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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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At least 253 records · Page 14

Swing Contract-Based Valuation for Distributed Energy Resources in Transactive Energy Systems: A Reinforcement Learning Approach

With the proliferation of distributed energy resources (DERs) and power grids with high fractions of renewable energy, market constructs are evolving to allow DERs to participate in multiple possible markets, at different levels of grid hierarchy. The effective participation of DERs in market environments is aided by swing contract-based pricing mechanisms, whereby DERs have a two-part compensation structure – one for their reservation/commitment and another for performancedriven ex-post payment for their actual mobilization during dispatch. In this paper, we propose a reinforcement learningbased (Q-learning) approach that allows a rational DER agent to select the market it wants to participate in within a composite market environment where individual markets are coordinated by possibly different actors. The proposed Q-learning framework aids DERs in their self-valuation by implicitly maximizing their own payoff through market participation, assuming a swing contract-based compensation structure. We complement our work through simulation-based investigations where factors affecting the DER decision making process, such as parametric uncertainties in market (and grid) environments, are studied.

Naqvi, Syed Ahsan Raza↗

Techno-Economic Assessments of Second-Life Batteries for Electric Vehicle Charging Stations

When electric vehicle (EV) batteries degrade below a certain capacity, they may no longer be suitable for automotive use but can be repurposed as second-life batteries (SLBs) for other applications, such as EV charging stations. When integrated with photovoltaic (PV) systems, SLB can store surplus solar energy, reducing reliance on the grid and lowering operational costs. This paper presents a novel techno-economic assessment framework for deploying SLBs in combination with PV in grid-connected EV charging stations. The proposed framework integrates the value proposition, charging station operation, optimal dispatch strategies, battery degradation modeling, input data requirements, and detailed procedures for generating key economic performance metrics. Insightful analyses are performed to assess the performance of SLBs in comparison to new batteries across various cost scenarios. The results indicate that SLBs become financially attractive when their cost is 40% or lower than new batteries.

energy storage↗

Frequency Control and Disturbance Containment Using Grid-Forming Embedded Storage Networks

The paper presents a distributed approach for operating a network of inverter-based energy storage resources embedded in a bulk power system. Departing from their traditional role of steady-state reserves, the storage assets in the network are utilized as frequency-responsive resources shaping system dynamics. The power electronics converter systems interfacing the storage resources are equipped with local controllers designed to respond under transient disturbances. To this end, a safety-constrained distributed control strategy is explored. The paper compares the performance of converter-interfaced grid-forming and grid-following storage networks for fast frequency control and disturbance containment/localization. Sensitivity studies are performed to study the impact of storage size, steady-state dispatch, and controller design on dynamic performance. The findings are presented through case studies with results from the IEEE test systems.

Chatterjee, Kaustav (ORCID:0000000153273860)↗

Practical Implementation of GPU-based Computing at the Grid Edge for Resilience Scenarios

This paper presents a practical implementation of GPU-accelerated computing at the grid edge to enhance power system resilience through next-generation smart meters. Advanced Metering Infrastructure (AMI) systems rely predominantly on centralized processing architectures, which limit real-time response capabilities during grid disturbances. This work proposes the integration of GPU-enabled computational platforms directly within smart meter to enable local execution support for power system analytics, fault detection algorithms, and optimization routines. The proposed framework uses the Julia programming language to leverage highperformance parallel computing capabilities while maintaining code portability and development efficiency. We use two experimental scenarios to benchmark the computational feasibility of this approach: sparse linear system solutions representative of power flow analyses, and multi-stage production cost simulations incorporating unit commitment and economic dispatch operations. Results demonstrate that computationally intensive power system algorithms, such as those supporting resilience scenario calculations, can be effectively executed at the distribution edge using commercially available embedded GPU hardware. Keywords—GPU acceleration, edge computing, smart meters, grid resilience, AMI, resilience.

