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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Dispatching Grid-Forming Inverters in Grid-Connected and Islanded Mode: Preprint

This paper explores the dispatch-ability of grid-forming (GFM) inverters in grid-connected and islanded mode. Grid-forming (GFM) inverters usually use droop control to automatically share power with other GFM sources (inverters and synchronous generator (SG)) and follow the change of the load demand. However, they can be dispatched like their grid-following (GFL) counterparts to output the target active and reactive power. This will help the grid operator better manage their inverter-based resources (IBRs) for improved operation efficiency and reliability. Therefore, this paper proposes an innovative concept of dispatching GFM sources (inverters and SG) to output the target power for both grid-connected and islanded mode by adjusting their droop intercepts. The fundamental principle of doing so is that the GFM inverter's active and reactive power is dictated by its frequency and voltage, thus, dispatching active and reactve power of a GFM inverter can be achieved through dispatching its frequency and voltage. Moreover, the concept distinguishes the dispatch rules for grid-connected and islanded mode. Finally, the concept is validated with an example microgrid system with two GFM inverters, one diesel generator, one grid-following inverter and loads in both grid-connected and islanded mode. This pioneering work results in a practical guidance for power system energy management system (EMS) development to control a future grid with GFM and GFL inverters.

droop control↗
DOE OSTI2021

High-temperature Pumping of Silicon for Thermal Energy Grid Storage

As the cost of renewable energy falls below fossil fuels, the key barrier to widespread sustainable electricity has become availability on demand. Energy storage can enable dispatchable renewables, but only with drastic cost reductions compared to current batteries. One electricity storage concept that could enable these cost reductions stores electricity as sensible heat in an extremely hot liquid (>2000 °C) and uses multi-junction photovoltaics (MPV) as a heat engine to convert it back to electricity on demand, hours or days later. This paper follows previously reported technoeconomics and liquid containment, examining equipment that would be needed to exchange heat between resistive heaters, a molten silicon storage tank above 2000 °C, and a heat engine. Herein, we report on a pump that was designed and tested to circulate the liquid silicon between these three regions and the effect of spatial thermal cycling was simulated in models and experiments. While the pump successfully circulated silicon between 1800-2080 °C for ten hours, circulation with a temperature gradient caused it and other non-isothermal experiments to dissolve significantly due to the temperature dependent solubility of not only carbon, but also silicon carbide which otherwise protected the graphite infrastructure. Furthermore, methods to reduce dissolution and an alternative embodiment are presented.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Thermal energy grid storage: Liquid containment and pumping above 2000 °C

As the cost of renewable energy falls below fossil fuels, the key barrier to widespread sustainable electricity has become availability on demand. Energy storage can enable dispatchable renewables, but only with drastic cost reductions compared to current battery technologies. One electricity storage concept that could enable these cost reductions stores electricity as sensible heat in an extremely hot liquid (>2000°C) and uses multi-junction photovoltaics (MPV) as a heat engine to convert it back to electricity on demand hours, or days, later. Furthermore, this paper reports the first containment of silicon in a multipart graphite tank above 2000°C, using material grades that are affordable for energy storage at GWh scales. Low cost molded graphite with particle sizes as large as 10 μm successfully contained metallurgical grade silicon, even with as much as twothirds iron by mass for up to 10 hours and temperatures as high as 2300°C, in tanks as large as two gallons.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Replacing liquid fossil fuels and hydrocarbon chemical feedstocks with liquid biofuels from large-scale nuclear biorefineries

Liquid fossil fuels (1) enable transportation and (2) provide energy for mobile work platforms and (3) supply dispatchable energy to highly variable demand (seasonal heating and peak electricity). We describe a system to replace liquid fossil fuels with drop-in biofuels including gasoline, diesel and jet fuel. Because growing biomass removes carbon dioxide from the air, there is no net addition of carbon dioxide to the atmosphere from burning biofuels. In addition, with proper management, biofuel systems can sequester large quantities of carbon as soil organic matter, improving soil fertility and providing other environmental services. In the United States liquid biofuels can potentially replace all liquid fossil fuels. The required system has two key features. First, the heat and hydrogen for conversion of biomass into high-quality liquid fuels is provided by external low-carbon energy sources--nuclear energy or fossil fuels with carbon capture and sequestration. Using external energy inputs can almost double the energy content of the liquid fuel per unit of biomass feedstock by fully converting the carbon in biomass into a hydrocarbon fuel. Second, competing effectively with fossil fuels requires very large biorefineries—the equivalent of a 250,000 barrel per day oil refinery. This requires commercializing methods for converting local biomass into high-density storable feedstocks that can be economically shipped to large-scale biorefineries.

