Home / Current Issue / Paper 1703516
Advances in Digital Twin Technology for Monitoring Energy Supply Chain Operations
Subject area: Science,Engineering and Technology · Area of research: Digital Twin Technology
Abstract
Advances in digital twin technology have significantly enhanced the monitoring and optimization of energy supply chain operations. A digital twin is a virtual replica of physical assets, systems, or processes that allows real-time monitoring, simulation, and analysis to improve operational efficiency. In the energy sector, the implementation of digital twins provides a powerful tool to simulate the entire supply chain, from energy generation to distribution and consumption, enabling better decision-making, predictive maintenance, and optimization of resources. This paper explores the role of digital twin technology in the energy sector, focusing on its application for monitoring energy supply chain operations. By leveraging real-time data from sensors, IoT devices, and advanced analytics, digital twins enable energy companies to create accurate models of their infrastructure and processes. These models allow for continuous monitoring of critical systems, such as power plants, transmission lines, and distribution networks, identifying potential issues before they become critical, reducing downtime, and optimizing asset management. The integration of digital twin technology with other technologies like IoT and AI further enhances its capabilities. IoT sensors provide real-time data on equipment performance, energy consumption, and environmental conditions, which digital twins use to simulate and predict future scenarios. AI algorithms can then analyze these scenarios to optimize operations, reduce inefficiencies, and enhance resource allocation. Furthermore, digital twins facilitate collaboration between different stakeholders in the energy supply chain, providing a common platform for monitoring and decision-making. The paper also discusses the benefits of digital twin technology, including improved operational efficiency, reduced operational costs, better risk management, and enhanced sustainability. It highlights case studies from the energy sector where digital twins have been successfully implemented, demonstrating their impact on operational performance and the overall efficiency of energy supply chains.
Keywords
Digital Twin, Energy Supply Chain, Real-Time Monitoring, Iot, Predictive Maintenance, Operational Efficiency, Asset Management, AI, Optimization, Sustainability
References
[1] Adejugbe, A. (2020). Comparison Between Unfair Dismissal Law in Nigeria and the International Labour Organization’s Legal Regime. Social Science Research Network Electronic Journal. DOI:10.2139/ssrn.3697717
[2] Adejugbe, A., (2021). From Contract to Status: Unfair Dismissal Law. Nnamdi Azikiwe University Journal of Commercial and Property Law, 8(1), pp. 39-53. https://journals.unizik.edu.ng/jcpl/article/view/649/616
[3] Adejugbe, A., Adejugbe A. (2014). Cost and Event in Arbitration (Case Study: Nigeria). Social Science Research Network Electronic Journal. DOI:10.2139/ssrn.2830454
[4] Adejugbe, A., Adejugbe A. (2015). Vulnerable Children Workers and Precarious Work in a Changing World in Nigeria. Social Science Research Network Electronic Journal. DOI:10.2139/ssrn.2789248
[5] Adejugbe, A., Adejugbe A. (2016). A Critical Analysis of the Impact of Legal Restriction on Management and Performance of an Organization Diversifying into Nigeria. Social Science Research Network Electronic Journal. DOI:10.2139/ssrn.2742385
[6] Adejugbe, A., Adejugbe A. (2018). Women and Discrimination in the Workplace: A Nigerian Perspective. Social Science Research Network Electronic Journal. DOI:10.2139/ssrn.3244971
[7] Adejugbe, A., Adejugbe A. (2019). Constitutionalisation of Labour Law: A Nigerian Perspective. Social Science Research Network Electronic Journal. DOI:10.2139/ssrn.3311225
[8] Adejugbe, A., Adejugbe A. (2019). The Certificate of Occupancy as a Conclusive Proof of Title: Fact or Fiction. Social Science Research Network Electronic Journal. DOI:10.2139/ssrn.3324775
[9] Adejugbe, A., Adejugbe A. (2020). The Philosophy of Unfair Dismissal Law in Nigeria. Social Science Research Network Electronic Journal. DOI:10.2139/ssrn.3697696
[10] Adejugbe, A., Adejugbe, A. (2018). Emerging Trends in Job Security: A Case Study of Nigeria (1st ed.). LAP LAMBERT Academic Publishing. https://www.amazon.com/Emerging-Trends-Job-Security-Nigeria/dp/6202196769
[11] Adeniran, A. I., Abhulimen, A. O., Obiki-Osafiele. A. N., Osundare, O. S., Efunniyi, C. P., Agu, E. E. (2022). Digital banking in Africa: A conceptual review of financial inclusion and socio-economic development. International Journal of Applied Research in Social Sciences, 2022, 04(10), 451-480, https://doi.org/10.51594/ijarss.v4i10.1480
[12] Adeniran, I. A, Abhulimen A.O, Obiki-Osafiele, A.N, Osundare O.S, Efunniyi C.P, & Agu E.E. (2022): Digital banking in Africa: A conceptual review of financial inclusion and socio-economic development. International Journal of Applied Research in Social Sciences, Volume 4, Issue 10, P.No. 451-480, 2022
[13] Adenugba, A. A & Dagunduro A. O (2021): Leadership style and Decision Making As Determinants of Employee Commitment in Local Governments in Nigeria: International Journal of Management Studies and Social Science Research (IJMSSSR), 3(4), 257-267https://www.ijmsssr.org/paper/IJMSSSR00418.pdf
[14] Adenugba, A. A, & Dagunduro, A.O. (2019). Collective Bargaining. In Okafor, E.E., Adetola, O.B, Aborisade, R. A. & Abosede, A. J (Eds.) (June, 2019). Human Resources: Industrial Relations and Management Perspectives. 89 – 104. ISBN 078-978-55747-2-2. (Nigeria)
[15] Adenugba, A. A, Dagunduro, A. O & Akhutie, R. (2018): An Investigation into the Effects of Gender Gap in Family Roles in Nigeria: The Case of Ibadan City. African Journal of Social Sciences (AJSS), 8(2), 37-47. https://drive.google.com/file/d/1eQa16xEF58KTmY6-8x4X8HDhk-K-JF1M/view
[16] Adenugba, A. A, Excel, K. O & Dagunduro, A.O (2019): Gender Differences in the Perception and Handling of Occupational Stress Among Workers in Commercial Banks in IBADAN, Nigeria: African Journal for the Psychological Studies of Social Issues (AJPSSI), 22(1), 133- 147. https://ajpssi.org/index.php/ajpssi/article/view/371
[17] Adepoju, O., Esan, O., & Akinyomi, O. (2022). Food security in Nigeria: enhancing workers’ productivity in precision agriculture. Journal of Digital Food, Energy & Water Systems, 3(2).
