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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Design, Deployment, and Characterization of the World’s First Flexible Large Power Transformer

As we know, power transformers are the most critical asset of the transmission network. Although highly reliable, they still can fail prematurely or ultimately retire at the end of their service life. In today’s design practices, transformers are tailored to their specific application and therefore cannot replace each other unless identical. Additionally, they provide minimal support to the grid operation and therefore limit the grid flexibility and resiliency when facing severe conditions. In this presentation, we will introduce the concept of flexible power transformer and demonstrate how one single unit can serve as a spare to multiple units in a given fleet, allow to control the power flow between transformers or lines operating in parallel and ultimately be used to limit subsequent faults in transmission lines. We will also introduce the world’s first prototype in operation, a 60MVA, 165kV flexible autotransformer.

flexible power transformer, autotransformer, varia↗
DOE OSTI2025

Reimagining Energy Efficiency Resource Standards

Energy Efficiency Resource Standards (EERS) are a long-standing policy used to advance state goals and priorities, such as reliability, affordability and decarbonization. They ensure cost-effective energy efficiency is used to lower energy consumption, reduce peak demand, and enable grid flexibility. Adapting EERS through strategic design, and integrating EERS into broader energy plans and policies, can help states optimize their approach to meet modern and evolving power system needs and achieve sustainable energy outcomes. This report examines how states consider energy efficiency in the context of four policy priorities: providing grid benefits, addressing load growth, reducing emissions, and promoting affordability. It provides examples of states that are pursuing these priorities, reviews the role of energy efficiency in them and identifies opportunities to further promote energy efficiency alongside the priorities. Decisionmakers and stakeholders can draw directly from these examples and findings to design an EERS that maximizes co-benefits, captures synergies, and promotes consideration of the all the possible solutions to advance their goals.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Advanced Transmission Technologies – GETs and HPCs Session 2: Advanced Power Flow Control and Transmission Topology Optimization

The INL TADA GETs Cohort Session 2, held on November 7, 2025, conducted in collaboration with ScottMadden, focused on two core Advanced Transmission Technologies (ATTs): Advanced Power Flow Control (APFC) and Transmission Topology Optimization (TTO). These technologies are pivotal in enhancing grid flexibility, reliability, and cybersecurity resilience. APFC, particularly through modular FACTS devices like Modular Static Synchronous Series Compensators (M-SSSCs), enables dynamic voltage injection to reroute power flows. The session highlighted the deployment benefits of APFC, such as rapid installation, minimal civil works, and re-deployability. Regulatory drivers like FERC Order 2023 mandate the inclusion of Grid-Enhancing Technologies (GETs) in interconnection studies. Case studies from Central Hudson, CAISO, and National Grid (UK) demonstrated APFC’s effectiveness in congestion relief and cost savings. The session also addressed cybersecurity concerns, including firmware vulnerabilities, SCADA integration risks, and supply chain dependencies. Participants engaged in interactive exercises to rank cybersecurity and supply chain risks, emphasizing the need for robust digital assurance strategies. TTO involves software-based reconfiguration of transmission networks to optimize power flow without new infrastructure. The session showcased its operational value, with examples from SPP, PJM, and MISO showing significant congestion cost reductions. Cybersecurity vulnerabilities were discussed, particularly in API security and software supply chains, referencing incidents like SolarWinds and attacks on Danish utilities. Digital assurance exercises explored worst-case scenarios, attack paths, and mitigation responsibilities between vendors and utilities. Reliability challenges such as algorithm stability, vendor dependency, and operator trust were also examined. Cross-cutting themes emphasized the importance of digital assurance tools, including Software Bills of Materials (SBOMs) and hardware-in-loop testing. Human performance, training, and operational confidence were identified as critical enablers of technology adoption. The session concluded with a preview of Session 3, which will focus on High Performance Conductors (HPCs) and risk-based cybersecurity tools. Session 2 of 3.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Impact of Glen Canyon Generation Loss