09 - BIOMASS FUELS↗
DOE OSTI2024

Market optimization and technoeconomic analysis of hydrogen-electricity coproduction systems

Decarbonization efforts across North America, Europe, and beyond rely on variable renewable energy sources such as wind and solar, as well as alternative fuels, such as hydrogen, to support the sustainable energy transition. These advancements have prompted a need for more flexibility in the electric grid to complement non-dispatchable energy sources and increased demand from electrification. Integrated energy systems are well suited to provide this flexibility, but conventional technoeconomic modeling paradigms neglect the time-varying dynamic nature of the grid and thus undervalue resource flexibility. In this work, we develop a computational optimization framework for dynamic market-based technoeconomic comparison of integrated energy systems that coproduce low-carbon electricity and hydrogen (e.g., solid oxide fuel cells, solid oxide electrolysis) against technologies that only produce electricity (e.g., natural gas combined cycle with carbon capture) or only produce hydrogen. Our framework starts with rigorous physics-based process models, built in the open-source Institute for the Design of Advanced Energy Systems (IDAES) modeling and optimization platform, for six energy process concepts. Using these rigorous models and a workflow to optimally design each technology, the framework is shown to be capable of evaluating new and emerging technologies in varying energy markets under a plethora of future scenarios (i.e., renewables penetration, carbon tax, etc.). Ultimately, our framework finds that solid oxide fuel cell-based coproduction systems achieve positive profits for 85% of the analyzed market scenarios. From these market optimization results, we use multivariate linear regression (R 2 values up to 0.99) to determine which electricity price statistics are most significant to predict the optimized annual profit of each system. The proposed framework provides a powerful tool for directly comparing flexible, multi-product energy process concepts to help discern optimal technology and integration options.

08 HYDROGEN↗
DOE OSTI2020

Role of Electric Vehicles in the U.S. Power Sector Transition: A System-Level Perspective

After over a century of petroleum dominance many anticipate that electrification could disrupt the transportation energy landscape. At the same time, the electric power systems are undergoing profound changes: variable renewables are displacing conventional generation sources; distributed generation is disrupting utility business models; energy storage and other new technologies are emerging; and the traditional system based on the premise that generation is dispatched to match an inelastic demand is evolving to create a system with greater participation in power system planning and operations from traditionally passive consumers. In this context, it is important to understand how transportation electrification will impact electricity demand and in turn electricity supply, including changes in the load shapes that characterize the system and the opportunity to leverage flexible electric vehicle (EV) charging to better integrate demand and supply. Assessing the impacts of electrification on the energy system requires an understanding of how it might impact the amount and shape of electricity consumption, and how this electricity can be supplied. In particular, increased adoption of electric vehicles introduces a new source of demand altogether, potentially very flexible. Moreover, electrification could shift the consumption of natural gas between sectors, thereby affecting the economics for natural gas-fired generation relative to other electricity generation options. Several factors will impact the evolution of the power system under a widespread electrified future, which, in turn, could have far-reaching effects on future energy costs and emissions.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Numerical study of advanced solar receiver tubes based on a coupled thermo-mechanical analysis for concentrated solar power tower plant

The search for more sustainable energy to match the growing energy demand begins with finding more dispatchable resources such as solar energy. As one of the promising solar technologies, concentrated solar power (CSP) has a full capacity to store thermal energy for extended operation. Nevertheless, some key components in CSP systems usually face extreme environment, such as uneven solar flux, cyclic thermal expansion, structural degradation on the solar absorber tubes in a Concentrated Solar Power Tower (CSPT) Plant. In this study, we applied Multiphysics simulation to explore the benefits of introducing optimized fins for heat transfer enhancement and uniform temperature distribution, the goal is to improve the thermal efficiency of such advanced solar absorber tubes. The results of this study can supply design guidance for the manufacturing process of absorber tubes, and eventually can benefit the solar energy community for the next generation of molten salt based CSP system.