[18] Aftab, A. A. R. I., Ismail, A. R., Ibupoto, Z. H., Akeiber, H., & Malghani, M. G. K. (2017). Nanoparticles based drilling muds a solution to drill elevated temperature wells: A review. Renewable and Sustainable Energy Reviews, 76, 1301-1313.
[19] Agemar, T., Weber, J., & Schulz, R. (2014). Deep geothermal energy production in Germany. Energies, 7(7), 4397-4416.
[20] Agu, E.E, Abhulimen A.O, Obiki-Osafiele, A.N, Osundare O.S, Adeniran I.A & Efunniyi C.P. (2022): Artificial Intelligence in African Insurance: A review of risk management and fraud prevention. International Journal of Management & Entrepreneurship Research, Volume 4, Issue 12, P.No.768-794, 2022.
[21] Agupugo, C. P., & Tochukwu, M. F. C. (2021): A model to Assess the Economic Viability of Renewable Energy Microgrids: A Case Study of Imufu Nigeria.
[22] Agupugo, C. P., Ajayi, A. O., Nwanevu, C., & Oladipo, S. S. (2022); Advancements in Technology for Renewable Energy Microgrids.
[23] Agupugo, C. P., Ajayi, A. O., Nwanevu, C., & Oladipo, S. S. (2022): Policy and regulatory framework supporting renewable energy microgrids and energy storage systems.
[24] Ahlstrom, D., Arregle, J. L., Hitt, M. A., Qian, G., Ma, X., & Faems, D. (2020). Managing technological, sociopolitical, and institutional change in the new normal. Journal of Management Studies, 57(3), 411-437.
[25] Ahmad, T., Madonski, R., Zhang, D., Huang, C., & Mujeeb, A. (2022). Data-driven probabilistic machine learning in sustainable smart energy/smart energy systems: Key developments, challenges, and future research opportunities in the context of smart grid paradigm. Renewable and Sustainable Energy Reviews, 160, 112128.
[26] Ahmad, T., Zhang, D., Huang, C., Zhang, H., Dai, N., Song, Y., & Chen, H. (2021). Artificial intelligence in sustainable energy industry: Status Quo, challenges and opportunities. Journal of Cleaner Production, 289, 125834.
[27] Akpan, E. U. (2019). Water-based drilling fluids for high temperature and dispersible shale formation applications. University of Salford (United Kingdom).
[28] Alagorni, A. H., Yaacob, Z. B., & Nour, A. H. (2015). An overview of oil production stages: enhanced oil recovery techniques and nitrogen injection. International Journal of Environmental Science and Development, 6(9), 693.
[29] AlBahrani, H., Alsheikh, M., Wagle, V., & Alshakhouri, A. (2022, March). Designing Drilling Fluids Rheological Properties with a Numerical Geomechanics Model for the Purpose of Improving Wellbore Stability. In SPE/IADC Drilling Conference and Exhibition (p. D011S009R003). SPE.
[30] Ali, I., Ahmad, M., Arain, A. H., Atashbari, V., & Zamir, A. (2022). Utilization of Biopolymers in Water Based Drilling Muds. In Drilling Engineering and Technology-Recent Advances New Perspectives and Applications. IntechOpen.
[31] Bassey, K. E. (2022). Enhanced Design and Development Simulation and Testing. Engineering Science & Technology Journal, 3(2), 18-31.
[32] Bassey, K. E. (2022). Optimizing Wind Farm Performance Using Machine Learning. Engineering Science & Technology Journal, 3(2), 32-44.
[33] Beiranvand, B., & Rajaee, T. (2022). Application of artificial intelligence-based single and hybrid models in predicting seepage and pore water pressure of dams: A state-of-the-art review. Advances in Engineering Software, 173, 103268.
[34] Bello, O. A., Folorunso, A., Ogundipe, A., Kazeem, O., Budale, A., Zainab, F., & Ejiofor, O. E. (2022). Enhancing Cyber Financial Fraud Detection Using Deep Learning Techniques: A Study on Neural Networks and Anomaly Detection. International Journal of Network and Communication Research, 7(1), 90-113.
[35] Bristol-Alagbariya, B., Ayanponle, O. L., & Ogedengbe, D. E. (2022). Integrative HR approaches in mergers and acquisitions ensuring seamless organizational synergies. Magna Scientia Advanced Research and Reviews, 6(01), 078–085. Magna Scientia Advanced Research and Reviews.
[36] Bristol-Alagbariya, B., Ayanponle, O. L., & Ogedengbe, D. E. (2022). Strategic frameworks for contract management excellence in global energy HR operations. GSC Advanced Research and Reviews, 11(03), 150–157. GSC Advanced Research and Reviews.
[37] Bristol-Alagbariya, B., Ayanponle, O. L., & Ogedengbe, D. E. (2022). Developing and implementing advanced performance management systems for enhanced organizational productivity. World Journal of Advanced Science and Technology, 2(01), 039–046. World Journal of Advanced Science and Technology.
[38] Chen, X., Cao, W., Gan, C., & Wu, M. (2022). A hybrid partial least squares regression-based real time pore pressure estimation method for complex geological drilling process. Journal of Petroleum Science and Engineering, 210, 109771.
[39] Chenic, A. Ș., Cretu, A. I., Burlacu, A., Moroianu, N., Vîrjan, D., Huru, D., ... & Enachescu, V. (2022). Logical analysis on the strategy for a sustainable transition of the world to green energy—2050. Smart cities and villages coupled to renewable energy sources with low carbon footprint. Sustainability, 14(14), 8622.
[40] Child, M., Koskinen, O., Linnanen, L., & Breyer, C. (2018). Sustainability guardrails for energy scenarios of the global energy transition. Renewable and Sustainable Energy Reviews, 91, 321-334.
[41] Chukwuemeka, A. O., Amede, G., & Alfazazi, U. (2017). A Review of Wellbore Instability During Well Construction: Types, Causes, Prevention and Control. Petroleum & Coal, 59(5).
[42] Cordes, E. E., Jones, D. O., Schlacher, T. A., Amon, D. J., Bernardino, A. F., Brooke, S., ... & Witte, U. (2016). Environmental impacts of the deep-water oil and gas industry: a review to guide management strategies. Frontiers in Environmental Science, 4, 58.
