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Improving the trust in results of numerical simulations and scientific data analytics

This white paper investigates several key aspects of the trust that a user can give to the results of numerical simulations and scientific data analytics. In this document, the notion of trust is related to the integrity of numerical simulations and data analytics applications. This white paper complements the DOE ASCR report on Cybersecurity for Scientific Computing Integrity by (1) exploring the sources of trust loss; (2) reviewing the definitions of trust in several areas; (3) providing numerous cases of result alteration, some of them leading to catastrophic failures; (4) examining the current notion of trust in numerical simulation and scientific data analytics; (5) providing a gap analysis; and (6) suggesting two important research directions and their respective research topics. To simplify the presentation without loss of generality, we consider that trust in results can be lost (or the results’ integrity impaired) because of any form of corruption happening during the execution of the numerical simulation or the data analytics application. In general, the sources of such corruption are threefold: errors, bugs, and attacks. Current applications are already using techniques to deal with different types of corruption. However, not all potential corruptions are covered by these techniques. We firmly believe that the current level of trust that a user has in the results is at least partially founded on ignorance of this issue or the hope that no undetected corruptions will occur during the execution. This white paper explores the notion of trust and suggests recommendations for developing a more scientifically grounded notion of trust in numerical simulation and scientific data analytics. We first formulate the problem and show that it goes beyond previous questions regarding the quality of results such as V&V, uncertainly quantification, and data assimilation. We then explore the complexity of this difficult problem, and we sketch complementary general approaches to address it. This paper does not focus on the trust that the execution will actually complete. The product of simulation or of data analytic executions is the final element of a potentially long chain of transformations, where each stage has the potential to introduce harmful corruptions. These corruptions may produce results that deviate from the user-expected accuracy without notifying the user of this deviation. There are many potential sources of corruption before and during the execution; consequently, in this white paper we do not focus on the protection of the end result after the execution.

97 MATHEMATICS AND COMPUTING↗

Cybersecurity Platform and Certification Framework Development for Extreme Fast Charging (XFC)-Integrated Charging Ecosystem (Final Project Report)

This report summarizes a pioneering effort in Electric Vehicle charging infrastructure ecosystem cybersecurity requirements, assessment methodologies, functional verification, as well as embodiment of the key technologies in the form of hardware and software tools being made available to the public. EPRI led a team of experts, as well as a stakeholder coalition encompassing all key actors in the EV charging infrastructure ecosystem that includes eXtreme Fast Charging (XFC) equipment (defined as 200kW or above). EV charging infrastructure in the United States is a patchwork of networks that have continued to grow organically and have been designed to serve the charging needs of the EV owners, who are their customers. In doing so, each network provider, as well as their connected entities such as the cloud Electric Vehicle Service Providers or EVSPs, utility back office, utility AMI networks, payment networks, as well as Original Equipment Manufacturer (EV manufacturer) telematics networks, have designed systems that may work well individually, but no single entity is responsible for the entire ecosystem to be secure in terms of data exchange. Furthermore, there is no uniformity in how each actor has implemented the cybersecurity requirements since no system-wide cybersecurity requirements existed prior to this project. The final project report describes the technical approach guided by the EV charging infrastructure cybersecurity working group, convened specifically for this project. The technical approach included definition of requirements at the ecosystem level, treated as a ‘system of systems’, and then passed down to individual systems (EVSE, EV, cloud EVSP, utility, and the payment networks), followed by developing the cybersecurity risk and vulnerability assessment methods, that were later applied to real-world cyber-physical systems at EPRI, ANL, and NREL laboratories, to validate both the process and the results. Finally, in a spotlight over the most vulnerable equipment, which is the EV charge station (AC or DC), the team developed a multi-layer cybersecurity implementation in the embedded domain embodied by the open-source Secure Network Interface Card (SNIC) demonstrating the various ways in which the infrastructure can be secured protecting against the identified attack surfaces. Finally, the entire process of EV infrastructure cybersecurity assessment was encapsulated in the Electric Vehicle Charging Cybersecurity Management (EVC2M) online GUI-based tool, that is expected to be released to the public. The report presents the objectives, the technical approach, the key results, and recommendations for future work.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Creating an Energy Intelligent Campus: Data Integration Challenges and Solutions at a Large Research Campus

