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DOE OSTI2023

A Secure and Adaptive Hierarchical Multi-Timescale Framework for Resilient Load Restoration Using a Community Microgrid

Distribution system integrated community microgrids (CMGs) can partake in restoring loads during extended duration outages. At such times, the CMGs are challenged with limited resource availability, absence of robust grid support, and heightened demand-supply uncertainty. Here, this paper proposes a secure and adaptive three-stage hierarchical multi-timescale framework for scheduling and real-time (RT) dispatch of CMGs with hybrid PV systems to address these challenges. The framework enables the CMG to dynamically expand its boundary to support the neighboring grid sections and is adaptive to the changing forecast error impacts. The first stage solves a stochastic extended duration scheduling (EDS) problem to obtain referral plans for optimal resource rationing. The intermediate near-real-time (NRT) scheduling stage updates the EDS schedule closer to the dispatch time using new obtained forecasts, followed by the RT dispatch stage. To make the decisions more secure and robust against forecast errors, a novel concept called delayed recourse is designed. The approach is evaluated via numerical simulations on a modified IEEE 123-bus system and validated using OpenDSS and hardware-in-loop simulations. The results show superior performance in maximizing load supply and continuous secure distribution network operation under different operating scenarios.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Optimal Operation for Resilient and Economic Modes in an Islanded Alaskan Grid

Legacy energy management systems for distribution system or microgrids are typically driven by economics. During extreme events, resiliency can be defined as ability of the system to keep supplying critical loads. Resilient operation during extreme events (e.g. avalanche in Alaska) may require decision variables to be different and conflicting with economic operation. Operational objectives are driven by a complex consideration of the economic, reliable and resilient operation of the system: economic and reliable in normal operating state and resilient during extreme events. Challenge is to move between economic and resilient operation in optimal manner and setting up problem formulation and constraints specially with Distributed Energy Resources (DERs). In this paper, we focus on striking a balance between optimal economic and resilient operation using novel formulation and developed tool called Resiliency Enabled Energy System Operation Toolbox (RE-ESOT). Simulation results are provided for a real islanded grid in Alaska with battery energy systems.

50 EE - Wind and Water Power Program - Water (EE-4↗

DOE OSTI2022

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↗

DOE OSTI2020

Planning for the storm: Considering renewable energy for critical infrastructure resilience

This study uses the renewable energy optimization model to assess three critical facilities in North Carolina. Techno-economic results were then compared to analyses completed for critical facilities in California and New York to assess energy system cost effectiveness. Though solar photovoltaic (PV) arrays are cost-effective across each of the three North Carolina facilities, adopting battery storage to enable PV to operate with existing diesel generators in a hybrid energy system reduces the economic value of the system. This is in contrast to more economically viable systems in California and New York. All of these systems also offer unquantified resilience benefits by extending operation from hours to weeks across the facilities. If decision makers were able to value the resilience benefits offered by each system or utility rate structures were changed to incentivize battery storage during normal operations, it would impact these assessments. Even so, this analysis provides decision makers a key set of cost benchmarks when considering how they might improve resilience at their critical operations.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2023

Idaho National Laboratory Energy Cybersecurity Programs Update

This brief presentation provides a status update on three Idaho National Laboratory energy cybersecurity programs of particular interest to NERC Reliability and Security Technical Committee annual in-person Security Groups summit. Public information on the following three programs is included: Cybersecurity for Operational Technology Environments (CyOTE™) program Cyber-Informed Engineering (CIE) Cyber Testing for Resilient Industrial Control Systems (CyTRICS) program, and associated high-level information on the Energy Software Bill of Materials POC, Executive Order 14017, and the Energy Cyber Sense Act

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Workflows Community Summit 2022: A Roadmap Revolution

Scientific workflows have become integral tools in broad scientific computing use cases. Science discovery is increasingly dependent on workflows to orchestrate large and complex scientific experiments that range from the execution of a cloud-based data preprocessing pipeline to multi-facility instrument-to-edge-to-HPC computational workflows. Given the changing landscape of scientific computing (often referred to as a computing continuum) and the evolving needs of emerging scientific applications, it is paramount that the development of novel scientific workflows and system functionalities seek to increase the efficiency, resilience, and pervasiveness of existing systems and applications. Specifically, the proliferation of machine learning/artificial intelligence (ML/AI) workflows, need for processing large-scale datasets produced by instruments at the edge, intensification of near real-time data processing, support for long-term experiment campaigns, and emergence of quantum computing as an adjunct to HPC, have significantly changed the functional and operational requirements of workflow systems. Workflow systems now need to, for example, support data streams from the edge-to-cloud-to-HPC, enable the management of many small-sized files, allow data reduction while ensuring high accuracy, orchestrate distributed services (workflows, instruments, data movement, provenance, publication, etc.) across computing and user facilities, among others. Further, to accelerate science, it is also necessary that these systems implement specifications/standards and APIs for seamless (horizontal and vertical) integration between systems and applications, as well as enable the publication of workflows and their associated products according to the FAIR principles.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