De Souza, Reubun [School of Electrical Engineering↗

Insights Into On-Demand Transit: A Case Study of Houston METRO's curb2curb Transit Services: Preprint

As modern on-demand transit (ODT) deployments increase, the insights gained from studying real-world systems prove more useful. In this study, a shared ODT system called "METRO curb2curb" in the suburbs of Houston, Texas was studied, with a particular focus on the Missouri City zone, which has the highest ridership out of the four total zones in which the system operates. The Missouri City zone spans 18 square miles with an average daily ridership of nearly 400 as of November 2024. In order to gain a passenger perspective, data collection was performed through using the ODT system first-hand, completing 50 rides in March and April of 2023. These rides included a mix of three different types of on-demand travel accommodations - 1.) advance bookings (30 min - 2 hours ahead), 2.) as-soon-as-possible / real-time dispatch bookings, and 3.) no-reservation trips at two designated "anchor points." Wait and travel time were collected for each ride. Anecdotal findings related to ease of locating the driver/vehicle, the process of booking a ride, and popular trip purposes were also documented. This study provides an overview of the METRO curb2curb system, including its history, service provider, service area, ridership, booking options, wait time, and travel time. Intricacies related to different definitions of wait time are included. Finally, relevant considerations for automating the on-demand transit system and discussed.

33 ADVANCED PROPULSION SYSTEMS↗

Use of Digital Real-Time Simulation and Optimization to Identify Maximum Real Power Injection on the Banshee Distribution Network: Preprint

This study investigates the hosting capacity of the Banshee Distribution Network by optimizing the real power injection at carefully selected Distributed Energy Resource (DER) locations. The analysis is conducted within the framework of power system operational constraints, including bus voltage ranges, thermal line ratings, and transformer loading limits. A Python-based Genetic Algorithm (GA), implemented using the PyGAD library, is employed to iteratively identify the optimal power injection configuration that maximizes network utilization while preserving system reliability. The methodology integrates a real-time simulation environment using the Real-Time Digital Simulator (RTDS), allowing high-fidelity evaluation of power flow and voltage behavior under each proposed injection scenario. By coupling the optimization algorithm with real-time simulation feedback, this approach ensures that both static and dynamic constraints are enforced during the evaluation process. The GA leverages evolutionary operators such as selection, crossover, and mutation to navigate the nonlinear search space efficiently. The results of the study delineate the feasible hosting capacity at three targeted buses, reflecting maximum real power levels that can be injected without causing voltage violations, transformer overloading, or line congestion. These findings provide a decision- support tool for distribution planners and utilities aiming to integrate higher penetrations of DERs in existing infrastructure. Additionally, the work lays the foundation for extending such optimization techniques to multi-objective formulations, including economic dispatch and reactive power coordination, in future studies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Classic and Quantum Task-Based Intelligent Runtime for QIRs Running on Multiple QPUs

High-performance computing systems are rapidly evolving into heterogeneous platforms that fuse quantum accelerators with traditional classical processing units (CPUs) and graphical processing units (GPUs). This convergence calls for runtimes capable of managing both classical and quantum workloads in a unified manner. We introduce an intelligent, task-based runtime that marries the Intelligent RuntIme System (IRIS) asynchronous scheduler with a quantum programming stack through the Quantum Intermediate Representation Execution Engine (QIR-EE). Our design allows programs written in the quantum intermediate representation (QIR) to be dispatched concurrently to a variety of back-ends, including multiple quantum simulators and nascent quantum processors, enabling genuine hybrid execution on a single node. To illustrate its practicality, we partition a 4-qubit and 20-qubit circuit into three sub-circuits using quantum circuit cutting via the QCut library. Each sub-circuit is simulated independently by the QIR-EE driver within IRIS, after which a classical post-processing step merges the simulation results to recover the outcome of the original full-circuit computation. This case study demonstrates how finer task granularity can enable the parallel execution and lower the simulation burden per quantum task while preserving overall accuracy, highlighting the feasibility of our hybrid approach.

