“Big Data Analytics for Predicting Risk of Outages, and Managing and Mitigating Impacts using Distributed Energy Resources,” Keynote, IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies-GlobConHT-2023, Male, Maldives, March 2023

At the IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies (GlobConHT-2023) in the Maldives, a keynote presentation showcased how Big Data Analytics is revolutionizing the energy sector by predicting outage risks and optimizing the management of Distributed Energy Resources (DERs). By processing vast amounts of data and deploying machine learning models, this approach identifies vulnerabilities in energy grids, enabling proactive risk management and ensuring dynamic coordination of DERs. This results in enhanced grid reliability, optimized use of renewable resources, and cost savings for both utility providers and consumers. The solution also supports sustainability by reducing reliance on fossil fuels and improving energy access in underserved areas, demonstrating the transformative potential of data-driven strategies for a sustainable and resilient energy future