All Hazards Approach to Grid Modernization

Resilience hazards for electric power systems are on the rise, exacerbated by both a rise in extreme weather events and manmade physical and cyber attacks. At the same time, grid modernization challenges plague the United States, covering everything from increased electrification and ambitious renewable energy targets to aging infrastructure and regulation that lags behind today’s challenges. This talk will cover an all-hazards risk based approach that addresses both rising resilience and grid modernization challenges. Examples of this approach taken for national laboratory research projects will be discussed, including a deep dive into a project that addressed black start, resynchronization, distributed control, and cybersecurity challenges for an operational microgrid up to sub-transmission voltages. As takeaways from this project are translated from demonstration scale to real-world exercises, key lessons are noted on the translation from research into practice and how this can inform risk-based research moving forward

17 WIND ENERGY↗

DOE OSTI2023

Pillars of Innovation Across Southeast Idaho & the Interstate-15 Corridor

Since 1949, Idaho National Laboratory (INL) has been home to developing civilian and defense nuclear reactor technologies and managing spent nuclear fuel. Today, INL is the nation’s nuclear energy research laboratory, sustaining the safe and efficient operation of existing reactors, powering science in space, and breaking ground on the future fleet of advanced nuclear reactors. INL is only one of many rising technology resources in the region, however. Along the Interstate 15 (I-15) corridor, technology and cybersecurity industries and intellectual assets are rapidly expanding. Creating an innovation hub in this region would unite capabilities to solve current and future challenges in nuclear reactor sustainment and expanded deployment, integrated fuel cycle solutions, integrated energy systems, advanced materials and manufacturing for extreme environments, and secure and resilient cyber-physical systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2025

The Impact of Cultural Values and Organizational Processes on Nuclear Security Operations

Human performance is a pivotal factor in the design, testing, maintenance, and operation of security systems. The effectiveness of these systems relies not only on the capabilities, limitations, motives, and attitudes of the individuals involved, but also on the quality of training, instructional content, and evaluation methods provided. To uphold security standards, seamless integration between technologies and operators necessitates reliable human input. In security operations, human errors, often attributed to blame, sanctions, low motivation, individual accountability, or complacency, are primary causes of system failures. Complacency, characterized by a false sense of security, reflects a lack of awareness of potential threats and is a significant contributing factor to lapses in security. Security incidents arise from various factors, many extend beyond individual control, highlighting the need for a holistic approach to human performance that integrates organizational processes and team collaboration. Historically, errors have been attributed to individual moral or cognitive failures. However, insights from Operational Experiences (OEs) suggest that organizational processes weakness and deficiencies in nuclear cultural values contribute more significantly to security failures than individual mistakes. This paper consolidates lessons learned from diverse international nuclear security cultures and aims to highlight the importance of security culture in shaping global perspectives on nuclear security. It underscores the role of cultural values in shaping nuclear security practices and enhancing the resilience of security systems in the nuclear sector.

Zineddin, Dr. Z. [ORNL] (ORCID:0009000848740725)↗

DOE OSTI2024

Coupling of the Electricity and Transportation Sectors - Part II: Risk Assessment