14 SOLAR ENERGY↗
DOE OSTI2026

Operational Simulation of Multi-Functional Charging Station for Sustainable Transportation

As transportation systems move toward electrification and decarbonization, multifunctional charging stations (MFCS) are emerging as key infrastructure for electric vehicles (EVs) and hydrogen fuel cell vehicles (HFCVs). This paper presents a simulation model of an MFCS that integrates solar photovoltaic (PV), wind power, battery storage, hydrogen (\mathrm{H}_{2}) production, dual-pressure \mathrm{H}_{2} storage, fuel cells, and dynamic grid interactions. The model simulates daily operations using 5 -minute resolution data to capture realtime variability in renewable energy (RE), demand, and electricity prices. A flexible dispatch algorithm dynamically allocates energy for EV charging, \mathrm{H}_{2} production, storage, and grid transactions while respecting system constraints. Results show that the MFCS effectively prioritizes RE usage, minimizes waste, meets diverse energy demands, and achieves net operational profit. The model serves as a valuable decision-support tool for designing and optimizing integrated clean energy hubs for zero-emission transportation.

Gbadegoye, Jeremiah [University of Tennessee, Knox↗
DOE OSTI2026

Intelligent industrial demand response to increase grid flexibility and reliability: A review

The rapid transition toward renewable energy has introduced challenges in grid stability due to the intermittency of non-dispatchable sources like solar and wind. Industrial Demand Response (IDR) offers a promising, cost-effective solution that adjusts energy consumption patterns to align with supply, increases renewable utilization, and reduces costs. This review provides an updated analysis of IDR, sorting technologies into five categories: energy storage, scheduled energy usage, operational flexibility, on-site generation, and intelligent operations. Energy storage solutions, while requiring little flexibility, often have the longest payback periods. While slightly better, on-site generation also has longer payback periods, ranging from 5 to 20 years or more. Scheduled energy usage, operational flexibility, and intelligent operations allow significant peak reduction at lower capital costs but require greater flexibility. While 15–20 % peak reduction is within the range of all five categories, scheduled energy use and on-site energy generation are shown to have reductions of up to 70–80 % in select scenarios. Combining multiple IDR strategies from these five categories maximizes both financial and operational benefits. Synergistic approaches are shown to enhance grid stability while reducing costs. As the grid evolves, IDR will enable a more flexible, renewable-powered future that will benefit industrial facilities and the broader energy system.

Demand flexibility↗
DOE OSTI2020

Conceptual Design Study of a Thermal Energy Storage System Using Granular Solids for Coal-fired Boilers

<span style="font-size: 12pt;">Presentation for the 2020 International Pittsburgh Coal Conference held virtually from September 8-11, 2020.</span><span style="font-size: 12pt;">Abstract: As electricity from various renewable energy sources is increasingly supplied to the power grid, the grid’s stability will be challenged. Proposed grid-stability solutions will need to address variability of sources, such as solar and wind energy, in order to alleviate problems such as overgeneration and ramping. In regions where increases in solar energy are prominent, such as California, the net power demand curve often referred to as “the Duck Curve,” has caused problems for energy dispatchers, due to over-generation and fast ramping demands. In this project, we investigated a conceptual design for a Thermal Energy Storage System (TESS) integrated into a coal-fired power plant to support grid-scale storage. Implementing a TESS into power plants can allow for an increase in renewable sources, increase grid resilience, and allow conventional coal-fired plants to operate more efficiently. For this project, a TESS using granular solids as the energy-storage media is integrated into a conventional coal-fired power plant. The purpose of the TESS is to store energy from the flue gas during low demand periods and transfer the energy to steam during peak demand periods. The storage allows the stabilization of combustion and related boiler components at low loads and provides the opportunity to avoid some shutdowns. This study uses thermodynamic properties of several candidate thermal storage materials to estimate the size of storage system required for several operating scenarios. </span>

