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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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DOE OSTI2024

The circular bioeconomy: a driver for system integration

Background: Human and earth system modeling, traditionally centered on the interplay between the energy system and the atmosphere, are facing a paradigm shift. The Intergovernmental Panel on Climate Change’s mandate for comprehensive, cross-sectoral climate action emphasizes avoiding the vulnerabilities of narrow sectoral approaches. Our study explores the circular bioeconomy, highlighting the intricate interconnections among agriculture, forestry, aquaculture, technological advancements, and ecological recycling. Collectively, these sectors play a pivotal role in supplying essential resources to meet the food, material, and energy needs of a growing global population. We pose the pertinent question of what it takes to integrate these multifaceted sectors into a new era of holistic systems thinking and planning. Results: The foundation for discussion is provided by a novel graphical representation encompassing statistical data on food, materials, energy flows, and circularity. This representation aids in constructing an inventory of technological advancements and climate actions that have the potential to significantly reshape the structure and scale of the economic metabolism in the coming decades. In this context, the three dominant mega-trends—population dynamics, economic developments, and the climate crisis—compel us to address the potential consequences of the identified actions, all of which fall under the four categories of substitution, efficiency, sufficiency, and reliability measures. Substitution and efficiency measures currently dominate systems modeling. Including novel bio-based processes and circularity aspects might require only expanded system boundaries. Conversely, paradigm shifts in systems engineering are expected to center on sufficiency and reliability actions. Effectively assessing the impact of sufficiency measures will necessitate substantial progress in inter- and transdisciplinary collaboration, primarily due to their non-technological nature. In addition, placing emphasis on modeling the reliability and resilience of transformation pathways represents a distinct and emerging frontier that highlights the significance of an integrated network of networks. Conclusions: Existing and emerging circular bioeconomy practices can serve as prime examples of system integration. These practices facilitate the interconnection of complex biomass supply chain networks with other networks encompassing feedstock-independent renewable power, hydrogen, CO 2 , water, and other biotic, abiotic, and intangible resources. Elevating the prominence of these connectors will empower policymakers to steer the amplification of synergies and mitigation of tradeoffs among systems, sectors, and goals.

09 BIOMASS FUELS↗
DOE OSTI2024

The Transactive Energy Network Template Metamodel

While transactive energy, which is defined as an allocation of electricity based on dynamically discovered values or prices, has been extensively studied, its uptake and use has been slow. This report describes a tool, the transactive network template, which should hasten the creation and uptake of transactive energy networks. Some basic principles of transactive energy are familiar from existing wholesale electricity markets. Locational prices are calculated today for zones within bulk electric transmission systems. Locational prices differ while accounting for the locational costs of electricity generation and the losses and constraints incurred when electricity is transmitted from generators and distributed to consumers. A transactive energy network might include these transmission zones. However, current research strives to apply transactive energy also in electricity distribution circuits, buildings, and even for individual generating and consuming devices. At the same time, researchers explore how to apply transactive energy in real time during increasingly shorter time intervals. Automated computational agents become necessary as transactive energy becomes applied to smaller circuit zones and at faster dynamic timescales. A transactive energy network is an example of a multi-agent system. Each zone in the network is represented by its transactive agent, which makes decisions for and acts on behalf of a business entity that is responsible for and manages one of the circuit regions. A transactive energy network is also an example of a decentralized, distributed control system. Control decisions and responsibilities are distributed among the network’s transactive agents. The transactive agents are independent; that is, there typically is no centralized authority or oversight function. Instead, transactive agents exchange transactive signals and thereby negotiate the prices and quantities of electricity that they will exchange. Initially, the circuit regions and responsibilities of transactive agents appear to be very dissimilar. Each circuit region may comprise transmission, distribution, or building-level circuits. Each has a unique position and electrical connectivity within the transactive energy network. Each possesses unique assets that either generate or consume electricity, and these (e.g., renewable energy generator, diesel generator, aggregate utility load, building load, space conditioning, refrigerator, etc.) may further differ in their price flexibility and in their strategies for responding to dynamic electricity prices. Given such diversity, an implementer’s first inclination might be to start from scratch to define all these devices and to engineer their seemingly unique interactions. Given that each implementer’s perspective may be narrow within a transactive energy network, it is unlikely that uniquely engineered systems would interact well. This is where the transactive network template is applicable. The transactive network template is a metamodel that has been developed to guide implementers as they configure their own transactive agent within a network of such agents. The object-oriented design of the transactive network template provides basic code object types that may be used and extended by implementers to represent each of the assets in their circuit region. These objects further facilitate the transactive agent’s necessary computations, which are divided among responsibilities to schedule power usage, balance electric supply and demand, and coordinate the exchange of electricity with the other transactive agents. This report addresses the conceptual transactive network template design. Implementers are directed to more formal design documents and reference implementations. A Python™-based1 reference implementation of the transactive network template has been coded, and three implementations have been configured to represent a national laboratory and two university campuses. Version 2 of the transactive node template generalizes the market class and its methods to facilitate multiple, and more diverse market coordination mechanisms than were facilitated by and demonstrated using Version 1. Version 3 includes new Appendix B, which addresses the designs of methods that would make dynamic prices track approved electricity rates. In the future, the author wishes to make the transactive network template more generally applicable to networks that require more accurate power flow. Development of the transactive network template is jointly funded by the U.S. Department of Energy (DOE) Energy Efficiency and Renewable Energy and the DOE Office of Electricity. In late 2015, one of the first projects to be funded by the DOE Grid Laboratory Modernization Laboratory Consortium was the Clean Energy and Transactive Campus project, led by Pacific Northwest National Laboratory. DOE funds were matched by an investment by the Washington Department of Commerce through its Clean Energy Fund. The transactive network template was developed to guide the implementation of transactive energy networks within this project’s scope.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Become EV Friendly With Planning Resources for Charging Infrastructure

