of energy use (correlation 0.91), in the top countries by energy imports (−0.65), and in the top countries by fuel exports (−0.17%); the relationship of these indicators is negative.

˗ The Government AI Readiness Index is positively associated with energy sustainability only in the top countries by GDP per unit of energy use (correlation 0.78), in the top countries by energy imports (0.67), and in the top countries by fuel exports (−0.99%); the relationship of these indicators is negative.

This brings us to the conclusion that Industry 4.0 technologies make a considerable and significant contribution to ensuring the sustainability and environmental friendliness of the energy economy. In this regard, a new (alternative) approach to the development of digital energetics based on the technologies of Industry 4.0 is proposed, which supports the implementation of SDG 7 and assumes a focus on the digitalization of energy companies, the flexibility necessary to consider the characteristics of each category of countries, and the priority of the efficiency of the digital energy economy.

Based on model (1), the new approach is expected to increase energy sustainability by 6.20% (73.24–77.78 points) while maximizing the readiness for advanced technologies of the index (+33.83%, 74.17–100 points). The established approach to the development of digital energetics based on the technologies of Industry 4.0 is versatile—it can be implemented around the world (by large energy suppliers and exporters and by large energy consumers and importers, as well as by other countries). This approach will ensure the accelerated digitalization of the energy economy and increase its efficiency; as a result, it will support the global implementation of SDG 7.

Discussion

The article contributed to the development of the theory of digital energetics by clarifying the relationship between digitalization and energy sustainability. In contrast to Amir et al. (2022), Chen et al. (2022), Favi et al. (2022), and Vlasov et al. (2019), the use of advanced Industry 4.0 technologies in the energy economy provides advantages only in the production (but not in distribution) processes. The argumentation of this conclusion is based on the fact that the relationship of energy sustainability with the readiness for Frontier Technologies Index and with the government AI Readiness Index among countries of different categories is much stronger in the top countries by GDP per unit of energy use compared to other categories of countries. Consequently, advanced technologies of Industry 4.0 contribute to the growth of energy efficiency of the economy, but only to a small extent improve distribution processes.

In contrast to Maggiore et al. (2021), Morelli et al. (2022), Wachnik et al. (2022), and Zaidan et al. (2022), it was justified that, in order to take advantage of the use of advanced technologies of Industry 4.0 in the energy economy, it is advisable to actively use them only in entrepreneurship, while their use in society and the state does not provide advantages with the current approach to the development of the energy economy based on Industry 4.0 technologies. The reasoning of this conclusion is based on the revealed absence of a positive contribution of the government AI Readiness Index to the sustainability of energy.

Unlike Baxter (2012), Inshakov et al. (2019), Kabeyi and Olanrewaju (2022), Kapitonov et al. (2019), Kluczek et al. (2021), and Ratner et al. (2022), it was proved that digitalization of the energy economy based on advanced technologies of Industry 4.0 is not universal—it should be based on a unique organizational model for each category of countries, considering its peculiarities. The reasoning of this conclusion is based on the fundamental differences in the connection of energy sustainability with the readiness for the Frontier Technologies Index and with the government AI Readiness Index among countries of different categories.

Furthermore, this study contributes to the development of the methodology for monitoring the development of digital energetics based on the technologies of Industry 4.0. The methodological guidelines proposed in this study allow for the highly accurate quantification of the competitiveness (through the arithmetic mean of Industry 4.0 technologies, sustainability, and environmental friendliness of the energy economy) and efficiency (through the ratio of sustainability and environmental friendliness of the energy economy to Industry 4.0 technologies) of the digital energy economy.

This is of particular assistance in the “decade of action”—in the modern global context, where the implementation of SDG 7 is the priority of the development of the digital energy economy. Authors’ guidelines have established a methodological basis for the measurement (evaluation formulas, regression model) and management (a new approach to the development of digital energetics based on the technologies of Industry 4.0) of the development of the digital energy economy to support the implementation of SDG 7.

Conclusion

Therefore, the global monitoring of the development of digital energetics based on the technologies of Industry 4.0 has shown that, with the current approach, the connection between digitalization and energy sustainability is weak. Although Industry 4.0 technologies generally determine the sustainability and environmental friendliness of the global energy economy by 67.78%, their relationship is contradictory at the level of certain categories of countries. In the top countries in terms of GDP per unit of energy use, Industry 4.0 technologies determine the sustainability and environmental friendliness of the energy economy by 78%–91%. In the top countries in terms of energy imports, this contribution is lower and amounts to 65%–67%, whereas in the top countries in terms of fuel exports, no positive contribution has been identified. This indicates significant differences in the development of digital energetics based on the technologies of Industry 4.0 (IoT, blockchain, robots, and AI) across the world.

