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DOE OSTI2026

Poster: Responsible Adoption of Artificial Intelligence (AI) in Electric Grid Operations

The rapid integration of artificial intelligence (AI) in the utility transmission and distribution (T&D) sector is revolutionizing traditional grid management practices. As utilities encounter complexities from evolving consumer behaviors and energy integration, AI becomes a critical solution for enhancing grid monitoring, fault detection, and operational optimization. However, increased reliance on interconnected technologies introduces significant cybersecurity risks, regulatory compliance challenges, and human factors concerns. This study proposes a strategic, responsible and consequence-driven approach to AI implementation, examining the dual nature of AI adoption by highlighting its transformative benefits for utilities and associated risks. It provides utilities with a framework for evaluating AI integration, enabling them to navigate challenges and capitalize on opportunities to achieve greater reliability, efficiency, and resilience in an increasingly complex energy landscape.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

Addressing Rising Energy Demand Through Innovation

The U.S. is facing a significant increase in energy demand, driven by AI advancements, the rapid expansion of data centers, manufacturing and industrial growth, and the electrification of transportation and buildings. Buildings alone account for approximately 75% of U.S. electricity consumption and 40% of total energy use. To address these challenges, NLR leverages its state-of-the-art research facilities, advanced energy modeling, hardware-in-the-loop emulation, and real-world demonstrations to provide data-driven insights that de-risk emerging energy solutions, increase efficiency and demand flexibility, optimize grid controls, and identify vulnerabilities to enhance energy security. This presentation will highlight our research ecosystem and its role in supporting a more reliable, affordable, and adaptive energy infrastructure in the face of accelerating demand.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Advanced Transmission Technologies – GETs and HPCs Session 1: ATT Foundations and Dynamic Line Ratings (DLRs)

The INL TADA GETs Cohort Session 1, held on November 4, 2025, convened experts to address the integration of advanced transmission technologies, including Grid-Enhancing Technologies (GETs) and High Performance Conductors (HPCs), with a focus on digital assurance challenges. The session highlighted the growing importance of cybersecurity, supply chain transparency, reliability, and business risk management in deploying GETs, especially Dynamic Line Ratings (DLRs). Participants examined how expanded attack surfaces, limited vendor pools, and new regulatory requirements—such as FERC Orders 881, 2023, and 1920—are influencing utilities and technology providers. The workshop underscored the need for cyber-informed engineering, secure-by-design principles, and practical risk management strategies, while fostering collaboration and knowledge sharing among industry peers. Technical discussions covered the evolution from static to dynamic line ratings, complexities of cloud-based architectures, and NERC CIP compliance challenges. The session concluded with a collaborative risk exercise and a preview of future workshops on advanced power flow control and transmission topology optimization, reinforcing the cohort’s commitment to advancing digital assurance in the energy sector.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Cyber100 Compass: Quantification of Cybersecurity Risks for Systems Transitioning to High Levels of Renewables (Final Report)

The shift to high levels of renewable deployment will entail a significant re-engineering of the grid. As investors, utilities, customers, and others prepare for clean energy transitions, there is need to understand how restructuring the grid to accommodate renewables will change the attack surface of the grid and accompanying cyber risk. However, today the cyber-physical risks associated with electric grids incorporating high levels of renewable deployment remain largely unknown. The Cyber100 Compass proof-of-concept application attempts to quantify future cyber-physical security risks by combining risk data gathered from subject matter experts (SMEs) with input from system planners about conditions they expect to be true about their electric systems in the future. Users provide data about their organization’s tolerance for risk; the value they place on avoiding the consequences of different cyber events; and conditions that they expect to be true on their systems at some point in the future. The SMEs provide baseline probabilities for different cyber events; the probability that an event will be low-, moderate-, or high-impact; and the amount by which user-identified conditions on their systems will change the likelihood of the cyber events. The application takes both the user and SME input and performs a series of Monte Carlo simulations to arrive at a quantification of risk.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Anomaly Detection and Mitigation for Dynamic Frequency Regulation in Hydropower-Battery Systems