State and local governments are key to the successful build-out of a nationwide electric vehicle (EV) charging infrastructure network. Visit the Alternative Fuels Data Center for resources on EV infrastructure planning, including key considerations and best practices for navigating regulatory updates to streamline infrastructure build-out.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Analyzing Infrastructure Interdependencies Using Network-Of-Networks Modeling

Infrastructure networks play a crucial role in our day-to-day lives, and modeling these infrastructure networks can help decisionmakers prepare for and respond to disruptions such as natural disasters or cyberattacks. Because these infrastructure networks depend on each other, it is not sufficient to model a single network in isolation. We build on previous single-network-modeling techniques to develop a methodology for modeling infrastructure interdependencies as a Network-of-Networks. Using distributionlevel data from a real U.S. city on the power grid, road geometry, and hospital locations, we show how to apply this methodology to modeling three of the U.S. Department of Homeland Security's Critical Infrastructure Sectors: Healthcare, Transportation, and Energy. We also analyze three primary metrics before and after a simulated disaster: 1) impact on hospital access; 2) road network impact with the change in betweenness centrality; 3) electric customer outage. We simulate three different disruptions: 1) road flooding from nearby rivers; 2) a malicious actor targeting the road networks; 3) a malicious actor targeting the electric grid. Finally, we discuss how our methodology can be applied to additional infrastructure networks and types of disruption, and how Artificial Intelligence (AI) techniques may be incorporated into this methodology for further research.

Scherrer, Evan [Drake University, Iowa]↗
DOE OSTI2024

Biphasic response of human iPSC-derived neural network activity following exposure to a sarin-surrogate nerve agent

Organophosphorus nerve agents (OPNA) are hazardous environmental exposures to the civilian population and have been historically weaponized as chemical warfare agents (CWA). OPNA exposure can lead to several neurological, sensory, and motor symptoms that can manifest into chronic neurological illnesses later in life. There is still a large need for technological advancement to better understand changes in brain function following OPNA exposure. The human-relevant in vitro multi-electrode array (MEA) system, which combines the MEA technology with human stem cell technology, has the potential to monitor the acute, sub-chronic, and chronic consequences of OPNA exposure on brain activity. However, the application of this system to assess OPNA hazards and risks to human brain function remains to be investigated. In a concentration-response study, we have employed a human-relevant MEA system to monitor and detect changes in the electrical activity of engineered neural networks to increasing concentrations of the sarin surrogate 4-nitrophenyl isopropyl methylphosphonate (NIMP). We report a biphasic response in the spiking (but not bursting) activity of neurons exposed to low (i.e., 0.4 and 4 μM) versus high concentrations (i.e., 40 and 100 μM) of NIMP, which was monitored during the exposure period and up to 6 days post-exposure. Regardless of the NIMP concentration, at a network level, communication or coordination of neuronal activity decreased as early as 60 min and persisted at 24 h of NIMP exposure. Once NIMP was removed, coordinated activity was no different than control (0 μM of NIMP). Interestingly, only in the high concentration of NIMP did coordination of activity at a network level begin to decrease again at 2 days post-exposure and persisted on day 6 post-exposure. Notably, cell viability was not affected during or after NIMP exposure. Also, while the catalytic activity of AChE decreased during NIMP exposure, its activity recovered once NIMP was removed. Gene expression analysis suggests that human iPSC-derived neurons and primary human astrocytes resulted in altered genes related to the cell’s interaction with the extracellular environment, its intracellular calcium signaling pathways, and inflammation, which could have contributed to how neurons communicated at a network level.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Peer-to-peer communication control for resilient operations of networked cyberphysical systems