Colorado River Basin hydropower generation has faced challenges due to droughts and ecological and social water requirements. Specifically, Glen Canyon hydropower generation fluctuates substantially with recent extreme weather trends. Further, the western grid evolves with higher wind and solar share, and Glen Canyon hydropower's contribution to grid flexibility services is essential. The Western Area Power Administration (WAPA) markets and schedules electricity production at GCD, and the loss of this power could have significant financial consequences for the WAPA Colorado River Storage Project's (CRSP) Office because it may need to purchase relatively large amounts of energy to serve its firm electrical obligations. In addition, GCD provides grid reliability services for the WAPA Colorado-Missouri (WACM) balancing authority (BA). Both WAPA and DOE's Water & Power Technology Office (WPTO) are interested in researching how these drier hydrological conditions will impact federal electrical energy production, the Western Electricity Coordinating Council (WECC) power grid, and the value of hydropower in the face of lower production. We study multiple hydrologic and power grid scenarios to understand the grid impacts of the loss of Glen Canyon generation. The study uses a production cost model, water resources planning models, water-centric grid models, and various data analytic techniques. The study progress presentation discusses the selection of probable CRSP' hydropower scenarios and power grid scenarios to understand the impacts of Glen Canyon generation, which includes technologies that compensate the Glen Canyon energy and ancillary services contributions, transmission availability, and energy local marginal prices at interested grid locations of WAPA operation.

droughts↗
DOE OSTI2025

Virtual Power Plants: Pilots, Challenges, and Innovations Shaping Future Development

Virtual Power Plants (VPPs) aggregate distributed energy resources (DERs) to provide grid services traditionally delivered by centralized power plants. This article reviews the current state of VPP deployment, highlighting business models, compensation mechanisms, and global pilot projects. While VPPs offer benefits such as grid flexibility, resilience, and cost savings, challenges remain in communication infrastructure, regulatory frameworks, market access, and customer engagement. To address these, we propose a scalable, privacy-preserving hierarchical VPP architecture that coordinates with distribution utilities and preserves customer data. We also present the Integrated T&D Control Room of the Future as a key test bed for validating and accelerating VPP adoption. These innovations can help transition VPPs from pilot programs to integral components of a modern, reliable power grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

WBS 1.2.3.405 - Life Cycle Assessment of Storage Technologies

Recent commitments by the Biden administration have established targets to achieve a net-zero energy system by 2050. Meeting these targets will spur a rapid transition to clean energy technologies and a commensurate need to develop and deploy energy storage technologies at scale. Pumped Storage Hydro (PSH) is expected to be part of this solution because its ability to provide grid flexibility and stability and enable the dispatching of disparate variable renewable energy technologies. Despite PSH being a mature technology with a history of deployment dating back several decades, there is very little information on the greenhouse gas (GHG) implications of PSH as compared to other storage technologies. The objective of this project is to perform a full lifecycle assessment (LCA) of new PSH projects in the U.S. This LCA includes all project phases (resource extraction, construction, operation, maintenance, end-of-life). The functional unit for this study is 1 kWh electricity delivered by system to grid substation connection point and the estimated lifetime for our base case is 80 years. Data used in this study are based on over 30 potential PSH projects that are in preliminary planning phases and are represent a wide range of potential closed-loop PSH systems in terms of location, technology, and capacity. The project approach, data sources, and modeling assumptions have been informed by a technical review committee of stakeholders that include experts from academia, national and international government, industry, and utilities. The GHGs and energy return on investment (EROI) from PSH will be compared to other storage technologies (e.g., stationary battery storage). Results from this project will improve the PSH community's understanding of the environmental impacts and sustainability of new PSH projects and how PSH compares to other storage technologies. The approach used in this project relies on open-source programming. The analysis framework (source code and data) and will be made publicly available at the end of the project. In addition to reporting results for the base case, we will perform rigorous sensitivity analysis to identify the major drivers, understand impacts of different configurations, and future energy markets. Results from this project will be published in a suitable journal.