Miniskar, Narasinga Rao [ORNL] (ORCID:000000018259↗

Data Centers and Digital Assurance Introduction to Supply Chain and Cybersecurity for Data Centers, Session 1

The first session of the TADA (Technical Assistance for Digital Assurance) Data Centers Cohort Workshop, held on October 30, 2025, introduced foundational concepts of Digital Assurance in the context of data center and grid integration. Sponsored by the U.S. Department of Energy, the workshop brought together utilities, data center operators, developers, and vendors to address cybersecurity and supply chain vulnerabilities. The session emphasized the growing criticality of data centers within the electric grid and the need for secure, real-time, bidirectional communication. Participants explored the principles of Digital Assurance, including cybersecurity, cyber-informed engineering (CIE), and lifecycle security, and applied a threat-vulnerability-consequence framework to identify and mitigate risks at the data center–grid interface. Discussions covered a range of threats such as spoofed dispatch signals and insider threats, architectural vulnerabilities like SCADA interfaces and insecure protocols, and potential consequences including cascading grid failures. The session also raised strategic questions about business value, vendor assurance, and defining cyber boundaries and responsibilities. This foundational workshop set the stage for deeper technical analysis and the development of actionable frameworks in subsequent sessions. Session 1 of 3.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

Enhancing Synchronous Condenser Operation of Hydrogenerators

Hydropower plants are sometimes dispatched below capacity or even shut down to meet water regulations. These can temporarily be repurposed to operate as synchronous condensers. To enable this capability, this paper proposes a design that allows hydrogenerators to safely operate as synchronous condensers, providing fast voltage and reactive power support under both normal and boost conditions. The proposed design integrates capability curves with hydrogenerators’ excitation systems through modifications using proposed MVA-field current curve, current controller, and limiter. The design is implemented locally at the machine for rapid response. Simulation results demonstrate the effectiveness of the proposed design and using hydrogenerators as synchronous condensers in power grids.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

Grid and Wind Transient Ride Through Assessment of Type-5 Synchronous Wind Turbine

The integration of the inverter-based renewable energy resources is increasing and replacing conventional synchronous generators in the evolving bulk power system (BPS), impacting the system inertia along the way. Also, the limited over-current capability of power electronic converters continues to deteriorate the grid strength of the evolving power systems. Type-5 wind turbines have the potential to mitigate these problems because this configuration interfaces with the grid through a synchronous generator; hence, its operation and consequent grid impacts might mimic the conventional synchronous generator. The drivetrain of this type of turbines, however, is different from the more common Type-3 and Type-4 turbines. A hydraulic torque converter and gearbox with torque limiting feature are integral parts of a Type-5 wind turbine drivetrain, to isolate the wind speed variations at the wind turbine rotor from the grid connected generator side. This supports the synchronous operation of the generator. However, high fidelity models of Type-5 wind turbine drivetrain including these core components are not openly and widely available for grid integration and transient stability studies. Moreover, Type-5 turbines are not commonly deployed and hence its power generation and frequency stability characteristics are not widely publicized. This hinders appropriate assessment of Type-5 wind power plant's contribution to bulk grid resilience. This work provides transient stability assessment of a standalone Type-5 wind turbine. Normal operation and grid transient studies are performed to see the step load change and wind speed disturbance impacts on the Type-5 drivetrain and generation dispatch. Preliminary results show that Type-5 wind turbines can support load changes of between 0.6 p.u to 1.15 p.u. Beyond this point, the synchronization of the generator starts to deviate from its set point.

17 - WIND ENERGY↗

Characterizing and improving the performance of molten-salt-steam heat exchangers in concentrating solar power plants

Shell-and-tube heat exchangers (HXs) for steam generation from molten salts in concentrating solar power (CSP) plants experience thermal fatigue due to significant temperature gradients and inherent transient operation. Molten salt-steam HX design lifespans exceed actual lifespans, and, as a consequence, designers overpredict plant profitability and operators neglect appropriate prescriptions to optimize these lifetimes. Here, this study refines HX lifespan estimates with data benchmarked against thermal-fluid mechanical modeling of stress and accumulated fatigue. Reduced-order thermal models of the molten salt-steam, shell-and-tube evaporator and superheater predict transient temperature profiles along the two HXs salt-steam flow paths. The modeled evaporator and superheater temperature profiles enable assessment of cyclic stresses within the HX tubesheets, where molten-salt HX failures are most common. Evaporator and superheater performance data from a current 110 MW elec commercial CSP plant provide a basis for validating the reduced-order HX models. HX life predictions derived from stochastic failure distributions serve as inputs for simulating and optimizing existing plant operations. The impact of the updated lifespans on overall plant revenue depends on operating scenarios. This study suggests that typical ramping rates for a CSP plant with a high-temperature Rankine cycle result in an evaporator and superheater life of approximately 10 and 25 years, respectively, compared to the design target of 30 years. Reduced HX lifespans decrease operational plant revenue on average by 4.6-5.1%. Furthermore, there may be as many as four HX replacements over the 30-year lifetime of the plant; and, purchase agreement loss due to failure to meet contractual production requirements can have ramifications that include the risk of bankruptcy.