This report includes two main accomplishments of the peer-to-peer communication control for resilient operation of networked microgrids project in FY24, which include a scheme for cyberattack-aware coordination of networked microgrids for supporting voltages of bulk power systems and a scheme for price signal-based operations of EV-rich networked microgrids with mixed ownership. First, the cyberattack-aware scheme enables networked microgrids to distributedly determine the amount of reactive power injection to support the voltage of bulk power system (BPS) in a fair manner. In this scheme, a risk-informed algorithm is presented to generate the peer-to- peer (P2P) communication graph with minimal risk of attack on communication links. To deal with cyberattacks on MG controllers, the resilient consensus algorithm (CA) is utilized for MG controllers to robustly estimate the total reactive power headroom, from which the MGs can accurately provide the needed amount of reactive power injection for supporting the voltage of BPS. The CA implementation and performance within the P2P communication framework are demonstrated on the IEEE 39-bus system with 6 microgrids contained in the distribution feeder under different cyberattack scenarios. Second, the price-based scheme enables the usage of the real-time price signal for the operations of electric vehicle (EV)-rich networked-microgrids with mixed ownership, in which not all the microgrids can communicate with the distribution system operator (DSO). In this scheme, a max consensus is introduced to enable the real-time price signal to be propagated from the DSO to all the microgrids, from which each microgrid controller will manage the DERs to balance the load demand and the power injection from the EV charging stations within its microgrid. Numerical results over one day with 288 slots of 5-minute intervals on the modified 123-node test feeder including 3 microgrids with high penetration of EV are presented to evaluate how the price signal affects the operations of networked microgrids under different charging strategies of the EV charging stations. The result indicates that our proposed EVCS (dis)charging strategy, which leverages the flexibility of EVs to support the grid through discharging during peak demand, proves to be a cost-effective solution that reduces operational costs while improving the social welfare of EV charging.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Optimizing dynamic wireless charging for electric buses: A data-driven approach to infrastructure planning

The network configuration significantly impacts the performance of dynamic wireless charging (DWC) technology for electric buses. Here, this study presents a novel approach to planning charging infrastructure for public transit using data-driven nonconvex mixed-integer optimization. Integrating DWC and charging station technologies reveals a trade-off between enroute and stationary charging times. Our framework optimizes bus frequency settings and transmitter coil arrangements to minimize operational and infrastructure costs. A case study in Chattanooga, Tennessee, demonstrates the method's effectiveness in mitigating range anxiety and reducing charging expenses. This research implies that integrating DWC technology into public transit systems can enhance the feasibility and cost-effectiveness of electric bus operations, promoting sustainable urban mobility.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Digital Twin Based Condition Monitoring of LCC-LCC Inductive Power Transfer Systems

Inductive power transfer (IPT) systems provide a flexible, hands-free charging opportunity to electric vehicles (EV). The resonant network components and the transmitter and receiver coils are often subjected to high voltages or currents. Component aging in the compensation network and coils of resonant IPT systems is detrimental to the reliability and power transfer efficiency of the IPT system. Monitoring the component health of such multi-element complex systems requires robust optimization algorithms. This paper discusses condition monitoring of a resonant IPT system for an EV charger using a digital twin model. A hybrid estimation algorithm based on genetic algorithms and adaptive particle swarm optimization is developed to estimate the parameters of the digital twin model. Simulation results are used to verify the monitoring capabilities of the developed algorithm under various operating conditions of the IPT system.

Weldehawaryat, Lidya Mussie [graduate research ass↗
DOE OSTI2026

Optimized Gear Selection to Maximize Energy Savings in Electric Traction Drives for Medium and Heavy Duty Vehicles

Multi‑gear transmission systems are commonly used in electric traction drives for medium and heavy‑duty vehicles, while most passenger‑vehicle electric drivetrains rely on a single fixed ratio to reduce cost, weight, and complexity. Using multiple gear ratios can enable downsizing of the motor and inverter while still meeting performance requirements. Additionally, appropriately chosen ratios allow the motor to operate more frequently in high‑efficiency regions, improving overall energy usage and reducing operating costs over the drive cycle. This paper presents a systematic approach for selecting optimal gear ratios for electric drive systems. A neural‑network model is first developed to represent motor losses across the full torque–speed range using data generated from finite element analysis. This model enables fast, accurate evaluation of motor efficiency under varying operating conditions. A genetic‑algorithm‑based optimization framework is then applied to identify gear ratios that maximize energy cost savings over the drive cycle, with the resulting optimal ratios stored for real‑time implementation.