In order to solve this problem, a new (alternative) approach to the development of digital energetics based on the technologies of Industry 4.0 is proposed, supporting the implementation of SDG 7 and assuming a focus on the digitalization of energy companies, the flexibility necessary to consider the characteristics of each category of countries, and the priority of the efficiency of the digital energy economy.

The theoretical significance of the study is to substantiate the primacy of energy sustainability over its digitalization. This fundamental conclusion allowed us to more accurately determine the order of development of digital energetics based on the technologies of Industry 4.0. The practical significance of the article is explained by the fact that the proposed new approach to the development of digital energetics based on the technologies of Industry 4.0 allows accelerating this development and increasing its efficiency, considering the peculiarities of countries of different categories.

Author Contributions

VK, VL, NF, and EP contributed to the conception and design of the study. VK, VL, NF, and EP wrote sections of the manuscript. All authors contributed to manuscript revision and read and approved the submitted version.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations or those of the publisher, the editors, and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

References

Akram, R., Umar, M., Xiaoli, G., and Chen, F. (2022). Dynamic linkages between energy efficiency, renewable energy along with economic growth and carbon emission. A case of MINT countries an asymmetric analysis. Energy Rep. 8, 2119–2130. doi:10.1016/j.egyr.2022.01.153

CrossRef Full Text | Google Scholar

Amir, M., Prajapati, A. K., and Refaat, S. S. (2022). Dynamic Performance Evaluation of Grid-Connected Hybrid Renewable Energy-Based Power Generation for Stability and Power Quality Enhancement in Smart Grid. Front. Energy Res. 10, 861282. doi:10.3389/fenrg.2022.861282

CrossRef Full Text | Google Scholar

Baxter, R. (2012). Energy storage & the digital economy: Enabling innovative change. Oil Gas J. 110 (12), 8–12.

Google Scholar

Bezbakh, V. V., and Frolova, E. E. (2022). Artificial intelligence in the regulatory context of Industry 4.0 and epistemological optimism. Adv. Res. Russ. Bus. Manag. 2022, 289–307.

Google Scholar

Che, X., Jiang, M., and Fan, C. (2021). Multidimensional Assessment and Alleviation of Global Energy Poverty Aligned With UN SDG 7. Front. Energy Res. 9, 777244. doi:10.3389/fenrg.2021.777244

CrossRef Full Text | Google Scholar

Chen, G., Gao, H., Ma, G., Liu, J., and Yin, W. (2022). The Evolution Trend of “Digital Economy” and Its Enlightenment to Energy Enterprises. Lect. Notes Data Eng. Commun. Technol. 85, 858–863. doi:10.1007/978-981-16-5854-9_114

CrossRef Full Text | Google Scholar

European Comission (2022). Digital Transformation Monitor Germany: Industrie 4.0, January 2017. Available at: https://ati.ec.europa.eu/sites/default/files/2020-06/DTM_Industrie%204.0_DE.pdf (accessed date: 05.06.2022).

Google Scholar

Favi, C., Marconi, M., Mandolini, M., and Germani, M. (2022). Sustainable life cycle and energy management of discrete manufacturing plants in the Industry 4.0 framework. Appl. Energy 312, 118671. doi:10.1016/j.apenergy.2022.118671

CrossRef Full Text | Google Scholar

Firoiu, D., Ionescu, G. H., Pîrvu, R., Cismaș, L. M., Tudor, S., and Patrichi, I. C. (2021). Dynamics of implementation of sdg 7 targets in eu member states 5 years after the adoption of the paris agreement. Sustainability 13 (15), 8284. doi:10.3390/su13158284

CrossRef Full Text | Google Scholar

Gawusu, S., Zhang, X., Ahmed, A., Jamatutu, S. A., Miensah, E. D., Amadu, A. A., et al. (2022). Renewable energy sources from the perspective of blockchain integration: From theory to application. Sustain. Energy Technol. Assessments 52, 102108. doi:10.1016/j.seta.2022.102108

CrossRef Full Text | Google Scholar

Ghobakhloo, M., and Fathi, M. (2021). Industry 4.0 and opportunities for energy sustainability. J. Clean. Prod. 295, 126427. doi:10.1016/j.jclepro.2021.126427

CrossRef Full Text | Google Scholar

Gorus, M. S., and Karagol, E. T. (2022). Reactions of energy intensity, energy efficiency, and activity indexes to income and energy price changes: The panel data evidence from OECD countries. Energy 254, 124281. doi:10.1016/j.energy.2022.124281

CrossRef Full Text | Google Scholar

Government of Uk, (2022). Eight great technologies. Available at: https://www.gov.uk/government/speeches/eight-great-technologies (accessed date: 05.06.2022).