14 SOLAR ENERGY↗

Iterative methods in GPU-resident linear solvers for nonlinear constrained optimization

Linear solvers are major computational bottlenecks in a wide range of decision support and optimization computations. The challenges become even more pronounced on heterogeneous hardware, where traditional sparse numerical linear algebra methods are often inefficient. For example, methods for solving ill-conditioned linear systems have relied on conditional branching, which degrades performance on hardware accelerators such as graphical processing units (GPUs). To improve the efficiency of solving ill-conditioned systems, our computational strategy separates computations that are efficient on GPUs from those that need to run on traditional central processing units (CPUs). Our strategy maximizes the reuse of expensive CPU computations. Iterative methods, which thus far have not been broadly used for ill-conditioned linear systems, play an important role in our approach. In particular, we extend ideas from Arioli et al., (2007) to implement iterative refinement using inexact LU factors and flexible generalized minimal residual (FGMRES), with the aim of efficient performance on GPUs. In conclusion, we focus on solutions that are effective within broader application contexts, and discuss how early performance tests could be improved to be more predictive of the performance in a realistic environment.

97 MATHEMATICS AND COMPUTING↗

Multi-parametric analysis for mixed integer linear programming: An application to transmission upgrade and congestion management

Upgrading the capacity of existing transmission lines is essential for meeting the growing energy demands, facilitating the integration of renewable energy, and ensuring the security of the transmission system. This study focuses on the selection of lines whose capacities and by how much should be expanded from the perspective of the Independent System Operators (ISOs) to minimize the total system cost. We employ advanced multi-parametric programming and an enhanced branch-and-bound algorithm to address complex mixed-integer linear programming (MILP) problems, considering multi-period time constraints and physical limitations of generators and transmission lines. To characterize the various decisions in transmission expansion, we model the increased capacity of existing lines as parameters within a specified range. This study first relaxes the binary variables to continuous variables and applies the Lagrange method and Karush-Kuhn-Tucker (KKT) conditions to obtain optimal solutions and identify critical regions associated with active and inactive constraints. Moreover, we extend the traditional branch-and-bound (B&B) method by determining the problem’s upper and lower bounds at each node of the B&B decision tree, helping to manage computational challenges in large-scale MILP problems. Here, we compare the difference between the upper and lower bounds to obtain an approximate optimal solution within the decision-makers’ tolerable error range. In addition, the first derivative of the objective function on the parameters of each line is used to inform the selection of lines for easing congestion and maximizing social welfare. Finally, the capacity upgrades are selected by weighing the reductions in system costs against the expense of upgrading line capacities. The findings are supported by numerical simulations and provide transmission-line planners with decision-making guidance.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A Systematic Review on Coordinated Restoration Strategies for Power Distribution Grids

Power distribution grids are increasingly exposed to High-Impact Low-Probability (HILP) events, which cause widespread disruptions with severe societal and economic impacts. The growing complexity of modern grids, driven by the integration of distributed energy resources and smart grid technologies, has introduced new challenges to effective service restoration. While significant research has explored individual restoration strategies, such as network reconfiguration and microgrid formation, limited attention has been given to methods in which they can be effectively coordinated. Furthermore, the absence of systematic review papers addressing this issue hampers the development of cohesive restoration frameworks capable of addressing the operational complexities of modern grids. This paper presents a systematic review synthesizing existing knowledge on power grid restoration, identifying key limitations, and highlighting opportunities for coordinated strategies. By addressing research gaps and emphasizing the integration of diverse approaches, this study provides critical insights for advancing grid resiliency and recovery, offering a foundation for future research and practical applications in the face of HILP events.