Gadiyar, Nishanth [ORNL] (ORCID:0000000348267524)↗
DOE OSTI2025

Coherency-Constrained Spectral Clustering for Power Network Reduction

This paper presents a methodology for reducing the complexity of large-scale power network models using spectral clustering, aggregation of electrical components, and cost function approximation. Two approaches are explored using unconstrained and constrained spectral clustering to determine areas for effective system reduction. Once the system areas are determined, both loads and generators by type are aggregated, and their new cost function is approximated through polynomial curve-fitting or statistical methods. The performance of reduced networks is evaluated in terms of their ability to follow the true daily cost of the original system over a 24-hour period considering a set of several days. Two test systems are taken as test beds. Application of the methodology to a modified version of the IEEE 39-bus system reduces it from 17 generators to a 4-bus system and 9 generators with about 93% of accuracy. Similarly, the IEEE 118-bus system is reduced from 19 generators to a 3-bus system with three aggregated units achieving over 99% of accuracy. These findings address scalability challenges and enhance accuracy for high and mid-loading level conditions, and by aggregating thermal units with similar cost functions.

42 ENGINEERING↗
DOE OSTI2025

Precision Time Protocol Performance Testing Over Optical Transport Network

The US Department of Energy Office of Electricity has partnered with Oak Ridge National Laboratory (ORNL) to find alternative precision timing solutions for the nation’s power grid. This effort is in response to the vulnerabilities identified in the Global Navigation Satellite System (GNSS), of which the US Global Positioning System (GPS) platform is a part. Additionally, Executive Order 139055 has highlighted the need for alternative or backup timing solutions. ORNL has established a Timing Lab and has been testing various technologies and timing devices as part of this effort. Precision Time Protocol (PTP), and the off-the-shelf timing devices and network connections that support it, are among the alternatives being tested. This work reports the accuracy of PTP over an Optical Transport Network (OTN) and is part of a series published by the Center for Alternative Synchronization and Timing (CAST).

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Dry-processed electrodes enabled by polytetrafluoroethylene fibrillation for high-performance lithium-ion batteries

The dry processing technique of polytetrafluoroethylene (PTFE) fibrillation offers significant advancements in cost reduction, environmental impact, and electrochemical performance. Dry processing alone allows for ∼ 20–60% cost reduction and increases of up to 40 mg cm⁻2 of areal loading – it typically comes at a reduction of rate capability. By leveraging the network structure of fibers, this method enhances rate capability and cycling performance, providing a compelling alternative to the conventional and currently predominant wet processing. The review delves into PTFE fibrillation mechanisms and examines critical influencing factors including material properties and processing parameters. It also discusses challenges associated with the electrodes fabricated by PTFE fibrillation, including structural instability due to insufficient PTFE fibrillization, compromised electrical conductivity from an insufficient conductive network, inhomogeneous dispersion resulting from the absence of solvents, restricted ionic transport due to increased electrode thickness, inadequate adhesion to current collector because of low surface energy of PTFE, electrochemical degradation due to low lowest unoccupied molecular orbital (LUMO) level of PTFE, particle damage during processing and environmental concerns related PTFE being a perfluoroalkyl and polyfluoroalkyl substances (PFAS). Recent research innovations aimed at mitigating these issues, their application in beyond-lithium batteries, and future research directions are thoroughly discussed.

Park, Hyunji↗
DOE OSTI2025

Resilience of the Electric Grid Through Trustable IoT-Coordinated Assets

The electricity grid has evolved from a physical system to a cyberphysical system with digital devices that perform measurement, control, communication, computation, and actuation. The increased penetration of distributed energy resources (DERs) including renewable generation, flexible loads, and storage provides extraordinary opportunities for improvements in efficiency and sustainability. However, they can introduce new vulnerabilities in the form of cyberattacks, which can cause significant challenges in ensuring grid resilience. We propose a framework in this paper for achieving grid resilience through suitably coordinated assets including a network of Internet of Things devices. A local electricity market is proposed to identify trustable assets and carry out this coordination. Situational Awareness (SA) of locally available DERs with the ability to inject power or reduce consumption is enabled by the market, together with a monitoring procedure for their trustability and commitment. With this SA, we show that a variety of cyberattacks can be mitigated using local trustable resources without stressing the bulk grid. Multiple demonstrations are carried out using a high-fidelity cosimulation platform, real-time hardware-in-the-loop validation, and a utility-friendly simulator.