ENERGY PLANNING, POLICY, AND ECONOMY,HYDRO ENERGY↗
DOE OSTI2020

Axisymmetric hydrodynamics in numerical relativity using a multipatch method

In this paper, we describe a method of implementing the axisymmetric evolution of general-relativistic hydrodynamics and magnetohydrodynamics through modification of a multipatch grid scheme. In order to ease the computational requirements required to evolve the post-merger phase of systems involving binary compact massive objects in numerical relativity, it is often beneficial to take advantage of these system's tendency to rapidly settle into states that are nearly axisymmetric, allowing for 2D evolution of secular timescales. We implement this scheme in the spectral Einstein code and show the results of application of this method to four test systems including viscosity, magnetic fields, and neutrino radiation transport. Our results show that this method can be used to quickly allow already existing 3D infrastructure that makes use of local coordinate system transformations to be made to run in axisymmetric 2D with the flexible grid creation capabilities of multipatch methods. Our code tests include a simple model of a binary neutron star postmerger remnant, for which we confirm the formation of a massive torus which is a promising source of post-merger ejecta.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Dual-season thermal energy storage-integrated heat pump system for load shifting: experiments, modeling and nationwide analysis

Here, this paper proposes and validates a dual-season thermal energy storage-integrated heat pump (TES-HP) system that shifts building electric load in both cooling and heating modes using a single phase-change TES. The design uses the TES as a heat sink for the condenser in summer and a heat source for the evaporator in winter, thereby reducing on-peak electric demand while ensuring compatible with existing air-distribution systems. A 14-kW TES-HP prototype with six operating modes and novel refrigerant charge management strategies was experimentally tested under varied conditions. Subsequently, data-driven polynomial performance curves were developed and validated against experiments, then coupled with a phase change material (PCM) model and a calibrated building model within a rule-based controller. Single-day case studies demonstrated effective on-peak demand reduction while maintaining thermal comfort. During cooling, hourly power was lowered by up to 1.5 kW; in heating, average hourly power decreased from over 3.5 kW to 1.8 kW, compared to an HP-only system, achieving 64.5 % load shifting, and the need for resistance heating was eliminated. Seasonal simulations showed typical on-peak electricity savings of 25–35 % in cooling and 40–65 % in heating, with the largest benefits on the hottest and coldest days. Extended response-surface analysis and nationwide mapping quantified load shifting as functions of ambient and TES temperatures, revealing a seasonal trade-off in TES phase-change temperature. These results demonstrate the TES-HP system as a practical and scalable solution for grid-interactive buildings that reduces on-peak demand and electricity use while maintaining thermal comfort and enhancing grid flexibility and reliability.

Grid-interactive buildings↗
DOE OSTI2025

Grid Modernization of Cooperatives and Municipal Utilities via Breakthrough System Monitoring, Control and Optimization (CRADA Final Report)

This project aims at developing and demonstrating successful implementation of breakthrough approaches in real-time data visualization as well as real-time distributed DER control and optimization to provide ample benefits to both utilities and end users. The National Renewable Energy Laboratory (NREL), Holy Cross Energy (HCE), National Rural Electric Cooperative Association (NRECA) and Survalent are collaborating to enable Cooperative and Municipal utilities to fully leverage DERs as part of their strategies for providing safe, reliable, and affordable electric services to their customers and help meet DOE Grid modernization goal of achieving at least 10% active devices to provide grid flexibility by 2035. This project will use novel real-time control algorithms and approaches for distributed control recently developed under DOE-funded projects, using the date from the Survalent’s basic SCADA engine, GIS and AMI engines deployed at HCE combined with NRECA’s globally-used MultiSpeak(R) software interoperability specification for seamless and real-time communications between electric utility enterprise software to embrace DER as part of their strategies for providing safe, reliable and affordable electric service to their customers.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Deep reinforcement learning based optimization for a tightly coupled nuclear renewable integrated energy system

New ways to integrate energy systems to maximize efficiency are being sought to meet carbon emissions goals. Nuclear-renewable integrated energy system (NR-IES) concepts are a leading solution that couples a nuclear power plant with renewable energy, hydrogen generation plants, and energy storage systems, such that thermal and electrical power are dispatchable to fulfill grid-flexibility requirements while also producing hydrogen and maximizing revenue. Here, this paper introduces a deep reinforcement learning (DRL)-based framework to address the complex decision-making tasks for NR-IES. The objective is to maximize revenue by generating and selling hydrogen and electricity simultaneously according to their time-varying prices while keeping the energy flow in the subsystems in balance. A Python-based simulator for a NR-IES concept has been developed to integrate with OpenAI Gym and Ray/RLlib to enable an efficient and flexible computational framework for DRL research and development. Three state-of-the-art DRL algorithms have been investigated, including two-delayed deep deterministic policy gradient (TD3), soft-actor critic (SAC), proximal policy optimization (PPO), to illustrate DRL’s superiority for controlling NR-IES by comparing it with a conventional control approach, particle swarm optimization (PSO). In this effort, PPO has shown more-stable performance and also better generalization capability than SAC and TD3. Comparisons with PSO have demonstrated that, on average, PPO can achieve 13.9% more mean episode returns from the training process and 29.4% more mean episode returns from the testing process when different hydrogen-production targets are applied.