Rich, well-organized building performance and energy consumption data enable a host of analytic capabilities for building owners and operators, from basic energy benchmarking to detailed fault detection and system optimization. Unfortunately, data integration for building control systems is challenging and costly in any setting. Large portfolios of buildings--campuses, cities, and corporate portfolios--experience these integration challenges most acutely. These large portfolios often have a wide array of control systems, including multiple vendors and nonstandard communication protocols. They typically have complex information technology (IT) networks and cybersecurity requirements and may integrate distributed energy resources into their infrastructure. Although the challenges are significant, the integration of control system data has the potential to provide proportionally greater value for these organizations through portfolio-scale analytics, comprehensive demand management, and asset performance visibility. As a large research campus, the National Renewable Energy Laboratory (NREL) experiences significant data integration challenges. To meet them, NREL has developed an architecture for effective data collection, integration, and analysis, providing a comprehensive view of data integration based on functional layers. The architecture is being evaluated on the NREL campus through deployment of three pilot implementations.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Evaluation of IEC 62443 Standard Gaps for Electric Grid Substation Model Use Case

This report presents an evaluation of the IEC 62443 standards in the context of electric grid substations, as part of a collaborative effort among Sandia National Laboratories (SNL), Idaho National Laboratory (INL), and the National Renewable Energy Laboratory (NREL). The primary objective is to assess the applicability of these standards to enhance cybersecurity measures for industrial automation and control systems (IACS) within the energy sector. The evaluation identifies strengths, such as the scalability of security levels and the structured lifecycle guidance provided by IEC 62443. However, it also highlights significant gaps, including limited integration of physical security, insufficient guidance for legacy systems, and challenges in addressing emerging threats like supply chain vulnerabilities. Recommendations for refining the standards are proposed, including the need for tailored guidance for securing legacy systems, integrating physical security with cybersecurity frameworks, and enhancing interoperability across multi-vendor environments. By addressing these gaps, the IEC 62443 standards can be strengthened to ensure comprehensive cybersecurity for electric grid substations, thereby supporting the resilience and reliability of critical energy infrastructure.

24 POWER TRANSMISSION AND DISTRIBUTION↗

2021 Annual Report Laboratory Directed Research & Development

The Department of Energy’s (DOE) Laboratory Directed Research and Development (LDRD) program is an essential pathway for innovation, capability growth, and research staff development at Idaho National Laboratory (INL). This program enables timely and agile response to national security, energy, and environmental challenges that motivate INL’s mission to discover and demonstrate innovative nuclear energy solutions and other clean energy options as well as securing our critical infrastructure. This report highlights INL’s LDRD projects concluding in fiscal year (FY) 2021 which included innovative research and development (R&D) across INL’s five science and technology initiatives: nuclear reactor sustainment and expanded deployment, integrated fuel cycle solutions, integrated energy systems, advanced design and manufacturing for extreme environments, and secure and resilient cyber-physical systems.

99 GENERAL AND MISCELLANEOUS↗

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↗

Thermal Energy Delivery System Design Basis Report

Nuclear power plants operate most efficiently and economically when they are operating at some constant power output. However, with the current dynamics of the grid, including the introduction and growth of renewable energy sources such as wind and solar, nuclear generation facilities across the U.S. are finding it difficult to keep their power supply constant and provide for baseload generation capacities. As a result, most nuclear plants are finding it hard to compete with other generation fuel sources, most notably, natural gas. Finding a solution to this intermittent power supply dynamic could help U.S. nuclear power plants economically compete with other generation fuel sources such as natural gas, wind, and solar. The Thermal Energy Delivery System (TEDS) at the INL aims to investigate alternative solutions to this dilemma. The TEDS design focuses on the delivery of thermal energy to different systems throughout the Dynamic Energy Transport and Integration laboratory (DETAIL). Its strategy revolves around allowing the system to operate at full generation output while storing any surplus energy for later use and/or additional function.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Security Architecture for Microgrid Integration

