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
Citations
IRE Journals:
Ekene Cynthia Onukwulu , Ikiomoworio Nicholas Dienagha , Wags Numoipiri Digitemie , Peter Ifechukwude Egbumokei
"Advances in Digital Twin Technology for Monitoring Energy Supply Chain Operations" Iconic Research And Engineering Journals Volume 5 Issue 12 2022 Page 372-400
IEEE:
Ekene Cynthia Onukwulu , Ikiomoworio Nicholas Dienagha , Wags Numoipiri Digitemie , Peter Ifechukwude Egbumokei
"Advances in Digital Twin Technology for Monitoring Energy Supply Chain Operations" Iconic Research And Engineering Journals, 5(12)
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