Systematic review↗

Bidding Curve Design for Hybrid Power Plants with Uncertain Solar Forecast

This paper presents a novel bidding curve design algorithm tailored for hybrid power plants (HPPs) to participate in the wholesale electricity market. Utilizing forecasts for photovoltaic (PV) generation and available battery power, our algorithm strategically computes the bidding curve to maximize HPP profit while adeptly managing the inherent uncertainty associated with PV power generation. In addition, the introduction of the penalty cost in HPP bidding curves provides the system operator a tool to effectively manage the system-level uncertainty that caused by HPPs. Numerical analysis through Monte Carlo simulations confirms that our bidding curve methodology outperforms the benchmark across various scenarios.

bidding curve↗

Hazard and risk analysis framework for nuclear power plant–based integrated energy systems

Employing integrated energy systems (IESs) with nuclear power plants (NPPs) can improve NPP utilization by leveraging dedicated thermal and electric power delivery, but it may also increase operational safety risks. This paper presents a framework to identify and quantify hazards and risks for such IESs. The framework combines accidentology to review past industrial accidents with failure modes and effects analysis (FMEA) to identify potential future incidents. Hydrogen explosion and toxic chemical release hazards are of particular concern. Explosion consequences are quantified using the Bauwens-Dorofeev (Bauwens) and trinitrotoluene equivalent mass (TNT-EM) methods, while chemical release consequences are computed using the Gaussian atmospheric dispersion method. Operational disturbances from direct electrical and thermal integration that may affect NPP safety are modeled using probabilistic risk analysis (PRA). Hazards and risks are then evaluated for regulatory compliance. The framework is applied to IESs comprising pressurized or boiling water reactors supplying three levels of thermal and electrical power to industrial customers. Case studies include high-temperature steam electrolysis hydrogen plants of varying capacities and a synthetic fuel production plant. Sensitivity analysis examines piping component failures in the PRA model as a precursor to cost estimation for thermal extraction line design. Additionally, Fussel-Vessely (FV) and risk increase importance (RII) measures identify risk-informed design improvements for the thermal extraction system. FMEA highlights hazards such as loss of offsite power, prompt loss of electrical load, loss of thermal output, and immediate steam diversion, in addition to hydrogen explosions and toxic chemical releases. Both Bauwens and TNT-EM methods suggest maintaining several hundred meters of separation between the NPP and hydrogen facility to mitigate explosion risks. PRA results show a maximum initiating event frequency increase of 1.15% and an overall risk increase of 0.28%. Importance measure analysis identifies upstream pipe leak isolation components as critical. Evaluating the results against safety regulations, it is concluded that hazards and risks can be managed to comply with regulations through risk-informed thermal and electrical connection designs, component selection, maintenance programs, and safe separation distances between NPPs and integrated industrial facilities.

08 - HYDROGEN↗

Hydropower Flexibility Framework (Final Technical Report)

The Hydropower Flexibility Framework (HFF) tool focuses on providing the hydropower community with an effective means of assessing optimized hydropower plant outcomes. This tool combines both site specific characteristics, which act to constrain plant operation, and the hydrologic and grid characteristics which drive hydropower plant operation. The hydropower community faces a confluence of factors which drive the importance of developing such a capability, including an aging hydropower fleet subject to a range of modernization opportunities, a large number of hydropower plant relicensing activities which may affect operational requirements, an electrical grid with increasing levels of variable resources which must be balanced to maintain grid stability, and climate change influencing riverine hydrologic patterns outside of design characteristics. With support from the hydropower community, the project team developed the HFF tool and demonstrated the tool through a series of Use Cases. This guidance was developed as a part of the larger HFF tool User’s Manual (see Appendix B), a resource designed to inform other users and to empower community uptake of the tool. The HFF tool, hosted at https://hfftool.com/, was developed with the support of the U.S. Department of Energy (DOE) Water Power Technologies Office (WPTO). EPRI is currently exploring alternatives to support the continued maintenance and functionally of the online tool.

13 HYDRO ENERGY↗