Hydropower operators and energy storage providers are increasingly interested in participating in frequency regulation services, driven by the incentives offered by independent system operators, such as the PJM Interconnection. This transition, however, unfolds against the backdrop of a modernizing and rapidly digitizing power grid, exposing the integrated legacy infrastructure to a multitude of cybersecurity threats. This work presents an approach for developing an anomaly detection and mitigation system to address cybersecurity challenges during the participation of a hydropower-integrated battery energy storage system (BESS) in a frequency regulation market. The applied anomaly detector utilizes machine learning algorithms to provide detailed classification of cyber-physical events. Later, the applied mitigation system triggers predefined corrective actions to minimize the impact of data integrity attacks on the regulation market and system stability. We evaluated the proposed approach on a hydropower-integrated BESS topology, specifically analyzing the slow regulation signal (Reg A) coming from the PJM market. Our simulation results demonstrate that the proposed approach performs well in detecting data integrity attacks within the allocated time frame and also minimizes the system's transient instability during the participation of hydropower and BESS in the regulation market.

battery energy storage system↗

DOE OSTI2025

Progress on the MARVEL Cybersecurity by Design Model-Based Systems Engineering Project

Formal model-based systems engineering (MBSE) combines a model, systems thinking, and systems engineering to visually depict the boundaries, context, and behavior of interconnected systems, facilitating effective design, development, and utilization of engineered systems throughout the systems engineering lifecycle. Although nuclear reactor vendors employ these tools to integrate functionality, performance, and safety, they are not yet addressing digital risk concerns introduced by use of operational technology, such as digital instrumentation and control systems. To accomplish this objective, the Microreactor Applications Research Validation and EvaLuation (MARVEL) microreactor was used as an MBSE case study. This real-world application provides a first-of-a-kind opportunity to demonstrate the benefits of integrating digital risk and cybersecurity into the MBSE design process of a nuclear reactor. This paper provides an update of the ongoing MARVEL Cyber MBSE project as it specifically relates to the integration of digital risk management and cybersecurity by design.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Cybersecurity Considerations for Hydrogen Infrastructure in Airport Environments

This report explores key cybersecurity concerns and best practices within environments that serve as reference points for the development of hydrogen fueling infrastructure for aviation. This cybersecurity analysis leverages prior NREL studies: 1) hydrogen fueling station component validation to identify vulnerabilities and failure events documented in physical equipment, and 2) electric aircraft charging infrastructure analysis to explore primary cybersecurity vulnerabilities. It reviews the criticality of digitized technologies in sustaining hydrogen fuel production, storage, and fueling systems, noting cybersecurity concerns that are universal to power systems and industrial control systems in general. In considering cybersecurity vulnerabilities within a future landscape of hydrogen energy for aviation applications, a reference architecture was intended to reveal the points of connection between assets and the potential sensors that are vulnerable to manipulation in the event of compromised access or communication within a SCADA system. A generalized reference architecture can help stakeholders, engineers, or strategists understand connections, criticalities, and standard practices when it comes to designing and planning for new systems. There are several gaps to account for in assessing the future of hydrogen production, storage, and fueling for aviation. Engaging stakeholders, including aircraft manufacturers, electric utilities, site property owners, and local communities, will inform decision-making around site structure, operations, and resources for future hydrogen fueling infrastructure to understand operational needs and cybersecurity awareness. Cybersecurity mitigation strategy must consider physical attack vectors that emerge with the integration of hydrogen systems into existing airport security requirements. The cybersecurity risk assessment contained in this report is an entry point into potential future granular-level analyses to be conducted as part of hazard and risk assessments for safe aviation hydrogen infrastructure, determining how the scale of hydrogen fuel infrastructure for aviation impacts the volume of cyber attack vectors, and what, if any, are the vulnerabilities associated with different types of on-board hydrogen systems. In this nascent development phase, assessing how best to integrate cybersecurity practices into an evolving U.S. aviation landscape provides critical insights into building increased awareness and stakeholder engagement to support a cyber-resilient infrastructure.