This comprehensive report explores the intricate interplay through “sector coupling” between the Transportation Sector, Energy Sector, and the critical infrastructure challenges faced by the United States. Aligned with the ambitious federal goal of reducing greenhouse gas emissions, the report analyzes the present vulnerabilities in the fossil fuel supply chain, highlighting instances where the dependence on this industry has been susceptible to local and global disruptions. With a focus on risk assessment, this report establishes a framework to compare the fossil fuel-based transportation sector with the burgeoning electrified sector, considering the evolving technologies in electric vehicles (EVs) and the nascent charging infrastructure. This study delves into the historical reliability of fossil fuel-based transportation and identifies opportunities for strengthening sector coupling between transportation and the electric sector. Assessments of the gasoline-diesel supply chain provide insights into both opportunities and threats, offering a roadmap for creating a more reliable and resilient electrified transportation system. We modeled sectoral coupling scenarios for the current internal combustion engine (ICE)-based and future EV-dominant landscapes, leveraging qualitative sector attributes to identify relative strengths and weaknesses in Part 1 of the report. In this report (Part 2) we continue to understand the role of the electricity sector on transportation and develop a semi-quantitative methodology is employed to evaluate and compare the risks associated with the fossil fueled and electric transportation sector during emergency scenarios, drawing from real-world events like hurricanes and geopolitical disruptions. Different operational scenarios for the fossil fuel and electrified sectors have been developed to understand the risks associated with them. This report concludes with recommendations for the architectural designs of electric charging infrastructure, underlining the need for informed decisions in the transition towards a sustainable and resilient transportation future.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Planning decentralized urban renewable energy systems using algal cultivation for closed-loop and resilient communities

To tackle climate challenges, communities need to harvest renewable energy and resources on site locally to close the loops for enhancing the resilience of communities facing unpredictable and uncertain future changes. A decentralization planning of urban renewable energy systems is proposed by treating urban waste streams and producing biomass through applying algal biotechnology. When applying algal technology as a renewable and decentralized energy source in urban systems, the overall performance can vary by levels of urban nutrients, solar and CO 2 resources, and the transportation cost when considering its application to different urban densities, urban form, and the spatial scale of urban settings. This research explores three potential impacts on the algal system’s energy performance: (1) urban density, (2) urban form in different contexts, and (3) spatial scale. The research examines the impacts by testing urban settings given in actual contexts in Atlanta, Georgia, USA. Four neighborhoods representing the high-density urban, mid-density urban, mixed suburban, and typical suburban areas are investigated. The density-scale–performance relationships are explored through testing different urban forms of neighborhoods in both hypothetical and actual neighborhood settings. A GIS-based model is developed to estimate the overall energy performance of the decentralized renewable energy system in urban environments. Results show that the energy performance is positive mainly for high-density urban neighborhoods with small-to-medium scales, up to 0.36 MJ per ton of municipal solid wastes for actual settings and 0.37 MJ for hypothetical cases. Neighborhoods with higher density have higher energy performance while up scaling has negative effects on the energy performance with a low degree of significance. Optimal scales are found as a 1-km radius in real test beds and 1.3 km in hypothetical settings, in which the results show trade-offs between scaling effects in the system efficiency gain and the transportation cost increase.

Quan, Steven Jige↗

DOE OSTI2025

ARM-IRL: Adaptive Resilience Metric Quantification Using Inverse Reinforcement Learning

The resilience of safety-critical systems is gaining importance due to the rise in cyber and physical threats, especially within critical infrastructure. Traditional static resilience metrics may not capture dynamic system states, leading to inaccurate assessments and ineffective responses to cyber threats. This work aims to develop a data-driven, adaptive method for resilience metric learning. We propose a data-driven approach using inverse reinforcement learning (IRL) to learn a single, adaptive resilience metric. The method infers a reward function from expert control actions. Unlike previous approaches using static weights or fuzzy logic, this work applies adversarial inverse reinforcement learning (AIRL), training a generator and discriminator in parallel to learn the reward structure and derive an optimal policy. The proposed approach is evaluated on multiple scenarios: optimal communication network rerouting, power distribution network reconfiguration, and cyber–physical restoration of critical loads using the IEEE 123-bus system. The adaptive, learned resilience metric enables faster critical load restoration in comparison to conventional RL approaches.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Framework for Quantitative Evaluation of Resilience Solutions: An Approach to Determine the Value of Resilience for a Particular Site