The purpose of this document is to present cyber security risk considerations and mitigations for community microgrids. The mitigations discussed herein specifically focus on cyber security technical requirements for the De-centralized Autonomous Community Controller (DAC) as part of the SECURE project’s technology development effort. These requirements also consider the associated security implementation challenges involved with the decentralized characteristics of microgrids where upstream communications to utility security management functions are lost. These security recommendations and technical requirements may be used by microgrid implementers and technology vendors to specify the security design of the microgrid systems and their components.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Trade-off Analysis of Operational Technologies to Advance Cyber Resilience through Automated and Autonomous Response to Threats

The advancement of cyber resilience requires a preliminary stage of characterizing the trade-off space of mitigation options and how these might affect the stability and determinism of an operational technology (OT). This first step will set the stage for the proper cyber-secure and cyber-resilient design and confirm the affects that can be considered and approved by the OT and the security groups. To provide a baseline for this discussion, this paper provides a consideration of the cyberphysical interactions, possible mitigation steps against certain attacks and their corresponding affects that lend to the security design planning and evaluation process. As an integral part of the proposed scheme this work introduces the concept of systemwide fuzzer, i.e., a tool that manipulates the system state in an effort to determine mitigation response sequences that minimize detriments and maximize benefit in accordance with specified operational requirements.

97 MATHEMATICS AND COMPUTING↗

Laboratory-Directed Research and Development 2016 Summary Annual Report

The Laboratory-Directed Research and Development (LDRD) Program at Idaho National Laboratory (INL) reports its status to the U.S. Department of Energy (DOE) by March of each year. The program operates under the authority of DOE Order 413.2C, “Laboratory Directed Research and Development” (April 19, 2006), which establishes DOE’s requirements for the program while providing the laboratory director broad flexibility for program implementation. LDRD funds are obtained through a charge to all INL programs. This report includes summaries of all INL LDRD research activities supported during Fiscal Year (FY) 2016. INL is the lead laboratory for the DOE Office of Nuclear Energy (DOE-NE). The INL mission is to discover, demonstrate, and secure innovative nuclear energy solutions, other clean energy options, and critical infrastructure with a vision to change the world’s energy future and secure our critical infrastructure. Operating since 1949, INL is the nation’s leading research, development, and demonstration center for nuclear energy, including nuclear nonproliferation and physical and cyber-based protection of energy systems and critical infrastructure, as well as integrated energy systems research, development, demonstration, and deployment. INL has been managed and operated by Battelle Energy Alliance, LLC (a wholly owned company of Battelle) for DOE since 2005. Battelle Energy Alliance, LLC, is a partnership between Battelle, BWX Technologies, Inc., AECOM, the Electric Power Research Institute, the National University Consortium (Massachusetts Institute of Technology, Ohio State University, North Carolina State University, University of New Mexico, and Oregon State University), and the Idaho university collaborators (i.e., University of Idaho, Idaho State University, and Boise State University). Since its creation, INL’s research and development (R&D) portfolio has broadened with targeted programs supporting national missions to advance nuclear energy, enable clean energy deployment, and secure and modernize critical infrastructure. INL’s research, development, and demonstration capabilities, its resources, and its unique geography enable integration of scientific discovery, innovation, engineering, operations, and controls into complex large-scale testbeds for discovery, innovation, and demonstration of transformational clean energy and security concepts. These attributes strengthen INL’s leadership as a demonstration laboratory. As a national resource, INL also applies its capabilities and skills to the specific needs of other federal agencies and customers through DOE’s Strategic Partnership Program.