[43] Craddock, H. A. (2018). Oilfield chemistry and its environmental impact. John Wiley & Sons.
[44] da Silva Veras, T., Mozer, T. S., & da Silva César, A. (2017). Hydrogen: trends, production and characterization of the main process worldwide. International journal of hydrogen energy, 42(4), 2018-2033.
[45] Dagunduro A. O & Adenugba A. A (2020): Failure to Meet up to Expectation: Examining Women Activist Groups and Political Movements In Nigeria: De Gruyter; Open Cultural Studies 2020: 4, 23-35.
[46] de Almeida, P. C., Araújo, O. D. Q. F., & de Medeiros, J. L. (2017). Managing offshore drill cuttings waste for improved sustainability. Journal of cleaner production, 165, 143-156.
[47] Diao, H., & Ghorbani, M. (2018). Production risk caused by human factors: a multiple case study of thermal power plants. Frontiers of Business Research in China, 12, 1-27.
[48] Dickson, M. H., & Fanelli, M. (2018). What is geothermal energy?. In Renewable Energy (pp. Vol1_302-Vol1_328). Routledge.
[49] Dominy, S. C., O’Connor, L., Parbhakar-Fox, A., Glass, H. J., & Purevgerel, S. (2018). Geometallurgy—A route to more resilient mine operations. Minerals, 8(12), 560.
[50] Dong, X., Liu, H., Chen, Z., Wu, K., Lu, N., & Zhang, Q. (2019). Enhanced oil recovery techniques for heavy oil and oilsands reservoirs after steam injection. Applied energy, 239, 1190-1211.
[51] Dufour, F. (2018). The Costs and Implications of Our Demand for Energy: A Comparative and comprehensive Analysis of the available energy resources. The Costs and Implications of Our Demand for Energy: A Comparative and Comprehensive Analysis of the Available Energy Resources (2018).
[52] Efunniyi, C.P, Abhulimen A.O, Obiki-Osafiele, A.N,Osundare O.S , Adeniran I.A , & Agu E.E. (2022): Data analytics in African banking: A review of opportunities and challenges for enhancing financial services. International Journal of Management & Entrepreneurship Research, Volume 4, Issue 12, P.No.748-767, 2022.3.
[53] El Bilali, A., Moukhliss, M., Taleb, A., Nafii, A., Alabjah, B., Brouziyne, Y., ... & Mhamed, M. (2022). Predicting daily pore water pressure in embankment dam: Empowering Machine Learning-based modeling. Environmental Science and Pollution Research, 29(31), 47382-47398.
[54] Eldardiry, H., & Habib, E. (2018). Carbon capture and sequestration in power generation: review of impacts and opportunities for water sustainability. Energy, Sustainability and Society, 8(1), 1-15.
[55] Elujide, I., Fashoto, S. G., Fashoto, B., Mbunge, E., Folorunso, S. O., & Olamijuwon, J. O. (2021). Application of deep and machine learning techniques for multi-label classification performance on psychotic disorder diseases. Informatics in Medicine Unlocked, 23, 100545.
[56] Elujide, I., Fashoto, S. G., Fashoto, B., Mbunge, E., Folorunso, S. O., & Olamijuwon, J. O. Informatics in Medicine Unlocked.
[57] Epelle, E. I., & Gerogiorgis, D. I. (2020). A review of technological advances and open challenges for oil and gas drilling systems engineering. AIChE Journal, 66(4), e16842.
[58] Ericson, S. J., Engel-Cox, J., & Arent, D. J. (2019). Approaches for integrating renewable energy technologies in oil and gas operations (No. NREL/TP-6A50-72842). National Renewable Energy Lab.(NREL), Golden, CO (United States).
[59] Erofeev, A., Orlov, D., Ryzhov, A., & Koroteev, D. (2019). Prediction of porosity and permeability alteration based on machine learning algorithms. Transport in Porous Media, 128, 677-700.
[60] Eshiet, K. I. I., & Sheng, Y. (2018). The performance of stochastic designs in wellbore drilling operations. Petroleum Science, 15, 335-365.
[61] Eyinla, D. S., Oladunjoye, M. A., Olayinka, A. I., & Bate, B. B. (2021). Rock physics and geomechanical application in the interpretation of rock property trends for overpressure detection. Journal of Petroleum Exploration and Production, 11, 75-95.
[62] Fakhari, N. (2022). A mud design to improve water-based drilling in clay rich formation (Doctoral dissertation, Curtin University).
[63] Farajzadeh, R., Eftekhari, A. A., Dafnomilis, G., Lake, L. W., & Bruining, J. (2020). On the sustainability of CO2 storage through CO2–Enhanced oil recovery. Applied energy, 261, 114467.
[64] Farajzadeh, R., Glasbergen, G., Karpan, V., Mjeni, R., Boersma, D. M., Eftekhari, A. A., ... & Bruining, J. (2022). Improved oil recovery techniques and their role in energy efficiency and reducing CO2 footprint of oil production. Journal of Cleaner Production, 369, 133308.
[65] Garia, S., Pal, A. K., Ravi, K., & Nair, A. M. (2019). A comprehensive analysis on the relationships between elastic wave velocities and petrophysical properties of sedimentary rocks based on laboratory measurements. Journal of Petroleum Exploration and Production Technology, 9, 1869-1881.
[66] Ghani, A., Khan, F., & Garaniya, V. (2015). Improved oil recovery using CO 2 as an injection medium: a detailed analysis. Journal of Petroleum Exploration and Production Technology, 5, 241-254.
[67] Gil-Ozoudeh, I., Iwuanyanwu, O., Okwandu, A. C., & Ike, C. S. (2022). The role of passive design strategies in enhancing energy efficiency in green buildings. Engineering Science & Technology Journal, Volume 3, Issue 2, December 2022, No.71-91
[68] Gil-Ozoudeh, I., Iwuanyanwu, O., Okwandu, A. C., & Ike, C. S. (2022). Life cycle assessment of green buildings: A comprehensive analysis of environmental impacts (pp. 729-747). Publisher. p. 730.
[69] Glassley, W. E. (2014). Geothermal energy: renewable energy and the environment. CRC press.
[70] Govender, P., Fashoto, S. G., Maharaj, L., Adeleke, M. A., Mbunge, E., Olamijuwon, J., ... & Okpeku, M. (2022). The application of machine learning to predict genetic relatedness using human mtDNA hypervariable region I sequences. Plos one, 17(2), e0263790.