The paper provides the approach to providing a benefit cost analysis of energy and water alternatives to provide resilience to extreme events. The approach estimates the costs and returns of providing greater resilience of water and energy infrastructure. Extreme events are defined as high impact, low-frequency events such as, but not limited to, hurricanes, floods, storm surges and earthquakes. The provides justification for hardening water and energy infrastructure. Resilience is defined as “the ability to prepare for and to withstand an extreme event with little or no damage, or to recover more quickly from an extreme event.” The approach can be summarized as follows. The approach requires the development of a baseline with which to compare alternatives. The baseline is used to evaluate the baseline’s resilience to hazards through the probability of the hazard(s), the likelihood of damage from that the hazard through a vulnerability analysis, and the consequence to calculate a cost of the damage. The approach then evaluates proposed mitigation alternatives that would improve the resilience of the system. Each alternative is evaluated based on probability of the hazard, probability of vulnerability and consequence to determine the reduced damage that each alternative presents. The approach includes any monetary and non-monetary benefits that can quantified for each of the alternatives. Non-quantifiable benefits are evaluated based on the relative importance of each alternative to the criteria used to determine how well the alternative meets the goals and objectives of the site/facility. Then, a life cycle cost analysis should be conducted for the baseline and alternatives. Finally, the results of the life cycle analysis should be presented in a decision matrix with cost, net present value, benefit/cost ratios, and any non-monetary criteria ranked to show how well the alternatives met the criteria, weighted with the decision maker’s weights and the results presented.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Redefining Net-Zero Water for Resilient Aquifers

Groundwater has long been a critical source of potable water, supplying one-third of all global water withdrawals and providing strategic reserves in times of drought (Konikow, 2012; Famiglietti, 2014). The risk in relying on groundwater is that it is often pumped at rates far greater than it can be naturally replenished. With increasing population and a changing climate, the depletion of potable water supplies has become an ever-growing concern (Srinivasan et al., 2012). Recently, the concept of “resilience” has been applied to groundwater, leaving many questions to be explored in terms of what resilience should mean for aquifers (Foster and MacDonald, 2014; Grönwall and Oduro-Kwarteng, 2017). The term is commonly used to indicate resilience to impacts of climate change specifically, but here we consider resilience in the context of more general water insecurity. Relatedly, the concept of “sustainable yield” has emerged in an attempt to determine a metric that can ensure the long-term resilience of groundwater systems, but the definition is fraught with inherent uncertainties and its quantification poses challenges (Rudestam and Langridge, 2014; Grönwall and Oduro-Kwarteng, 2017). At the heart of these concepts is a focus on sustainable management of aquifers. A sustainable approach to managing groundwater resources usually involves balancing long-term abstraction with the long-term recharge taking into account the needs for environmental flows and implementing drought-preparedness measures (Robins et al. 2006; Foster and MacDonald, 2014). At a high level, a sustainable balance of groundwater abstraction versus aquifer recharge may be considered “Net Zero” (NZ) or “Net Positive” (NP) in cases where recharge is equal to or in excess of abstraction, respectively. However, NZ/NP water management programs that address these concerns have varied definitions of compliance, which include considerations for the application at hand (ILFI, 2020; USGBC, 2020). Locations with high risk of low or poor water supply may be particularly interested in pursuing NZ/NP water. The AQUEDUCT Water Risk Atlas (World Resources Institute, 2019) indicates long-term availability, providing risk levels for quantity and quality of water at specific locations across the globe, for existing and predicted future conditions. This paper follows the U.S. Department of Energy (DOE) Federal Energy Management Program (FEMP) NZ water definition adopted by the U.S. Army for use at their installations, including Army Reserve Centers (ARCs). This definition also relates to the U.S. Army’s current focus on water resilience, which includes short-term and long-term availability of water resources.

net zero water, HUC12, Saipan, American Samoa, Mau↗

DOE OSTI2022

A Power Outage Data Informed Resilience Assessment Framework

Catastrophic impacts to power systems due to disruptive events have increased significantly during the last decade. These events highlight the need to develop approaches to assess the resilience of power systems against extreme events. However, the availability of data that capture power system performance during and after disruptive events is scarce. This paper proposes an assessment framework to evaluate the performance aspects of the grid system during extreme outage events using the Environment for Analysis of Geo-Located Energy Information (EAGLE-I) data. EAGLE-I includes information related to the number of impacted customers, duration, and location of power outages in the United States. Statistical analyses were conducted to extract resilient-based outage data and derive probability distribution functions of their impact and recovery characteristics. A list of extreme events is identified based on few predetermined threshold values. Metrics from other power outage assessments were used to measure the characteristics of each event, including impact rate and duration, recovery rate and duration, and impact level. A probability distribution function is obtained for each metric. The obtained results provide a representation of national grid performance during extreme events, which can be applied as a framework to evaluate various resilience enhancement techniques.