08 HYDROGEN↗
DOE OSTI2023

Privacy-preserving federated learning: Application to behind-the-meter solar photovoltaic generation forecasting

Here, the growing usage of decentralized renewable energy sources has made accurate estimation of their aggregated generation crucial for maintaining grid flexibility and reliability. However, the majority of distributed photovoltaic (PV) systems are behind-the-meter (BTM) and invisible to utilities, leading to three challenges in obtaining an accurate forecast of their aggregated output. Firstly, traditional centralized prediction algorithms used in previous studies may not be appropriate due to privacy concerns. There is therefore a need for decentralized forecasting methods, such as federated learning (FL), to protect privacy. Secondly, there has been no comparison between localized, centralized, and decentralized forecasting methods for BTM PV production, and the trade-off between prediction accuracy and privacy has not been explored. Lastly, the computational time of data-driven prediction algorithms has not been examined. This article presents a FL power forecasting method for PVs, which uses federated learning as a decentralized collaborative modeling approach to train a single model on data from multiple BTM sites. The machine learning network used to design this FL-based BTM PV forecasting model is a multi-layered perceptron, which ensures privacy and security of the data. Comparing the suggested FL forecasting model to non-private centralized and entirely private localized models revealed that it has a high level of accuracy, with an RMSE that is 18.17% lower than localized models and 9.9% higher than centralized models.

14 SOLAR ENERGY↗
DOE OSTI2026

Thermal property characterization of phase change materials in building applications: A systematic review of fundamentals, recent progress, and future directions

Phase change materials (PCMs) can reduce building peak loads and enable demand-responsive thermal energy storage (TES), but their deployment depends on reliable measurement and interpretation of thermal properties across laboratory, intermediate, and application scales. Here, this review systematically examines characterization methods, testing protocols, and recent advances for neat PCMs and PCM composites, emphasizing thermal conductivity, enthalpy-related properties (phase change temperature, latent heat, specific heat), and cycling stability. For thermal conductivity, we compare steady-state and transient techniques and note limitations when phase transition and contact resistance affect measurements. For enthalpy–temperature characterization, we discuss differential scanning calorimetry together with intermediate- and bulk-scale methods, including T-history, heat flow meter testing, and three-layer calorimetry (3LC), to generate application-relevant enthalpy–temperature profiles. Cycling stability is organized into four experimental families: thermoelectric–air, fully thermoelectric, water-bath, and in situ chamber approaches, with attention to separating reversible supercooling from true degradation such as phase segregation. We highlight emerging noncontact diagnostics, including infrared thermography and embedded sensing, for spatially resolved validation and multiscale interpretation. Finally, we review the growing use of AI and machine learning for property prediction, inverse characterization from experimental signals, and real-time state estimation in building-integrated TES. Key needs include harmonized protocols, interlaboratory benchmarking, uncertainty reporting, and metadata-rich datasets to accelerate reproducible PCM qualification for grid-flexible buildings.

AI↗
DOE OSTI2026

Distributed optimization and control for autonomous distributed energy resource power dispatch and frequency regulation considering communication failures

Distributed energy resources (DERs) can significantly enhance grid flexibility by supplying power and secondary frequency regulation (SFR) services. Yet, their large number and dispersed nature limit the effectiveness of traditional centralized power dispatch and frequency control schemes, and expose the system to single-point communication failures. This paper presents a unified distributed optimization and control framework for DER power dispatch and SFR provision. A transmission-loss-aware distributed direct current optimal power flow is first formulated to optimize DER power dispatch and reserve scheduling. On top of this, a fully distributed control scheme for DER autonomous SFR provision is developed to allocate automatic generation control signals cost-effectively while ensuring robustness to communication link disruptions. The framework is validated on IEEE 14-bus and 39-bus transmission systems with large-scale distribution feeders using transmission-distribution dynamic co-simulation, demonstrating reliable and autonomous DER power dispatch and SFR provision under diverse operating conditions and communication contingencies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Evaluating power grid model hydropower feasibility with a river operations model