Huckaby, E. David↗
DOE OSTI2024

Economic dispatch of offshore renewable energy resources for islanded communities with optimal storage sizing

Coastal or isolated microgrids depend on diesel generators and could benefit from renewable energy resources, especially offshore wind and wave energy. Integrating these resources into microgrids is complicated by their high intermittency, which requires optimal economic dispatch to effectively evaluate. This study considers three coastal or islanded sites, and uses mid-fidelity models of wind and wave energy technologies, and local demand data to solve the optimal economic dispatch problem. An optimal storage sizing method is developed that finds the smallest capacity of energy storage required to meet the microgrid load during each season. The storage capacity decreases by a factor of two at most when adding wave energy converters to a system. Adding wave energy converters to a farm decreases cost by about 30%. Furthermore, the required storage size varies by two to three times from summer to winter. Compared with the state-of-the-art approaches that often overlook realistic offshore renewable energy technology in microgrid economic dispatch and optimal storage sizing, the proposed solution introduced in this study allows for better site selection, microgrid design, converter selection, and storage sizing considerations for isolated microgrids.

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

NRIC Strategy for Advancing Nuclear Integrated Energy Systems

Integrated energy systems (IES) combine low-carbon energy sources to meet demand for clean energy in multiple forms across multiple sectors of economy. IES create opportunities to cost-effectively dispatch generation resources to balance electricity supply and demand. In addition to producing electricity, IES increase the value of non-emitting energy sources by integrating generation technologies with industrial processes to efficiently produce commodities that benefit the manufacturing, industrial processing, and transportation industries. Nuclear energy technology is key to enabling these benefits. Advanced nuclear reactors capable of producing high-quality heat, electricity, and radiation, will play a foundational role in IES of the future.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

FORCE-DISPATCHES Integration - Initial Demonstration

Integrated energy systems (IES) combine, in mutually beneficial ways, power from variable renewable energy sources and nuclear power plants (NPP) to improve economic viability under uncertain market and weather conditions. The open-source Framework for Optimization of Resources and Economics (FORCE) tool suite, developed at Idaho National Laboratory (INL), has enabled comprehensive modeling and simulation of IES. The capabilities within FORCE include grid portfolio optimization through the Holistic Energy Resource Optimization Network (HERON) and the transient process model analysis library HYBRID, among others. Continuous efforts and investments from the IES programs have been made to expand and improve the versatility of the FORCE toolset in fiscal year 2022. Code-coupling and cross-tool communication have been important methods for improving this versatility. This report focuses on an additional workflow in the HERON tool for capacity and dispatch stochastic optimization through integration with the external tool Design Integration and Synthesis Platform to Advance Tightly Coupled Hybrid Energy Systems (DISPATCHES). DISPATCHES was primarily developed by the National Energy Technology Laboratory, in collaboration with other national laboratories, which included INL, universities, and industry partners. It is coupled to a library of algebraic models for specific plant components, and to a framework for stochastic optimization different from that provided in the current Risk Analysis Virtual Environment (RAVEN)-running-RAVEN algorithm in HERON. HERON currently conducts stochastic optimization via an outer-inner loop: it optimizes over variable capacity on the outer loop, and at each step within the capacity parameter space, conducts an inner optimization over scenarios (of market signals, demand, and/or weather patterns) and hourly dispatch throughout a user-specified number of years. On the other hand, DISPATCHES conducts stochastic optimization via an “all-at-once” strategy in which capacity variables are optimized at the same level as dispatch variables, as all scenarios are considered at once. The latter method works especially well for projects of limited size and project length, as the necessary computational power and memory increases with the number of variables and scenarios. The new capability to use the DISPATCHES workflow in HERON enhances standalone simulations by leveraging FORCE tools—namely, the economic metrics from the Tool for Economic Analysis (TEAL) and reduced-order model (ROM) sampling from RAVEN. The initial demonstration of the DISPATCHES workflow simulates an existing nuclear-case flowsheet within the DISPATCHES repository—this models a NPP with a secondary revenue stream for hydrogen production. Electrical output from the plant is converted to hydrogen via a proton-exchange membrane (PEM) electrolyzer, hydrogen tanks are used for storage, and an additional turbine is added for hydrogen combustion. Continued work regarding this FORCE-DISPATCHES integration will include automatic generation of DISPATCHES models from HERON inputs, offering analysts the option of using either the RAVEN-runsRAVEN or DISPATCHES workflow to solve technoeconomic optimization problems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Congestion Management Solutions for Enhanced Distribution System Operations with Aggregated Distribution Grid Resources Providing Grid Services and Market Participation