[71] Griffiths, S. (2017). A review and assessment of energy policy in the Middle East and North Africa region. Energy Policy, 102, 249-269.
[72] Gür, T. M. (2022). Carbon dioxide emissions, capture, storage and utilization: Review of materials, processes and technologies. Progress in Energy and Combustion Science, 89, 100965.
[73] Hoseinpour, M., & Riahi, M. A. (2022). Determination of the mud weight window, optimum drilling trajectory, and wellbore stability using geomechanical parameters in one of the Iranian hydrocarbon reservoirs. Journal of Petroleum Exploration and Production Technology, 1-20.
[74] Hossain, M. E., Al-Majed, A., Adebayo, A. R., Apaleke, A. S., & Rahman, S. M. (2017). A Critical Review of Drilling Waste Management Towards Sustainable Solutions. Environmental Engineering & Management Journal (EEMJ), 16(7).
[75] Huaman, R. N. E., & Jun, T. X. (2014). Energy related CO2 emissions and the progress on CCS projects: a review. Renewable and Sustainable Energy Reviews, 31, 368-385.
[76] Iwuanyanwu, O., Gil-Ozoudeh, I., Okwandu, A. C., & Ike, C. S. (2022). The integration of renewable energy systems in green buildings: Challenges and opportunities. Journal of Applied
[77] Jafarizadeh, F., Rajabi, M., Tabasi, S., Seyedkamali, R., Davoodi, S., Ghorbani, H., ... & Csaba, M. (2022). Data driven models to predict pore pressure using drilling and petrophysical data. Energy Reports, 8, 6551-6562.
[78] Jamrozik, A., Protasova, E., Gonet, A., Bilstad, T., & Żurek, R. (2016). Characteristics of oil based muds and influence on the environment. AGH Drilling, Oil, Gas, 33(4).
[79] Jharap, G., van Leeuwen, L. P., Mout, R., van der Zee, W. E., Roos, F. M., & Muntendam-Bos, A. G. (2020). Ensuring safe growth of the geothermal energy sector in the Netherlands by proactively addressing risks and hazards. Netherlands Journal of Geosciences, 99, e6.
[80] Jomthanachai, S., Wong, W. P., & Lim, C. P. (2021). An application of data envelopment analysis and machine learning approach to risk management. Ieee Access, 9, 85978-85994.
[81] Kabeyi, M. J. B. (2019). Geothermal electricity generation, challenges, opportunities and recommendations. International Journal of Advances in Scientific Research and Engineering (ijasre), 5(8), 53-95.
[82] Kabeyi, M. J. B., & Olanrewaju, O. A. (2022). Sustainable energy transition for renewable and low carbon grid electricity generation and supply. Frontiers in Energy research, 9, 743114.
[83] Karad, S., & Thakur, R. (2021). Efficient monitoring and control of wind energy conversion systems using Internet of things (IoT): a comprehensive review. Environment, development and sustainability, 23(10), 14197-14214.
[84] Khalid, P., Ahmed, N., Mahmood, A., Saleem, M. A., & Hassan. (2016). An integrated seismic interpretation and rock physics attribute analysis for pore fluid discrimination. Arabian Journal for Science and Engineering, 41, 191-200.
[85] Kinik, K., Gumus, F., & Osayande, N. (2015). Automated dynamic well control with managed-pressure drilling: a case study and simulation analysis. SPE Drilling & Completion, 30(02), 110-118.
[86] Kiran, R., Teodoriu, C., Dadmohammadi, Y., Nygaard, R., Wood, D., Mokhtari, M., & Salehi, S. (2017). Identification and evaluation of well integrity and causes of failure of well integrity barriers (A review). Journal of Natural Gas Science and Engineering, 45, 511-526.
[87] Kumari, W. G. P., & Ranjith, P. G. (2019). Sustainable development of enhanced geothermal systems based on geotechnical research–A review. Earth-Science Reviews, 199, 102955.
[88] Leung, D. Y., Caramanna, G., & Maroto-Valer, M. M. (2014). An overview of current status of carbon dioxide capture and storage technologies. Renewable and sustainable energy reviews, 39, 426-443.
[89] Li, G., Song, X., Tian, S., & Zhu, Z. (2022). Intelligent drilling and completion: a review. Engineering, 18, 33-48.
[90] Li, H., & Zhang, J. (2018). Well log and seismic data analysis for complex pore-structure carbonate reservoir using 3D rock physics templates. Journal of applied Geophysics, 151, 175-183.
[91] Li, W., Zhang, Q., Zhang, Q., Guo, F., Qiao, S., Liu, S., ... & Heng, X. (2019). Development of a distributed hybrid seismic–electrical data acquisition system based on the Narrowband Internet of Things (NB-IoT) technology. Geoscientific Instrumentation, Methods and Data Systems, 8(2), 177-186.
[92] Lindi, O. (2017). Analysis of Kick Detection Methods in the Light of Actual Blowout Disasters (Master's thesis, NTNU).
[93] Liu, W., Zhang, G., Cao, J., Zhang, J., & Yu, G. (2019). Combined petrophysics and 3D seismic attributes to predict shale reservoirs favourable areas. Journal of Geophysics and Engineering, 16(5), 974-991.
[94] Lohne, H. P., Ford, E. P., Mansouri, M., & Randeberg, E. (2016). Well integrity risk assessment in geothermal wells–Status of today. GeoWell, Stavanger.
[95] Luo, Y., Huang, H., Jakobsen, M., Yang, Y., Zhang, J., & Cai, Y. (2019). Prediction of porosity and gas saturation for deep-buried sandstone reservoirs from seismic data using an improved rock-physics model. Acta Geophysica, 67, 557-575.
[96] Mac Kinnon, M. A., Brouwer, J., & Samuelsen, S. (2018). The role of natural gas and its infrastructure in mitigating greenhouse gas emissions, improving regional air quality, and renewable resource integration. Progress in Energy and Combustion science, 64, 62-92.
[97] Mahmood, A., Thibodeaux, R., Angelle, J., & Smith, L. (2022, April). Digital transformation for promoting renewable energy & sustainability: A systematic approach for carbon footprint reduction in well construction. In Offshore Technology Conference (p. D031S038R005). OTC.