Production cost models (PCMs) simulate dispatch of generators across a large power grid and are used widely by planners to study the reliability of electricity supply. As energy systems transition away from the thermoelectric technologies that have traditionally balanced electricity supply and demand, hydropower and its representation in PCMs is of increasing importance. A limitation of PCMs applied to continental power grids with diverse generation portfolios is that hydropower generation is simulated without full consideration of complex river dynamics, leading to possible misrepresentation of grid flexibility and performance. In addition, data used in PCMs may reflect outdated operating policies. In this paper we propose a hydropower generation feasibility test for PCMs. The approach uses a detailed hydropower model to determine whether the hourly hydropower schedule from a PCM with simplified monthly parameterization can be attained after accounting for realistic river dynamics and operating policies, such as spill requirements and general water movement and balance through a cascade reservoir system. We perform this hydropower generation test for the ‘Big 10’ hydropower system on the Columbia River (part of the Western Interconnect of the United States), revealing 9% overestimation of available hydropower generation in a PCM solution in an average hydrologic year. Our evaluation provides insight on the cost and opportunities for better representing hydropower in PCMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Hydropower representation in water and energy system models: a review of divergences and call for reconciliation

Abstract Reservoir-based hydropower systems represent key interactions between water and energy systems and are being transformed under policy initiatives driven by increasing water and energy demand, the desire to reduce environmental impacts, and interacting effects of climate change. Such policies are often guided by complex system models, whereby divergence in system representations can potentially translate to incompatible planning outcomes, thereby undermining any planning that may rely on them. We review different approaches and assumptions in hydropower representation in water and energy systems. While the models and issues are relevant globally, the review focuses on applications in California given its extensive development of energy and water models for policy planning, but discusses the extent to which these observations apply to other regions. Structurally, both water-driven and energy-driven management models are similar. However, in energy models, hydropower is often represented as a single-priority output. Water management models typically allocate water for competing priorities, which are generally uninformed by dynamic electricity load demand, and often result in a lower priority for hydropower. In water models, constraints are increasingly resolved for non-energy components (e.g. inflow hydrology and non-energy water demand); few analogues exist for energy models. These limitations may result in inadequate representations of each respective sector, and vastly different planning outcomes for the same facilities between the two different sectors. These divergent modeling approaches manifest themselves in California where poorly reconciled outcomes may affect decisions in hydropower licensing, electricity grid flexibility and decarbonization, and planning for environmental water. Fully integrated water-energy models are computationally intensive and specific to certain regions, but better representation of each domain in respective efforts would help reconcile divergences in planning and management efforts related to hydropower across energy and water systems.

Rheinheimer, David E. (ORCID:0000000315259069)↗
DOE OSTI2022

Same Goal, Different Pathways for Energy Transition: A More Holistic, Multisector, Community-Driven Approach

Low- and zero-carbon power systems are central to global decarbonization efforts. Costs for renewable energy (RE) and storage have fallen significantly, and advances in technologies and practices have improved the grid flexibility and stability needed to maintain the reliability of high-RE systems. Zero-carbon power systems, in turn, enable deep decarbonization through the electrification of other sectors, including transportation, buildings, and industry.

100% clean electricity↗
DOE OSTI2021

Adaptive bandwidth management for entanglement distribution in quantum networks

Flexible grid wavelength division multiplexing is a powerful tool in lightwave communications to maximize spectral efficiency. In the emerging field of quantum networking, the need for effective resource provisioning is particularly acute, given the generally lower power levels, higher sensitivity to loss, and inapplicability of optical detection and retransmission. In this letter, we leverage flex grid technology to demonstrate reconfigurable distribution of quantum entanglement in a four-user tabletop network. By adaptively partitioning bandwidth with a single wavelength-selective switch, we successfully equalize two-party coincidence rates that initially differ by over two orders of magnitude. Our scalable approach introduces loss that is fixed with the number of users, offering a practical path for the establishment and management of quality-of-service guarantees in large quantum networks.

42 ENGINEERING↗