Microgrids and other aggregations of distribution grid resources (DGRs) are poised to actively participate in electricity markets and provide essential grid services in the coming years. In fact, DGRs already play such a role through behind-the-meter (BTM) demand response programs and small-scale BTM dispatchable generation initiatives. At the same time, the rapid growth of artificial intelligence (AI) and cryptocurrency datacenters imposes significant, often unpredictable, demands on the power distribution system. Aggregated DGRs can serve as flexible resources that help mitigate these pressures by using available transmission and distribution capacity more efficiently, supporting resource adequacy and other reliability services, and providing bridge strategies while long-term transmission infrastructure is being developed. The impacts this activity will have on distribution networks are not fully understood and could present significant challenges for distribution utilities due to capacity constraints and the need for congestion management. Technical issues include reverse power flow, variability and possible degradation of equipment integrity, voltage violations, and customer power quality concerns. These issues will likely intensify as electricity market operators across the United States implement Federal Energy Regulatory Commission Order 2222 over the next few years.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

EXERGETIC: De-Risking Next-Generation Resilient Geothermal Hybrids via At-Scale Evaluation Using Virtual Emulation Digital Twin Environment for Efficient Operation

The DOE-GTO-funded project, award number 5.1.2.12, entitled "EXERGETIC - De-risking Next Generation Resilient Geothermal Hybrids via at-Scale Evaluation Using a Virtual Emulation Digital Twin Environment for Efficient Operation," advances the solution to these challenges by developing and validating a geothermal co-emulation environment implemented at the National Laboratory of the Rockies (NLR)'s Advanced Research on Integrated Energy Systems (ARIES) platform. This framework enables the de-risking of next-generation geothermal and geothermal hybrid systems through high-fidelity modeling, real-time digital emulation, advanced control strategies, and techno-economic assessment. The project focused on geothermal hybrid configurations that integrate geothermal power plants with concentrated solar power and underground thermal energy storage, enabling enhanced efficiency, flexibility, and grid support capabilities. The main goal of this project was the development of a geothermal digital co-emulation environment to demonstrate the technical and economic value of geothermal hybrid systems and their contribution to grid stability and flexibility. The EXERGETIC framework combined physics-based models, controls, and real assets at ARIES, including digital real-time simulators (DRTS), a 20-MW-scale controllable grid interface (CGI), and a 2-MW conventional generator. Detailed transient models were developed for the key subsystems of a hybrid geothermal plant, including parabolic trough solar collectors, reservoir thermal energy storage (RTES), and a binary Organic Rankine Cycle (ORC) power plant. The ORC model explicitly captured thermal inertia and off-design operation and integrated control strategies to dynamically respond to electric load profiles. The models were validated against published experimental and numerical studies, demonstrating strong agreement and confirming the accuracy and robustness of the modeling approach. The resulting digital twin represents geothermal-solar-storage systems at multiple scales (1 MW to 100 MW) and enables realistic emulation of grid-connected operation. The control architecture allows the geothermal resource to provide stable baseload generation, while solar and stored thermal energy supply flexible, dispatchable support during periods of high demand or variable grid conditions. A key contribution of the EXERGETIC project is the demonstration that geothermal hybrid systems can be designed to be active grid assets rather than passive baseload generators. Using the ARIES platform, the digital twin was evaluated under multiple grid scenarios, including load following, voltage support at the distribution level, and frequency response at the transmission level. Results show that hybrid geothermal systems can respond effectively to dynamic grid conditions, providing inertia-like behavior, primary frequency support, and voltage regulation through coordinated control. In addition to the performance and grid services capability analysis of geothermal and hybrid geothermal systems, the EXERGETIC project also focused on scalability and techno-economic analysis of geothermal hybrid plants. In particular, for the scalability analysis, machine-learning (ML)-based surrogate models were trained using data generated from the geothermal digital twin under different grid-connected scenarios and plant capacities. These ML models demonstrated strong interpolation and extrapolation capabilities across plant sizes, accurately reproducing both steady-state and transient responses with very low errors. Regarding the techno-economic analysis, plant performance results were integrated with cost models for hybrid geothermal systems, and the levelized cost of electricity (LCOE) was used as the main economic metric to evaluate system performance across a range of system capacities, solar shares, solar multiples, and storage durations. Results indicate that economies of scale significantly reduce geothermal LCOE as plant capacity increases, with large-scale systems (25-100 MW) achieving substantially lower costs than small plants. Hybridization with solar thermal energy and storage further improves economic performance by increasing capacity utilization and enabling flexible dispatch. In addition, thermal storage plays a critical role in reducing LCOE by maximizing geothermal, solar, and stored energy resources. In summary, the results from this project demonstrate that geothermal hybrid systems represent a promising alternative for increasing the energy conversion efficiency of geothermal technologies, contributing to the preservation of geothermal resources, and supporting the transition of geothermal plants from traditional baseload resources into flexible, resilient, and cost-competitive energy conversion technologies.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Hybrid Simulation Framework