08 HYDROGEN↗

DOE OSTI2025

Natural Hazard Forecast Alert Grid Risk System

Weather events cause most power outages. Often, we even get notifications on our phones to take cover or be prepared for an imminent event. If electric grid utilities had a similar warning that also included probable scenarios and the equipment involved, they could prepare and minimize the effects. Idaho National Laboratory had a project with the U.S. Department of Energy’s Cybersecurity, Energy Security, and Emergency Response program to develop a grid alert application that receives messages from the existing emergency alert system, filters and determines components possibly affected by the emergency event, calculates probable scenarios using MASTERRI (Modeling And Simulation for Targeted Reliability and Resilience Improvement). For high-risk events, the application can then send alert links to subscribed electric distribution utility operations staff to allow them to see and evaluate the scenarios and the impact in a web based interactive map tool. This proof of concept application used data from utilities and organizations, such as the international regulatory body North American Electric Reliability Corporation, which have complied historical failure data of elements that comprise the U.S. electric grid. Nominal failure rates are obtained from this data. To make this tool possible, estimated failure rates were calculated for different component types given the alert type, severity, and location. Historic weather-related grid element failures were correlated with historic weather events from the Integrated Public Alert & Warning System. These correlated events and failures are used along with Bayesian updates from the historical norms to provide a modified failure rate for grid elements in the alert areas and calculate probable scenarios. Working with an industry collaborator, actual grid models and data were used for demonstration cases. This report outlines the work performed for this project.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Cybersecurity Considerations and Research Pathways for Grid-Interactive Efficient Buildings

Federal facilities serve critical missions and functions that require safe, reliable, and efficient operations. Digitization of several facility operations has increased the cost-effectiveness of energy usage and optimization of energy system performance. As the building controls landscape shifts to become more connected and smarter, building operators now face unique opportunities and challenges to adopt smart enabled devices that can lower energy usage while also optimizing building system performance. The grid-interactive efficient buildings (GEB) initiative aims to make buildings cleaner and more flexible through these smart devices. Smart enabled devices allow greater connectivity and control through remote operations and provide crucial data for analytics and increased efficiency. GEBs enable demand flexibility that has the potential to reduce electrical costs and transform the grid edge where buildings connect to power grids. This operation of interconnected systems, if not designed with cybersecurity practices, causes security gaps and introduces potential attack paths by adversarial and non-adversarial entities leading to disruption of operations.

building controls↗

DOE OSTI2025

Demonstration of Utility Managed Smart Charging for Multiple Benefit Streams (Final Report)

In the summer of 2020, the U.S. Department of Energy (DOE) awarded funding to Exelon’s Maryland utilities—Baltimore Gas and Electric (BGE), Delmarva Power & Light (DPL), and Potomac Electric Power Company (Pepco)—to implement the Smart Charge Management (SCM) pilot. This initiative aimed to design and implement managed electric vehicle (EV) charging strategies, evaluate the grid impacts of EV charging, and assess the utilities' ability to control EV load based on real-time grid conditions. The SCM pilot explored four aspects for continued improvement: (1) cybersecurity and managed charging functionality testing of two vendor platforms—WeaveGrid (telematics-based) and Shell Recharge Solutions (network-based)—which pursued charge scheduling and optimization through distinct approaches; (2) an analysis by Argonne National Laboratory (ANL) modeling team of three potential SCM enrollment scenarios within BGE and Pepco service territories over the next decade to assess future scalability; (3) employing customer engagement strategies, including surveys and a responsive pricing approach; and (4) the launch and implementation of pilots in Exelon’s Maryland territories in collaboration with WeaveGrid.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Correlation Between Weather Alerts and Grid Component Failures for Grid Alert