[98] Maraveas, C., Piromalis, D., Arvanitis, K. G., Bartzanas, T., & Loukatos, D. (2022). Applications of IoT for optimized greenhouse environment and resources management. Computers and Electronics in Agriculture, 198, 106993.
[99] Marhoon, T. M. M. (2020). High pressure High temperature (HPHT) wells technologies while drilling (Doctoral dissertation, Politecnico di Torino).
[100] Martin, C. (2022). Innovative drilling muds for High Pressure and High Temperature (HPHT) condition using a novel nanoparticle for petroleum engineering systems (Doctoral dissertation).
[101] Martin-Roberts, E., Scott, V., Flude, S., Johnson, G., Haszeldine, R. S., & Gilfillan, S. (2021). Carbon capture and storage at the end of a lost decade. One Earth, 4(11), 1569-1584.
[102] Matthews, V. O., Idaike, S. U., Noma-Osaghae, E., Okunoren, A., & Akwawa, L. (2018). Design and Construction of a Smart Wireless Access/Ignition Technique for Automobile. International Journal for Research in Applied Science & Engineering Technology (IJRASET), 6(8), 165-173.
[103] McCollum, D. L., Zhou, W., Bertram, C., De Boer, H. S., Bosetti, V., Busch, S., ... & Riahi, K. (2018). Energy investment needs for fulfilling the Paris Agreement and achieving the Sustainable Development Goals. Nature Energy, 3(7), 589-599.
[104] Mikunda, T., Brunner, L., Skylogianni, E., Monteiro, J., Rycroft, L., & Kemper, J. (2021). Carbon capture and storage and the sustainable development goals. International Journal of Greenhouse Gas Control, 108, 103318.
[105] Misra, S., Liu, R., Chakravarty, A., & Gonzalez, K. (2022). Machine learning tools for fossil and geothermal energy production and carbon geo-sequestration—a step towards energy digitization and geoscientific digitalization. Circular Economy and Sustainability, 2(3), 1225-1240.
[106] Mohd Aman, A. H., Shaari, N., & Ibrahim, R. (2021). Internet of things energy system: Smart applications, technology advancement, and open issues. International Journal of Energy Research, 45(6), 8389-8419.
[107] Mohsen, O., & Fereshteh, N. (2017). An extended VIKOR method based on entropy measure for the failure modes risk assessment–A case study of the geothermal power plant (GPP). Safety science, 92, 160-172.
[108] Mosca, F., Djordjevic, O., Hantschel, T., McCarthy, J., Krueger, A., Phelps, D., ... & MacGregor, A. (2018). Pore pressure prediction while drilling: Three-dimensional earth model in the Gulf of Mexico. AAPG Bulletin, 102(4), 691-708.
[109] Mrdjen, I., & Lee, J. (2016). High volume hydraulic fracturing operations: potential impacts on surface water and human health. International journal of environmental health research, 26(4), 361-380.
[110] Mushtaq, N., Singh, D. V., Bhat, R. A., Dervash, M. A., & Hameed, O. B. (2020). Freshwater contamination: sources and hazards to aquatic biota. Fresh water pollution dynamics and remediation, 27-50.
[111] Muther, T., Syed, F. I., Lancaster, A. T., Salsabila, F. D., Dahaghi, A. K., & Negahban, S. (2022). Geothermal 4.0: AI-enabled geothermal reservoir development-current status, potentials, limitations, and ways forward. Geothermics, 100, 102348.
[112] Najibi, A. R., & Asef, M. R. (2014). Prediction of seismic-wave velocities in rock at various confining pressures based on unconfined data. Geophysics, 79(4), D235-D242.
[113] Najibi, A. R., Ghafoori, M., Lashkaripour, G. R., & Asef, M. R. (2017). Reservoir geomechanical modeling: In-situ stress, pore pressure, and mud design. Journal of Petroleum Science and Engineering, 151, 31-39.
[114] Napp, T. A., Gambhir, A., Hills, T. P., Florin, N., & Fennell, P. S. (2014). A review of the technologies, economics and policy instruments for decarbonising energy-intensive manufacturing industries. Renewable and Sustainable Energy Reviews, 30, 616-640.
[115] Nduagu, E. I., & Gates, I. D. (2015). Unconventional heavy oil growth and global greenhouse gas emissions. Environmental science & technology, 49(14), 8824-8832.
[116] Nguyen, H. H., Khabbaz, H., Fatahi, B., Vincent, P., & Marix-Evans, M. (2014, October). Sustainability considerations for ground improvement techniques using controlled modulus columns. In AGS Symposium on Resilient Geotechnics. The Australian Geomechanics Society.
[117] Nimana, B., Canter, C., & Kumar, A. (2015). Energy consumption and greenhouse gas emissions in upgrading and refining of Canada's oil sands products. Energy, 83, 65-79.
[118] Njuguna, J., Siddique, S., Kwroffie, L. B., Piromrat, S., Addae-Afoakwa, K., Ekeh-Adegbotolu, U., ... & Moller, L. (2022). The fate of waste drilling fluids from oil & gas industry activities in the exploration and production operations. Waste Management, 139, 362-380.
[119] Okeke, C.I, Agu E.E, Ejike O.G, Ewim C.P-M and Komolafe M.O. (2022): A regulatory model for standardizing financial advisory services in Nigeria. International Journal of Frontline Research in Science and Technology, 2022, 01(02), 067–082.
[120] Okeke, I. C., Agu, E. E., Ejike, O. G., Ewim, C. P., & Komolafe, M. O. (2022). Developing a regulatory model for product quality assurance in Nigeria’s local industries. International Journal of Frontline Research in Multidisciplinary Studies, 1(02), 54–69.
[121] Okeke, I. C., Agu, E. E., Ejike, O. G., Ewim, C. P., & Komolafe, M. O. (2022). A service standardization model for Nigeria’s healthcare system: Toward improved patient care. International Journal of Frontline Research in Multidisciplinary Studies, 1(2), 40–53.
[122] Okeke, I. C., Agu, E. E., Ejike, O. G., Ewim, C. P., & Komolafe, M. O. (2022). A model for wealth management through standardized financial advisory practices in Nigeria. International Journal of Frontline Research in Multidisciplinary Studies, 1(2), 27–39.