Google Scholar

Haddouche, M., and Ilinca, A. (2022). Energy Efficiency and Industry 4.0 in Wood Industry: A Review and Comparison to Other Industries. Energies 15 (7), 2384. doi:10.3390/en15072384

CrossRef Full Text | Google Scholar

He, J., Yang, Y., Liao, Z., Xu, A., and Fang, K. (2022). Linking SDG 7 to assess the renewable energy footprint of nations by 2030. Appl. Energy 317, 119167. doi:10.1016/j.apenergy.2022.119167

CrossRef Full Text | Google Scholar

Hidayatno, A., Destyanto, A. R., and Hulu, C. A. (2019). Industry 4.0 technology implementation impact to industrial sustainable energy in Indonesia: A model conceptualization. Energy Procedia 156, 227–233. doi:10.1016/j.egypro.2018.11.133

CrossRef Full Text | Google Scholar

Huang, G., He, L.-Y., and Lin, X. (2022). Robot adoption and energy performance: Evidence from Chinese industrial firms. Energy Econ. 107, 105837. doi:10.1016/j.eneco.2022.105837

CrossRef Full Text | Google Scholar

Inshakov, O. V., Bogachkova, L. Y., and Popkova, E. G. (2019). Energy efficiency as a driver of global competitiveness, the priority of the state economic policy and the international collaboration of the Russian Federation. Lect. Notes Netw. Syst. 44, 119–134. doi:10.1007/978-3-319-90966-0_9

CrossRef Full Text | Google Scholar

Kabeyi, M. J. B., and Olanrewaju, O. A. (2022). Sustainable Energy Transition for Renewable and Low Carbon Grid Electricity Generation and Supply. Front. Energy Res. 9, 743114. doi:10.3389/fenrg.2021.743114

CrossRef Full Text | Google Scholar

Kanoun, O., Khriji, S., Naifar, S., Bradai, S., Bouattour, G., Bouhamed, A., et al. (2021). Prospects of wireless energy-aware sensors for smart factories in the industry 4.0 era. Electronics 10 (23), 2929. doi:10.3390/electronics10232929

CrossRef Full Text | Google Scholar

Kapitonov, I. A., Filosofova, T. G., and Korolev, V. G. (2019). Development of digital economy in the energy industry-specific modernization. Ijeep 9 (4), 273–282. doi:10.32479/ijeep.8013

CrossRef Full Text | Google Scholar

Kluczek, A., Żegleń, P., and Matušíková, D. (2021). The use of prospect theory for energy sustainable Industry 4.0. Energies 14 (22), 7694. doi:10.3390/en14227694

CrossRef Full Text | Google Scholar

Knez, S., Šimić, G., Milovanović, A., Starikova, S., and Županič, F. Ž. (2022). Prices of conventional and renewable energy as determinants of sustainable and secure energy development: regression model analysis. Energ Sustain Soc. 12 (1), 6. doi:10.1186/s13705-022-00333-9

CrossRef Full Text | Google Scholar

Koyuncu, T., Beşer, M. K., and Alola, A. A. (2021). Environmental sustainability statement of economic regimes with energy intensity and urbanization in Turkey: a threshold regression approach. Environ. Sci. Pollut. Res. 28 (31), 42533–42546. doi:10.1007/s11356-021-13686-z

CrossRef Full Text | Google Scholar

Krishnan, P. R., and Jacob, J. (2022). An IOT based efficient energy management in smart grid using DHOCSA technique. Sustain. Cities Soc. 79, 103727. doi:10.1016/j.scs.2022.103727

CrossRef Full Text | Google Scholar

Madurai Elavarasan, R., Pugazhendhi, R., Jamal, T., Dyduch, J., Arif, M. T., Manoj Kumar, N., et al. (2021). Envisioning the UN Sustainable Development Goals (SDGs) through the lens of energy sustainability (SDG 7) in the post-COVID-19 world. Appl. Energy 292, 116665. doi:10.1016/j.apenergy.2021.116665

CrossRef Full Text | Google Scholar

Maggiore, S., Realini, A., Zagano, C., Bazzocchi, F., Gobbi, E., and Borgarello, M. (2021). Energy efficiency in Industry 4.0: assessing the potential of Industry 4.0 to achieve 2030 decarbonisation targets. Int. J. EQ 6 (4), 371–381. doi:10.2495/EQ-V6-N4-371-381

CrossRef Full Text | Google Scholar

Mahmoudian Esfahani, M. (2022). A hierarchical blockchain-based electricity market framework for energy transactions in a security-constrained cluster of microgrids. Int. J. Electr. Power & Energy Syst. 139, 108011. doi:10.1016/j.ijepes.2022.108011