99 GENERAL AND MISCELLANEOUS↗

A Functional All-Hazard Approach to Critical Infrastructure Dependency Analysis

The critical infrastructures protection landscape is a vast and varied pattern of independent, but interconnected infrastructure systems that are essential to the function of our modern society. The U.S. policy on critical infrastructure protection has been continually evolving since the “President’s Commission on Critical Infrastructure Protection” was published in 1997. In response to these policies, federal, state, and local governments, along with research institutions, have invested a substantial amount of time and effort into identifying and analyzing critical infrastructure, their functions, and dependencies/interdependencies to better understand their vulnerabilities. To date, the ability to assess vulnerabilities, resiliency, and priorities for protecting interdependent critical infrastructure systems from an all-hazards perspective remains a difficult problem. In this paper we introduce the All-Hazards Analysis (AHA) methodology, which provides an integrated functional basis across infrastructure systems, through the implementation of a common language and a scalable level of decomposition to effectively evaluate the resilience of interconnected infrastructure systems. AHA models infrastructure systems as directed multidimensional graphs, which enable the evaluation of cross-sector interdependencies prior to, during, and after disruptive events. Finally, and by design, AHA enables the cross linking of data taxonomies to enable more effective data sharing, such as the National Critical Functions (NCF) and Infrastructure Data Taxonomy (IDT).

02 PETROLEUM↗

Situational Awareness of Grid Anomalies (SAGA) for Visual Analytics—Near-Real-Time Cyber-Physical Resiliency Through Machine Learning

The Situational Awareness of Grid Anomalies (SAGA) project built upon foundational power system tools developed at the National Renewable Energy Laboratory (NREL) integrated with an ever-increasing set of Gridmetrics data extracted from the cable television (CATV) broadband network infrastructure while assimilating other time-series geospatial data and information, such as weather and cyber-physical phenomena, to demonstrate a disruptive technology for power system data analytics relying on existing infrastructure. Three research thrusts supported (1) visual analytics, (2) cyber-physical power system simulation, and (3) anomaly detection. SAGA created technology that leverages, couples, and fortifies two vastly different realms - power and broadband - to increase the resiliency of the power grid in the face of increasing cyberattacks and operational challenges related to integrating DERs. The exploration of potential synergies of broadband-enabled grids resulted in identifying a mutually beneficial symbiosis that can increase the resiliency of both power and broadband services. Broadband networks perform better with reliable power and are good at providing real-time measurements that identify where the grid is under attack, is failing, or is weak. Likewise, sensor-starved distribution grids perform better and can be more reliable when their operation is buttressed with observations of broadband-detected anomalies. Future research can explore broadband's contribution to continuing to improve grid resiliency, reliability, and cost-effective operation.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Distributed Optimization in Distribution Systems: Use Cases, Limitations, and Research Needs

We report electric distribution grid operations typically rely on both centralized optimization and local non-optimal control techniques. As an alternative, distribution system operational practices can consider distributed optimization techniques that leverage communications among various neighboring agents to achieve optimal operation. With the rapidly increasing integration of distributed energy resources (DERs), distributed optimization algorithms are growing in importance due to their potential advantages in scalability, flexibility, privacy, and robustness relative to centralized optimization. Implementation of distributed optimization offers multiple challenges and also opportunities. This paper provides a comprehensive review of the recent advancements in distributed optimization for electric distribution systems and classifications using key attributes. Problem formulations and distributed optimization algorithms are provided for example use cases, including volt/var control, market clearing process, loss minimization, and conservation voltage reduction. Finally, this paper also presents future research needs for the applicability of distributed optimization algorithms in the distribution system.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Cyber-Informed Engineering Case Study of an Integrated Hydrogen Generation Plant