[123] Okeke, I. C., Agu, E. E., Ejike, O. G., Ewim, C. P., & Komolafe, M. O. (2022). A conceptual model for standardizing tax procedures in Nigeria’s public and private sectors. International Journal of Frontline Research in Multidisciplinary Studies, 1(2), 14–26
[124] Okeke, I. C., Agu, E. E., Ejike, O. G., Ewim, C. P., & Komolafe, M. O. (2022). A conceptual framework for enhancing product standardization in Nigeria’s manufacturing sector. International Journal of Frontline Research in Multidisciplinary Studies, 1(2), 1–13.
[125] Okeke, I. C., Agu, E. E., Ejike, O. G., Ewim, C. P., & Komolafe, M. O. (2022). Modeling a national standardization policy for made-in-Nigeria products: Bridging the global competitiveness gap. International Journal of Frontline Research in Science and Technology, 1(2), 98–109.
[126] Okeke, I. C., Agu, E. E., Ejike, O. G., Ewim, C. P., & Komolafe, M. O. (2022). A theoretical model for standardized taxation of Nigeria’s informal sector: A pathway to compliance. International Journal of Frontline Research in Science and Technology, 1(2), 83–97.
[127] Okeke, I. C., Agu, E. E., Ejike, O. G., Ewim, C. P., & Komolafe, M. O. (2022). A model for foreign direct investment (FDI) promotion through standardized tax policies in Nigeria. International Journal of Frontline Research in Science and Technology, 1(2), 53–66.
[128] Okeke, I. C., Agu, E. E., Ejike, O. G., Ewim, C. P., & Komolafe, M. O. (2022). A regulatory model for standardizing financial advisory services in Nigeria. International Journal of Frontline Research in Science and Technology, 1(2), 67–82.
[129] Okeke, I.C, Agu E.E, Ejike O.G, Ewim C.P-M and Komolafe M.O. (2022): A conceptual model for financial advisory standardization: Bridging the financial literacy gap in Nigeria. International Journal of Frontline Research in Science and Technology, 2022, 01(02), 038–052
[130] Okoroafor, E. R., Smith, C. M., Ochie, K. I., Nwosu, C. J., Gudmundsdottir, H., & Aljubran, M. J. (2022). Machine learning in subsurface geothermal energy: Two decades in review. Geothermics, 102, 102401.
[131] Okwiri, L. A. (2017). Risk assessment and risk modelling in geothermal drilling (Doctoral dissertation).
[132] Olayiwola, T., & Sanuade, O. A. (2021). A data-driven approach to predict compressional and shear wave velocities in reservoir rocks. Petroleum, 7(2), 199-208.
[133] Olufemi, B. A., Ozowe, W. O., & Komolafe, O. O. (2011). Studies on the production of caustic soda using solar powered diaphragm cells. ARPN Journal of Engineering and Applied Sciences, 6(3), 49-54.
[134] Olufemi, B., Ozowe, W., & Afolabi, K. (2012). Operational Simulation of Sola Cells for Caustic. Cell (EADC), 2(6).
[135] Oyedokun, O. O. (2019). Green human resource management practices and its effect on the sustainable competitive edge in the Nigerian manufacturing industry (Dangote) (Doctoral dissertation, Dublin Business School).
[136] Oyeniran, C.O., Adewusi, A.O., Adeleke, A. G., Akwawa, L.A., Azubuko, C. F. (2022). Ethical AI: Addressing bias in machine learning models and software applications. Computer Science & IT Research Journal, 3(3), pp. 115-126
[137] Oyeniran, O. C., Adewusi, A. O., Adeleke, A. G., Akwawa, L. A., & Azubuko, C. F. (2022): Ethical AI: Addressing bias in machine learning models and software applications.
[138] Ozowe, W. O. (2018). Capillary pressure curve and liquid permeability estimation in tight oil reservoirs using pressure decline versus time data (Doctoral dissertation).
[139] Ozowe, W. O. (2021). Evaluation of lean and rich gas injection for improved oil recovery in hydraulically fractured reservoirs (Doctoral dissertation).
[140] Ozowe, W., Quintanilla, Z., Russell, R., & Sharma, M. (2020, October). Experimental evaluation of solvents for improved oil recovery in shale oil reservoirs. In SPE Annual Technical Conference and Exhibition? (p. D021S019R007). SPE.
[141] Ozowe, W., Russell, R., & Sharma, M. (2020, July). A novel experimental approach for dynamic quantification of liquid saturation and capillary pressure in shale. In SPE/AAPG/SEG Unconventional Resources Technology Conference (p. D023S025R002). URTEC.
[142] Ozowe, W., Zheng, S., & Sharma, M. (2020). Selection of hydrocarbon gas for huff-n-puff IOR in shale oil reservoirs. Journal of Petroleum Science and Engineering, 195, 107683.
[143] Pan, S. Y., Gao, M., Shah, K. J., Zheng, J., Pei, S. L., & Chiang, P. C. (2019). Establishment of enhanced geothermal energy utilization plans: Barriers and strategies. Renewable energy, 132, 19-32.
[144] Pereira, L. B., Sad, C. M., Castro, E. V., Filgueiras, P. R., & Lacerda Jr, V. (2022). Environmental impacts related to drilling fluid waste and treatment methods: A critical review. Fuel, 310, 122301.
[145] Popo-Olaniyan, O., James, O. O., Udeh, C. A., Daraojimba, R. E., & Ogedengbe, D. E. (2022). Future-Proofing human resources in the US with AI: A review of trends and implications. International Journal of Management & Entrepreneurship Research, 4(12), 641-658.
[146] Popo-Olaniyan, O., James, O. O., Udeh, C. A., Daraojimba, R. E., & Ogedengbe, D. E. (2022). A review of us strategies for stem talent attraction and retention: challenges and opportunities. International Journal of Management & Entrepreneurship Research, 4(12), 588-606.
[147] Popo-Olaniyan, O., James, O. O., Udeh, C. A., Daraojimba, R. E., & Ogedengbe, D. E. (2022). Review of advancing US innovation through collaborative HR ecosystems: A sector-wide perspective. International Journal of Management & Entrepreneurship Research, 4(12), 623-640.
[148] Quintanilla, Z., Ozowe, W., Russell, R., Sharma, M., Watts, R., Fitch, F., & Ahmad, Y. K. (2021, July). An experimental investigation demonstrating enhanced oil recovery in tight rocks using mixtures of gases and nanoparticles. In SPE/AAPG/SEG Unconventional Resources Technology Conference (p. D031S073R003). URTEC.
[149] Radwan, A. E. (2022). Drilling in complex pore pressure regimes: analysis of wellbore stability applying the depth of failure approach. Energies, 15(21), 7872.