CrossRef Full Text | Google Scholar

Matsunaga, F., Zytkowski, V., Valle, P., and Deschamps, F. (2022). Optimization of Energy Efficiency in Smart Manufacturing Through the Application of Cyber-Physical Systems and Industry 4.0 Technologies. J. Energy Resour. Technol. Trans. ASME 144 (10), 102104. doi:10.1115/1.4053868

CrossRef Full Text | Google Scholar

Morelli, G., Magazzino, C., Gurrieri, A. R., Pozzi, C., and Mele, M. (2022). Designing Smart Energy Systems in an Industry 4.0 Paradigm towards Sustainable Environment. Sustainability 14 (6), 3315. doi:10.3390/su14063315

CrossRef Full Text | Google Scholar

Nagel, N. O., Kirkerud, J. G., and Bolkesjø, T. F. (2022). The economic competitiveness of flexibility options: A model study of the European energy transition. J. Clean. Prod. 350, 131534. doi:10.1016/j.jclepro.2022.131534

CrossRef Full Text | Google Scholar

Otoum, S., Ridhawi, I. A., and Mouftah, H. (2022). A Federated Learning and Blockchain-enabled Sustainable Energy-Trade at the Edge: A Framework for Industry 4.0. IEEE Internet Things J., 1. doi:10.1109/JIOT.2022.3140430

CrossRef Full Text | Google Scholar

Oxford Insights (2022). Government AI Readiness Index 2021. Available at: https://static1.squarespace.com/static/58b2e92c1e5b6c828058484e/t/61ead0752e7529590e98d35f/1642778757117/Government_AI_Readiness_21.pdf.

Google Scholar

Popkova, E. G. (2022). Advanced Issues in the Green Economy and Sustainable Development in Emerging Market Economies (Elements in the Economics of Emerging Markets). Cambridge: Cambridge University Press. doi:10.1017/9781009093408 Advanced Issues in the Green Economy and Sustainable Development in Emerging Market Economies.

CrossRef Full Text | Google Scholar

Ratner, S., Berezin, A., Gomonov, K., Serletis, A., and Sergi, B. S. (2022). What is stopping energy efficiency in Russia? Exploring the confluence of knowledge, negligence, and other social barriers in the Krasnodar Region. Energy Res. Soc. Sci. 85, 102412. doi:10.1016/j.erss.2021.102412

CrossRef Full Text | Google Scholar

Shuai, J., Zhao, Y., Wang, Y., and Cheng, J. (2022). Renewable energy product competitiveness: Evidence from the United States, China and India. Energy 249, 123614. doi:10.1016/j.energy.2022.123614

CrossRef Full Text | Google Scholar

UNCTAD (2022). Technology And Innovation Report 2021 Catching technological waves Innovation with equity. Available at: https://unctad.org/system/files/official-document/tir2020_en.pdf (Accessed April 20, 2022).

Google Scholar

Vlasov, A. I., Shakhnov, V. A., Filin, S. S., and Krivoshein, A. I. (2019). Sustainable energy systems in the digital economy: Concept of smart machines. Jesi 6 (4), 1975–1986. doi:10.9770/jesi.2019.6.4(3010.9770/jesi.2019.6.4(30)

CrossRef Full Text | Google Scholar

Wachnik, B., Kłodawski, M., and Kardas-Cinal, E. (2022). Reduction of the Information Gap Problem in Industry 4.0 Projects as a Way to Reduce Energy Consumption by the Industrial Sector. Energies 15 (3), 1108. doi:10.3390/en15031108

CrossRef Full Text | Google Scholar

World Bank (2022). Indicators: Energy and Mining. Available at: https://data.worldbank.org/indicator (Accessed April 20, 2022).

Google Scholar

World Energy Council (2022). Energy Trilemma Index. Available at: https://trilemma.worldenergy.org/ (Accessed April 20, 2022).

Google Scholar

Yu, M., Kubiczek, J., Ding, K., Jahanzeb, A., and Iqbal, N. (2022). Revisiting SDG-7 under energy efficiency vision 2050: the role of new economic models and mass digitalization in OECD. Energy Effic. 15 (1), 2. doi:10.1007/s12053-021-10010-z

PubMed Abstract | CrossRef Full Text | Google Scholar

Zaidan, E., Ghofrani, A., Abulibdeh, A., and Jafari, M. (2022). Accelerating the Change to Smart Societies- a Strategic Knowledge-Based Framework for Smart Energy Transition of Urban Communities. Front. Energy Res. 10, 852092. doi:10.3389/fenrg.2022.852092

CrossRef Full Text | Google Scholar

Zhao, W., Chen, J., Hai, T., Mohammed, M. N., Yaseen, Z. M., Yang, X., et al. (2022). Design of low-energy buildings in densely populated urban areas based on IoT. Energy Rep. 8, 4822–4833. doi:10.1016/j.egyr.2022.03.139

CrossRef Full Text | Google Scholar