distributed energy resources↗
DOE OSTI2024

Focus on monitoring and control of complex supply systems

The ongoing rapid transformation of our energy supply challenges the operation and stability of electric power grids and other supply networks. This focus issue comprises new ideas and concepts in the monitoring and control of complex networks to address these challenges.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Deep Reinforcement Learning for Distribution System Operations: A Tutorial and Survey

Here, the rapid evolution of modern electric power distribution systems into complex networks of interconnected active devices, distributed generation (DG), and storage poses increasing difficulties for system operators. The large-scale integration of distributed energy resources (DERs) and the rapid exchange of measurement data via communication networks present major opportunities for advancing grid operations but also introduce greater uncertainty, higher data dimensionality, more complex network and device models, and challenging control and optimization problems. Deep reinforcement learning (DRL) algorithms are promising in addressing these challenges. However, they have not been effectively adapted for power systems applications, requiring extensive customization for implementation and evaluation. This has resulted in reproducibility challenges and a steep learning curve for researchers new to applying DRL algorithms to the power systems domain. To bridge these gaps, this tutorial aims to serve as a valuable resource for researchers interested in exploring learning-based algorithms to operate active power distribution networks. Specifically, this work presents a generalized process for translating sequential decision-making problems in power distribution systems into Markov decision process (MDP) formulations, illustrated through concrete grid service examples. Additionally, we introduce a simple environment design strategy to develop and evaluate example DRL algorithms for distribution system applications, complete with an included code repository to guide users through environment construction.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Cybersecurity Risk Profiles for Distributed Energy Resource Management Systems

Managing the digitalization of increasingly diversity energy resources is a complex challenge for energy systems planners and managers. As the penetration of solar photovoltaics (PV) and other distributed renewable energy resources (DERs) expands, distributed energy resource management systems (DERMS) will play an increasingly important role in managing, monitoring, and controlling DERs as electric systems before more distributed, interconnected, and networked. However, the cybersecurity implications of DERMS deployments are not well understood today. A lack of understanding around the cybersecurity implications of DERMS deployments and variability in the security posture of DERMS vendors, owners, and operators could introduce new security risks to evolving electric power systems. This paper describes cybersecurity attack scenarios on DERMS, identifies related cybersecurity standards and guidelines, reviews the security features of state-of-the-art DERMS solutions, and offers cybersecurity guidance for DERMS vendors, owners, and operators to protect DERMS' unique capabilities. Standardizing cybersecurity requirements for DERMS could help improve the security of DERMS integrations and improve innovations that are more secure by design. The cybersecurity guidance found in this paper is intended to offer a unified approach and lay the foundation for future standardization of DERMS cybersecurity to reduce risk to the solar industry and other renewable energy stakeholders when integrating these technologies with electric power systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

A review of United States energy-only generator interconnection service policy and considerations for reform

Grid interconnection has emerged as a significant obstacle to the development of new electricity resources. There is growing interest in energy-only interconnection, which is an interconnection service option meant to allow the interconnection of new generators without ensuring their energy deliverability during all hours through the transmission system to customers. This approach potentially avoids upfront congestion-related transmission upgrades but could increase curtailment risk. Interest in energy-only interconnection is shaped by incomplete understanding of how interconnection policy functions in different jurisdictions, a knowledge gap that makes it difficult to determine how energy-only interconnection might be better used or re-designed. In this paper, we provide a regulatory review of energy-only interconnection in U.S. interconnection policy and practice, identifying jurisdictions in which rules are close to -or farther from-the theoretical concept of energy-only interconnection service. We find substantial jurisdictional differences in how energy-only interconnection is implemented, driven by differences in resource adequacy frameworks, real-time transmission operations, and state-level procurement practices. U.S. regulators have preferred local jurisdictional flexibility over federal prescription of interconnection study methods and procedures, which also contributes to differences among regions. Such findings raise fundamental questions about whether competition policies in electricity markets should extend beyond spot energy markets and into more prescriptive guidelines around interconnection rules and market entry. This paper sheds light on tensions that energy-only interconnection raises in allowing generators to access the transmission system on an as available basis and discusses how controlling thresholds for congestion-related network upgrades may be a barrier to electricity market entry.

Gorman, Will↗