[150] Rahman, M. M., Canter, C., & Kumar, A. (2014). Greenhouse gas emissions from recovery of various North American conventional crudes. Energy, 74, 607-617.
[151] Raliya, R., Saharan, V., Dimkpa, C., & Biswas, P. (2017). Nanofertilizer for precision and sustainable agriculture: current state and future perspectives. Journal of agricultural and food chemistry, 66(26), 6487-6503.
[152] Rashid, M. I., Benhelal, E., & Rafiq, S. (2020). Reduction of greenhouse gas emissions from gas, oil, and coal power plants in Pakistan by carbon capture and storage (CCS): A Review. Chemical Engineering & Technology, 43(11), 2140-2148.
[153] Raza, A., Gholami, R., Rezaee, R., Rasouli, V., & Rabiei, M. (2019). Significant aspects of carbon capture and storage–A review. Petroleum, 5(4), 335-340.
[154] Salam, A., & Salam, A. (2020). Internet of things in sustainable energy systems. Internet of Things for Sustainable Community Development: Wireless Communications, Sensing, and Systems, 183-216.
[155] Seyedmohammadi, J. (2017). The effects of drilling fluids and environment protection from pollutants using some models. Modeling Earth Systems and Environment, 3, 1-14.
[156] Shahbaz, M., Mallick, H., Mahalik, M. K., & Sadorsky, P. (2016). The role of globalization on the recent evolution of energy demand in India: Implications for sustainable development. Energy Economics, 55, 52-68.
[157] Shahbazi, A., & Nasab, B. R. (2016). Carbon capture and storage (CCS) and its impacts on climate change and global warming. J. Pet. Environ. Biotechnol, 7(9).
[158] Shaw, R., & Mukherjee, S. (2022). The development of carbon capture and storage (CCS) in India: A critical review. Carbon Capture Science & Technology, 2, 100036.
[159] Shortall, R., Davidsdottir, B., & Axelsson, G. (2015). Geothermal energy for sustainable development: A review of sustainability impacts and assessment frameworks. Renewable and sustainable energy reviews, 44, 391-406.
[160] Shrestha, N., Chilkoor, G., Wilder, J., Gadhamshetty, V., & Stone, J. J. (2017). Potential water resource impacts of hydraulic fracturing from unconventional oil production in the Bakken shale. Water Research, 108, 1-24.
[161] Soeder, D. J., & Soeder, D. J. (2021). Impacts to human health and ecosystems. Fracking and the Environment: A scientific assessment of the environmental risks from hydraulic fracturing and fossil fuels, 135-153.
[162] Soga, K., Alonso, E., Yerro, A., Kumar, K., & Bandara, S. (2016). Trends in large-deformation analysis of landslide mass movements with particular emphasis on the material point method. Géotechnique, 66(3), 248-273.
[163] Soltani, M., Kashkooli, F. M., Souri, M., Rafiei, B., Jabarifar, M., Gharali, K., & Nathwani, J. S. (2021). Environmental, economic, and social impacts of geothermal energy systems. Renewable and Sustainable Energy Reviews, 140, 110750.
[164] Sowiżdżał, A., Starczewska, M., & Papiernik, B. (2022). Future technology mix—enhanced geothermal system (EGS) and carbon capture, utilization, and storage (CCUS)—an overview of selected projects as an example for future investments in Poland. Energies, 15(10), 3505.
[165] Spada, M., Sutra, E., & Burgherr, P. (2021). Comparative accident risk assessment with focus on deep geothermal energy systems in the Organization for Economic Co-operation and Development (OECD) countries. Geothermics, 95, 102142.
[166] Stober, I., & Bucher, K. (2013). Geothermal energy. Germany: Springer-Verlag Berlin Heidelberg. doi, 10, 978-3.
[167] Sule, I., Imtiaz, S., Khan, F., & Butt, S. (2019). Risk analysis of well blowout scenarios during managed pressure drilling operation. Journal of Petroleum Science and Engineering, 182, 106296.
[168] Suvin, P. S., Gupta, P., Horng, J. H., & Kailas, S. V. (2021). Evaluation of a comprehensive non-toxic, biodegradable and sustainable cutting fluid developed from coconut oil. Proceedings of the Institution of Mechanical Engineers, Part J: Journal of Engineering Tribology, 235(9), 1842-1850.
[169] Suzuki, A., Fukui, K. I., Onodera, S., Ishizaki, J., & Hashida, T. (2022). Data-driven geothermal reservoir modeling: Estimating permeability distributions by machine learning. Geosciences, 12(3), 130.
[170] Szulecki, K., & Westphal, K. (2014). The cardinal sins of European energy policy: Nongovernance in an uncertain global landscape. Global Policy, 5, 38-51.
[171] Tabatabaei, M., Kazemzadeh, F., Sabah, M., & Wood, D. A. (2022). Sustainability in natural gas reservoir drilling: A review on environmentally and economically friendly fluids and optimal waste management. Sustainable Natural Gas Reservoir and Production Engineering, 269-304.
[172] Tahmasebi, P., Kamrava, S., Bai, T., & Sahimi, M. (2020). Machine learning in geo-and environmental sciences: From small to large scale. Advances in Water Resources, 142, 103619.
[173] Tapia, J. F. D., Lee, J. Y., Ooi, R. E., Foo, D. C., & Tan, R. R. (2016). Optimal CO2 allocation and scheduling in enhanced oil recovery (EOR) operations. Applied energy, 184, 337-345.
[174] Teodoriu, C., & Bello, O. (2021). An outlook of drilling technologies and innovations: Present status and future trends. Energies, 14(15), 4499.
[175] Tester, J. W., Beckers, K. F., Hawkins, A. J., & Lukawski, M. Z. (2021). The evolving role of geothermal energy for decarbonizing the United States. Energy & environmental science, 14(12), 6211-6241.
[176] Thomas, L., Tang, H., Kalyon, D. M., Aktas, S., Arthur, J. D., Blotevogel, J., ... & Young, M. H. (2019). Toward better hydraulic fracturing fluids and their application in energy production: A review of sustainable technologies and reduction of potential environmental impacts. Journal of Petroleum Science and Engineering, 173, 793-803.
[177] Tula, O. A., Adekoya, O. O., Isong, D., Daudu, C. D., Adefemi, A., & Okoli, C. E. (2004). Corporate advising strategies: A comprehensive review for aligning petroleum engineering with climate goals and CSR commitments in the United States and Africa. Corporate Sustainable Management Journal, 2(1), 32-38.