EAGLE-I↗

DOE OSTI2025

Understanding the Benefit of Hybrid Electrolytes towards Vanadium Dissolution Suppression and Improved Capacity Retention in Zinc‐Aqueous Batteries Using NaV 3 O 8 Cathodes

Vanadate cathodes used in aqueous Zn-ion batteries with ZnSO 4 are hindered by capacity loss from V dissolution into the electrolyte. However, studies pinpointing the onset of dissolution as a function of electrochemical redox state and quantifying the amount of associated active material are lacking. To prevent dissolution of the NaV 3 O 8 active material, Na + ions are introduced into the electrolyte. Specifically, a hybrid ZnSO 4 + Na 2 SO 4 electrolyte is investigated in concert with NaV 3 O 8 (NVO) cathodes of varied crystallinity to determine the resulting impacts on cathode dissolution and functional electrochemistry. The use of Na + -containing hybrid electrolyte shows no significant change in Zn 2+ diffusion coefficients yet improved capacity retention. Time-resolved quantitative optical emission spectroscopy demonstrates the suppression of V dissolution with the hybrid electrolyte in both pristine and cycled electrodes. Operando synchrotron X-ray diffraction and absorption provide mechanistic insights. Hydrated NVO with wider interplanar spacing exhibits much higher H + /Zn 2+ capacity, while the Na 2 SO 4 mitigates the formation of irreversible side products. Furthermore, this study demonstrates that the use of hybrid electrolytes and control of crystallite size in the parent material can significantly improve electrochemical behavior of layered V-based cathodes in Zn-ion batteries, providing a general strategy toward safe and resilient aqueous battery systems.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Tri-level hybrid interval-stochastic optimal scheduling for flexible residential loads under GAN-assisted multiple uncertainties

Various building loads, such as heating, ventilation, and air conditioners (HVACs), electric water heaters (EWHs), and electric vehicles (EVs), can introduce opportunities for improving the flexibility of electricity consumption while satisfying the needs of building owners as well as benefiting the resilience of distribution system. To utilize such flexibility, a tri-level distribution market framework is established, including residential consumers, load aggregators (LAs), and the distribution system operator (DSO). In this work, the uncertainties from all three levels are considered. The random consumption behavior at the consumer level is modeled as a Gaussian noise that is also aggregated and transmitted to the LA level. The weather temperature in the LA level is forecasted as an interval, and the photovoltaic (PV) power in the market-clearing level is modeled by a set of power scenarios generated by Generative Adversarial Networks (GANs). Then, a hybrid interval-stochastic programming is proposed to transform the uncertain problems in the first two levels into deterministic ones. For real-time implementations, a rolling horizon optimization (RHO) scheme is employed to continuously optimize the power consumption based on the latest operating information. Finally, case studies on a modified IEEE 69-bus system validate the effectiveness of the proposed uncertainty modeling strategies and the RHO scheme.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

A review of Geological Thermal Energy Storage for seasonal, grid-scale dispatching

Energy storage is essential for the decarbonization of the U.S. energy grid, especially with the increasing deployment of variable renewable energy sources like solar and wind. Geological thermal energy storage (GeoTES) has emerged as a promising long duration, grid scale solution, providing stability and security through flexible operations and valuable grid services. GeoTES utilizes subsurface reservoirs to store thermal energy for power generation and direct-use heating and cooling. This approach significantly enhances the use of low-temperature reservoirs, which would otherwise be unsuitable for geothermal power plants. It also aligns well with depleted oil and gas reservoirs, concentrating solar power, non-flexible renewables (photovoltaic and wind), and geothermal-related power cycles. Given the favorable marginal costs of GeoTES as storage duration increases, it becomes particularly competitive for seasonal, grid-scale dispatch, where few technologies are viable. This paper provides a comprehensive review of GeoTES systems and the research underpinning itsr development. This analysis begins by defining and categorizing the unique characteristics of thermal energy storage techniques, setting GeoTES apart from other technologies. The various components, configurations, subsurface characteristics, and modeling efforts that guide GeoTES development are then explored. Finally, challenges in GeoTES research, development, and deployment are discussed, along with mitigation strategies and lessons from related technologies. Beyond their economic benefits, GeoTES systems support grid resilience and decarbonize industrial processes. Their scalability, broad distribution, seasonal storage potential, and flexible dispatch capacity make GeoTES a valuable tool for expanding renewable energy deployment and addressing climate change.

15 - GEOTHERMAL ENERGY↗