Data analytics for resilient and low-carbon energy supply chains: Strengthening energy security in the net-zero era

In the wake of escalating climate change concerns and growing geopolitical instability, the transformation of global energy supply chains into resilient, low-carbon systems has become imperative. The transition to net-zero energy frameworks demands a proactive integration of data analytics to enable real-time visibility, predictive decision-making, and emissions optimization across the energy value chain. This study explores the pivotal role of data analytics in strengthening energy security while advancing the decarbonization of supply chains. At a macro level, it evaluates how data-driven technologies ranging from AI-powered forecasting and digital twins to blockchain traceability support strategic planning for renewable energy integration, infrastructure resilience, and crisis response. The analysis then narrows its focus to operational aspects, including predictive maintenance of transmission systems, smart inventory management for critical energy components, and optimization of multimodal logistics to reduce carbon footprints. Special emphasis is placed on how big data platforms enable scenario modeling and stress-testing of supply routes under extreme weather and geopolitical tensions. Furthermore, the paper highlights the role of analytics in enhancing transparency and ESG compliance through life-cycle carbon tracking and automated reporting systems. By presenting case examples from solar, wind, and green hydrogen logistics, this study demonstrates how advanced data systems can align decarbonization objectives with supply reliability. The findings underscore that achieving net-zero goals without compromising energy access hinges on adaptive, data-enabled infrastructures that can anticipate, absorb, and respond to dynamic supply-demand challenges. The paper concludes with policy recommendations for scaling digital energy ecosystems across national and cross-border networks.