Weather events cause most grid failures. Often, we even get notifications on our phones to take cover or be prepared for an imminent event. If electric grid utilities had a similar warning that also included probable scenarios and the equipment involved, they could prepare and minimize the effects. Recent research at Idaho National Laboratory into electric grid risk analysis methods resulted in a tool that allows for the development of the most likely scenarios given failure probabilities of grid components. INL has a project with the U.S. Department of Energy’s Cybersecurity, Energy Security, and Emergency Response (CESER) program to develop a Grid Alert application that receives messages from the existing emergency alert system, filters and determines components possibly affected by the emergency event, calculates probable scenarios uses MASTERRI and then notifies the utility if there is significant risk. Historical failure data of elements that comprise the U.S. electric grid have been compiled by utilities and organizations such as the international regulatory body North American Electric Reliability Corporation (NERC). Nominal failure rates are obtained from this data. To make this tool possible, estimated failure rates are needed for different component types given the alert type, severity, and location. Historic weather-related grid element failures are correlated with historic weather events from Integrated Public Alert & Warning System (IPAWS). These correlated events and failures are used along with Bayesian updates from the historical norms to provide a modified failure rate for grid elements in the alert areas and calculate probable scenarios. This discusses the Grid Alert project plan but focuses on the data gathered and process used in determining failure rates for possible grid failure scenarios.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Grid Communications: Digital Assurance and Supply Chain Challenges and Emerging Regulation Session Two

The TADA Grid Communications Workshops are designed to strengthen cybersecurity and digital assurance across the energy sector by focusing on secure deployment and management of grid communications technologies. These workshops bring together state energy offices, utilities, and technology suppliers to explore the intersection of communications infrastructure, supply chain risks, and emerging regulatory requirements. Participants will apply Cyber-Informed Engineering (CIE) principles to reduce risks in communications systems, engage with INL’s procurement guidance, and explore future tools. Through scenario-based exercises and peer exchange, attendees will develop risk-based security strategies and actionable compliance roadmaps tailored to their grid communications projects. The workshops also help participants navigate evolving regulatory frameworks such as FEOC rules in the OBBB, NERC CIP-013, and NDAA 2024, while identifying compliance gaps in mixed-technology environments. A key outcome is the formation of a practitioner network with ongoing access to INL expertise and resources, fostering long-term resilience in the digital energy ecosystem. This is Session 2 of 3 (Full Version).

29 - ENERGY PLANNING, POLICY AND ECONOMY↗

DOE OSTI2025

Grid Communications: Cybersecurity and Supply Chain Challenges and Emerging Regulation Session Three

29 - ENERGY PLANNING, POLICY AND ECONOMY↗

DOE OSTI2025

Grid Communications Supply Chain & Emerging Regulation Challenges Session 1

29 - ENERGY PLANNING, POLICY AND ECONOMY↗

DOE OSTI2024

ByzSec — A Multi-layered Byzantine Resilient Architecture for Bulk Power System Protective Relays

Reliability, selectivity, and sensitivity are the fundamental attributes of any protection system, acting as the main drivers in the selection of schemes, and equipment. In high-voltage systems, microprocessor-based relays represent the industry’s preferred solution, providing engineers with a vast array of benefits. However, they remain vulnerable to cybersecurity events that may compromise their functionality. To help mitigate against potential cybersecurity risks, this paper presents a fault-tolerant, Byzantine Resilient (BR) architecture that significantly increases the cybersecurity attributes of a protection system while minimizing the amount of performance impacts and integration overheads introduced. The solution relies on an array of independent relays that utilize robust consensus methods (based on Spire [1], [2]) to ensure correct system behavior is achieved even when a relay has been compromised. Furthermore, the solution has been complemented with a custom-built Situational Awareness engine that can be used to detect and identify potential threats. The implemented solution has been developed in consultation with three hardware vendors and has been tested to comply with the performance requirements of a 345kV differential protection scheme (87T). The results indicate that the proposed architecture is a comprehensive solution that: supports the strict correctness and performance requirements of the bulk power grid while providing a cost-effective alternative that offers a seamless, long-term solution.

byzantine security, Fault Tolerant Application Sof↗

DOE OSTI2025

Dynamic probabilistic risk assessment and game theory for cyber security risk analysis in nuclear power plants