HYBRID is a modeling toolset to assess the economic viability of Nuclear-Renewable Integrated Energy Systems (N-R IES). The frameworks enabling this toolset are INL’s RAVEN, its CashFlow plugin and the Modelica language. The toolset includes sample RAVEN workflows performing economic assessments. These workflows consist of: generation of stochastic time series and application of probabilistic analysis and optimization algorithms (RAVEN); a library of Modelica models representing the physical behavior of N-R IES; and the CashFlow plugin mapping physical performance to economic performance. The toolset allows assembling existing and new models such as nuclear reactors, renewable energy sources, energy storage, gas turbines, industrial processes, etc. into an N-R IES. The toolset workflows evaluate the dynamics of the N-R IES responding to stochastic conditions (electricity demand, price, etc.) and optimize the dispatch economics as well as N-R IES capacity planning.

Epiney, Aaron↗
DOE OSTI2022

Water and Climate Impacts on ERCOT Long-Term Systems Assessment

Water and climate change pose many potential challenges to the electric power system. Substantial water is withdrawn every day to support thermoelectric power generating unit operations, and changes to water supply have the potential to affect generation dispatch. Climate change can accelerate growing demand for electricity, which can necessitate additional generating capacity, often in locations with limited water supply. Drought conditions also threaten thermoelectric power plant operations due to streamflow and reservoir levels dropping below intake structures, or water temperatures exceeding a power plants' permitted operating conditions. Here we explore how future climate change might influence decisions related to electricity capacity expansion planning in Electric Reliability Council of Texas (ERCOT) using a multi-model framework. Specifically, water resource modeling is used to simulate climate impacts on the future water supply for thermoelectric and hydropower generation for four future climate projections. Separately, temperature impacts on electricity load are evaluated for these scenarios. These climate impacts are applied to five alternative electricity futures in an electricity capacity expansion model that projects future generation and transmission capacity additions in ERCOT. Results indicate that climate has a measurable influence on future generation and transmission capacity needs, with temperature-driven increases in peak and average load resulting in 5-15 GW additional generating capacity and up to 1 GW additional transmission capacity. Additional capacity is a diverse mix of PV, natural gas, and wind, depending on the makeup of economic, policy and technology assumptions. Climate impacts increase total system costs 2-5%, while the marginal cost of energy and emissions are not affected substantially by climate change effects.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