Strategies for securing digital instrumentation and control (I&C) systems within the nuclear industry are provided by multiple standards and guidance documents. However, since selection and use of security controls outlined in these documents are frequently only considered during or after installation, there are often limitations on their use, such as technological constraints related to design or operation. Furthermore, alternative controls intended to provide the same or similar security countermeasure as the primary control may also be infeasible at these stages, leaving the I&C system vulnerable to cyber-attacks. The limitations associated with ‘bolting on’ security controls late in the systems engineering lifecycle can be reduced by integrating Cyber-Informed Engineering (CIE) into the process. This paper evaluates the use of CIE during the high-level design stage of a hydrogen generation project where heat and electricity are provided by a nuclear power plant. Applying CIE to this project highlighted potential cyber vulnerabilities of the initial design, leading to recommendations for process flow and I&C system design modifications to reduce, and at times eliminate, the risk from both deliberate and unintentional cyber incidents.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Overview and Recommendations for Cyber Risk Assessment in Nuclear Power Plants

Digital instrumentation and control (I&C) systems are being deployed in nuclear power plants (NPPs) for both existing and advanced reactor designs. As I&C systems become more digitized to allow features like near autonomous control and remote operation, they introduce greater cyber risk to NPPs. Cyberattacks targeting industrial control systems (ICSs) are growing in both qualities and capabilities, which indicates that cybersecurity needs to be an integral part of risk assessment in the industry. Although there are some risk assessment methods in traditional information technology (IT) cybersecurity, the differences between IT and ICS cybersecurity make it infeasible to apply these risk assessment methods directly to ICSs. Some research has focused on risk assessment methods for ICSs, but few studies focus on applications to NPPs. Ideal risk frameworks for the nuclear industry are dynamic and account for system dependencies; this survey review focuses on such risk assessment methods both in and outside the nuclear field. In this article, the major challenges in cybersecurity risk assessment research are pointed out, and further research suggestions and considerations for cyber risk assessment in I&C systems are identified.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

California Energy Systems for the 21st Century (CES-21) Annual Report - 2018

The California Energy Systems for the 21st Century (CES-21) Program is a public-private collaborative research and development (R&D) program between the California Joint Utilities1 and Lawrence Livermore National Laboratory (LLNL). The purpose of this annual report is to provide the California Public Utilities Commission (CPUC or Commission) with a summary of the 2018 progress of the CES-21 Program2. The CES-21 Program is designed to research solutions for the medium- and far-term challenges of a fastevolving energy marketplace. The program is comprised of two projects: Cybersecurity Project and Grid Integration - Flexibility Metrics Project. This report provides information on the operations of the CES-21 program, including projects funded, results of research, efforts made to involve third parties, and intellectual property that results from the research.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Using Semantic Web Technologies to Develop Intrinsically Resilient Energy Control Systems

To preserve critical energy control functions while under attack, it is necessary to perform comprehensive analysis on root causes and impacts of cyber intrusions without sacrificing the availability of energy delivery. We propose to design an intrinsically resilient energy control system where we extensively utilize Semantic Web technologies, which play critical roles in knowledge representation and acquisition. While our ultimate goal is to ensure availability/resiliency of energy delivery functions and the capability to assess root causes and impacts of cyber intrusions, the focus of this paper is to demonstrate a proof of concept of how Semantic Web technologies can significantly contribute to resilient energy control systems.

cybersecurity↗

Connecting the Dots: An Assessment of Cyber-risks in Networked Building and Municipal Infrastructure Systems

The buildings and city streets we walk down are changing. Driven by various data-driven use cases, there is increased interest in networking and integrating lighting and other building systems (e.g., heating, ventilation, and air conditioning (HVAC), security, scheduling) that were previously not internet-facing, and equipping them with sensors that collect information about their environment and the people that inhabit it. These data-enabled systems can potentially deliver improved occupant and resident experiences and help meet the U.S. Department of Energy (DOE) national energy and carbon reduction goals. Deploying connected devices new to being networked, however, is not without its challenges. This paper explores tools available to system designers and integrators that facilitate a cybersecurity landscape assessment – or more specifically the identification of threats, vulnerabilities, and adversarial behaviors that could be used against these networked systems. These assessments can help stakeholders shift security prioritization proactively toward the beginning of the development process.

cyber-risk assesment, adversarial behavior, MITRE ↗