Nuclear Power Plants and energy systems have become more prone to cyber-attacks with their digitalization and the increased use of smart equipment. Hence, it is important to quantify the risk associated with cyber-attacks in such systems. Dynamic Probabilistic Risk Assessment which involves studying the evolution of a system due to random events and operator and attacker actions during a cyber-attack by employing a physics-based model of the system is a suitable framework to quantify cybersecurity risk in nuclear power plants. In addition to the plant dynamics, it is also important to model the strategies of the attackers and plant operators for an effective cybersecurity risk assessment. Game theory provides a set of necessary tools to model such strategic interactions. In this research, a framework that integrates dynamic probabilistic risk assessment with game theory for cybersecurity risk analysis in nuclear power plants is presented. The mathematical formulation is derived based on the theory of continuous event trees. We propose a game theory based action model, that utilizes physics-based rewards to define the strategies of attackers and operators at every decision epoch. As a case study, the risk associated with cyber-attacks on the digital components in the secondary side of a pressurized water reactor is studied using a reduced order model. A set of attacker actions and a set of operator actions are defined for the system. The operator and attacker interactions were modelled using simultaneous game, their action policies were computed using the concept of mixed strategy Nash equilibrium and the evolution of the system was studied.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

ARCADE Analysis Methods & Validation Pathway

The Advanced Reactor Cyber Analysis and Development Environment (ARCADE) provides an automated analysis system which supports risk-informed performance based (RIPB) evaluations of nuclear control systems. Every possible cyber threat which could lead to consequence is identified by simulating the unsafe control action sequences which transform digital harm into physical harm. Eliminating the simulation of complex digital cyber attack chains cuts out unnecessary computational overhead and focuses directly on the physics of cyber-physical attacks. This focus enables designers to make informed decisions which can entirely eliminate categories of cyber threats against advanced reactors through the physical nature of the plant design. This narrowing of cyber threat against nuclear power plants through the physics of the system is intended to make any remaining threat management and cost efficient. This is the goal of the Tiered Cyber Analysis (TCA) outlined in NRC Draft Regulation Guide (RG) 5.96, which provides a RIPB cybersecurity approach for new reactors. ARCADE has been custom developed to meet the demands of the rigorous analysis required in Tier 1 of the TCA, which forms the foundation of the TCA process. Currently, ARCADE is still under development, but has made significant leaps in capability. A pilot analysis on the opensource Asherah simulator was performed which demonstrated key functionality goals. The next stage of ARCADE development involves improvements to the applications which support the analysis system, and enabling the analysis system to utilize the full suite of unsafe control action simulations. Since the analysis method’s core functions are complete, validation of the analysis method will be started concurrent to the next development stages. The automated analysis ARCADE will provide can radically change the cybersecurity design process for advanced reactors, reducing the cost of security implementation while enhancing cyber resilience. The pathway for ARCADE’s development to this goal has become much clearer. The majority of technical hurdles have been cleared, and the remaining development needs have been solidified. ARCADE is now capable of assisting the advanced reactor design process and directly support advanced reactor industry RIPB practices.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2026

Designing resilient IoT and Edge Computing with federated tinyML

The rapid growth of the Internet of Things (IoT) and Edge Computing (EC) has brought significant conveniences to modern society but has also greatly expanded the cyber attack surfaces, particularly as these technologies are being increasingly integrated into critical systems such as power grids, healthcare, and smart homes. Here, to improve IoT/EC’s cybersecurity posture, we leveraged Artificial Intelligence (AI) and Machine Learning (ML) by employing tinyML to monitor voluminous IoT data for cyber threats while addressing devices’ resource constraints, and utilizing Federated Learning (FL) to share local detection knowledge across the system while preserving privacy. Building on our three-layer architecture combining tinyML and FL to enhance autonomous cyber attack detection, this paper demonstrated that the architecture improves detection accuracy, reduces resource consumption, and enables lightweight, secure IoT device monitoring. These results were validated using the public N-BaIoT dataset as well as real IoT network traffic data collected under multiple attack scenarios from our testbeds. Additionally, we introduced an enhanced FL methodology with a novel preprocessing stage, including federated feature selection and global preprocessor construction, to address IoT/EC data heterogeneity. We developed a physical IoT testbed for attack simulations and data collection, implemented a tinyML-powered detector for realistic model validation, and also built a virtual testbed for scalable evaluations of FL models across diverse network environments.

Cognitive cyber↗