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Researchers at the Department of Energy’s Oak Ridge National Laboratory (ORNL) and their partner institutions have embarked on a project to create a cutting-edge suite of tools designed to enhance cybersecurity for the U.S. power grid. This initiative comes in response to the rapid evolution of the energy sector, characterised by the growing prevalence of distributed energy resource systems – ranging from solar panels and electric vehicles to demand response programmes—reshaping traditional grid operations.
The integration of these distributed systems introduces new cybersecurity challenges. Traditional power grid operations, reliant on centralised systems, are increasingly complemented by advanced information and communication technologies. While these technologies enhance connectivity and operational efficiency, they expose utility systems to broader cyber threats. To address these risks effectively, the research team is leveraging artificial intelligence (AI) to develop innovative tools capable of comprehensive cybersecurity analysis.
The new suite of tools, AI-PhyX, is designed to streamline data collection and analysis and address all aspects of cyber resilience. This includes vulnerability analysis, attack detection, threat mitigation, and system recovery. By converting raw data into actionable insights, AI-PhyX enables system operators to make more informed decisions, enhancing their ability to protect and maintain the integrity of the power grid.
Jamie Lian, the leader of ORNL’s Grid-Interactive Controls group, emphasises the importance of this initiative: “As we witness the proliferation of distributed energy resources across the grid, our focus lies in fortifying the cyber resilience of these systems. We aim to harness the power of AI to bolster cybersecurity measures and ensure secure and reliable operations.”
The development of AI-PhyX involves collaboration with several prominent partners, including the DOE’s National Renewable Energy Laboratory, the University of Connecticut, Pennsylvania State University, and Siemens Corp. Once developed, the tool suite will be demonstrated using system data provided by utility partners such as EPB of Chattanooga. This demonstration phase aims to ensure improved acceptance and integration by utility companies.
One of the key innovations of the AI-PhyX tool suite is its ability to integrate diverse cybersecurity applications into a single, unified platform. This approach addresses the challenge of fragmented data management, often leading to incomplete analysis and hindering effective deployment. By employing a common data pool and facilitating information sharing across platforms, AI-PhyX enhances functionality and reduces deployment barriers for machine learning technologies. This integration ensures that utilities can maximise the benefits of their AI investments.
“Employing a common platform with a unified data pool increases functionality and reduces the barriers for deploying machine learning technologies,” explains Lian. “This approach allows utilities to realise the full potential of AI in enhancing their cybersecurity measures.”
The promise of distributed energy systems is substantial, offering benefits such as improved grid reliability, lower electricity costs, and reduced greenhouse gas emissions. The AI-PhyX project aims to realise these benefits by providing a robust, AI-driven solution to cybersecurity challenges.
“Our work is focused on ensuring these benefits can be fully realised,” Lian adds. “By integrating cutting-edge AI methods with the development of an easy-to-deploy tool suite, we can guarantee the secure and reliable operation of distributed energy systems, paving the way to a sustainable energy future.”
The DOE Office of Cybersecurity, Energy Security, and Emergency Response funds the development of AI-PhyX. In addition to Jamie Lian, Teja Kuruganti co-leads the project, with ORNL researcher Yan Liu spearheading the software development efforts. This collaborative endeavour reflects a commitment to advancing cybersecurity in the energy sector and supporting the transition to a more resilient and sustainable energy grid.