[178] Udegbunam, J. E. (2015). Improved well design with risk and uncertainty analysis.
[179] Ugwu, G. Z. (2015). An overview of pore pressure prediction using seismicallyderived velocities. Journal of Geology and Mining Research, 7(4), 31-40.
[180] Van Oort, E., Chen, D., Ashok, P., & Fallah, A. (2021, March). Constructing deep closed-loop geothermal wells for globally scalable energy production by leveraging oil and gas ERD and HPHT well construction expertise. In SPE/IADC Drilling Conference and Exhibition (p. D021S002R001). SPE.
[181] Vesselinov, V. V., O'Malley, D., Frash, L. P., Ahmmed, B., Rupe, A. T., Karra, S., ... & Scharer, J. (2021). Geo Thermal Cloud: Cloud Fusion of Big Data and Multi-Physics Models Using Machine Learning for Discovery, Exploration, and Development of Hidden Geothermal Resources (No. LA-UR-21-24325). Los Alamos National Laboratory (LANL), Los Alamos, NM (United States).
[182] Vielma, W. E., & Mosti, I. (2014, November). Dynamic Modelling for Well Design, Increasing Operational Margins in Challenging Fields. In Abu Dhabi International Petroleum Exhibition and Conference (p. D041S071R003). SPE.
[183] Wang, K., Yuan, B., Ji, G., & Wu, X. (2018). A comprehensive review of geothermal energy extraction and utilization in oilfields. Journal of Petroleum Science and Engineering, 168, 465-477.
[184] Waswa, A. M., Kedi,. W. E.., & Sula, N. (2015). Design and Implementation of a GSM based Fuel Leakage Monitoring System on Trucks in Transit. Abstract of Emerging Trends in Scientific Research, 3, 1-18.
[185] Weldeslassie, T., Naz, H., Singh, B., & Oves, M. (2018). Chemical contaminants for soil, air and aquatic ecosystem. Modern age environmental problems and their remediation, 1-22.
[186] Wennersten, R., Sun, Q., & Li, H. (2015). The future potential for Carbon Capture and Storage in climate change mitigation–an overview from perspectives of technology, economy and risk. Journal of cleaner production, 103, 724-736.
[187] Wilberforce, T., Baroutaji, A., El Hassan, Z., Thompson, J., Soudan, B., & Olabi, A. G. (2019). Prospects and challenges of concentrated solar photovoltaics and enhanced geothermal energy technologies. Science of The Total Environment, 659, 851-861.
[188] Wojtanowicz, A. K. (2016). Environmental control of drilling fluids and produced water. Environmental technology in the oil industry, 101-165.
[189] Wu, Y., Wu, Y., Guerrero, J. M., & Vasquez, J. C. (2021). A comprehensive overview of framework for developing sustainable energy internet: From things-based energy network to services-based management system. Renewable and Sustainable Energy Reviews, 150, 111409.
[190] Younger, P. L. (2015). Geothermal energy: Delivering on the global potential. Energies, 8(10), 11737-11754.
[191] Yu, H., Chen, G., & Gu, H. (2020). A machine learning methodology for multivariate pore-pressure prediction. Computers & Geosciences, 143, 104548.
[192] Yudha, S. W., Tjahjono, B., & Longhurst, P. (2022). Sustainable transition from fossil fuel to geothermal energy: A multi-level perspective approach. Energies, 15(19), 7435.
[193] Zabbey, N., & Olsson, G. (2017). Conflicts–oil exploration and water. Global challenges, 1(5), 1600015.
[194] Zhang, P., Ozowe, W., Russell, R. T., & Sharma, M. M. (2021). Characterization of an electrically conductive proppant for fracture diagnostics. Geophysics, 86(1), E13-E20.
[195] Zhang, Z., & Huisingh, D. (2017). Carbon dioxide storage schemes: technology, assessment and deployment. journal of cleaner production, 142, 1055-1064.
[196] Zhao, X., Li, D., Zhu, H., Ma, J., & An, Y. (2022). Advanced developments in environmentally friendly lubricants for water-based drilling fluid: a review. RSC advances, 12(35), 22853-22868.
How to cite this paper
@article{1703516,
author = {Ekene Cynthia Onukwulu, Ikiomoworio Nicholas Dienagha, Wags Numoipiri Digitemie, Peter Ifechukwude Egbumokei},
title = {Advances in Digital Twin Technology for Monitoring Energy Supply Chain Operations},
journal = {Iconic Research And Engineering Journals},
year = {2022},
volume = {5},
number = {12},
pages = {372-400},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1703516.pdf},
abstract = {Advances in digital twin technology have significantly enhanced the monitoring and optimization of energy supply chain operations. A digital twin is a virtual replica of physical assets, systems, or processes that allows real-time monitoring, simulation, and analysis to improve operational efficiency. In the energy sector, the implementation of digital twins provides a powerful tool to simulate the entire supply chain, from energy generation to distribution and consumption, enabling better decision-making, predictive maintenance, and optimization of resources. This paper explores the role of digital twin technology in the energy sector, focusing on its application for monitoring energy supply chain operations. By leveraging real-time data from sensors, IoT devices, and advanced analytics, digital twins enable energy companies to create accurate models of their infrastructure and processes. These models allow for continuous monitoring of critical systems, such as power plants, transmission lines, and distribution networks, identifying potential issues before they become critical, reducing downtime, and optimizing asset management. The integration of digital twin technology with other technologies like IoT and AI further enhances its capabilities. IoT sensors provide real-time data on equipment performance, energy consumption, and environmental conditions, which digital twins use to simulate and predict future scenarios. AI algorithms can then analyze these scenarios to optimize operations, reduce inefficiencies, and enhance resource allocation. Furthermore, digital twins facilitate collaboration between different stakeholders in the energy supply chain, providing a common platform for monitoring and decision-making. The paper also discusses the benefits of digital twin technology, including improved operational efficiency, reduced operational costs, better risk management, and enhanced sustainability. It highlights case studies from the energy sector where digital twins have been successfully implemented, demonstrating their impact on operational performance and the overall efficiency of energy supply chains.},
keywords = {Digital Twin, Energy Supply Chain, Real-Time Monitoring, Iot, Predictive Maintenance, Operational Efficiency, Asset Management, AI, Optimization, Sustainability},
month = {June},
}