SEARCH · Engineering Papers

Results for “grid storage”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,459 records · Page 81

All sources NASA NTRS DOE OSTI

DOE OSTI2024

Underground hydrogen storage resource assessment for the Cook Inlet, Alaska

Underground hydrogen storage will be essential to a hydrogen economy. This work focuses on the challenge of identifying and screening candidate storage systems, given the unique behavior of hydrogen in the subsurface. Here, we describe a resource assessment methodology and apply it to Alaska’s Cook Inlet region. Alaska provides an interesting case study because of its abundant renewable energy resources, relatively low energy demand, and isolated electrical grid. The assessment framework considers each site’s ability to (1) store a specific volume, (2) physically-contain the stored gas, and (3) limit biogeochemical activity. We estimate that reservoirs in the Cook Inlet area could theoretically store a total of 286 TWh (or 8.6 million tonnes [Mt]) in hydrogen working gas in 92 pools. This is likely sufficient to meet both local hydrogen demand and support an array of exportable products. We further identify seven pools that may be especially well-suited for hydrogen storage. Broadly, this work demonstrates a framework for regional resource assessments. On a finer scale, this work supports an early demonstration of porous–media hydrogen storage in the United States.

08 HYDROGEN↗

DOE OSTI2025

Behind-the-Meter Energy Storage and Generation in Support of Electrified Rental Car Centers

Electrification of rental car centers at major airports is expected to generate tens of MW in additional power loads. The magnitude of these loads poses challenges including high utility costs, expensive and lengthy distribution capacity upgrades, and disruptions to traditional operation. Behind-the-meter stationary battery storage and onsite photovoltaic generation offer a viable solution to these challenges without impacting the operation and business model of rental car companies, defined by minimal fleet inventory and short vehicle dwell time. Using data-driven syn-thetic charging loads for the rental car center at the Dallas/Fort Worth airport in the United States, we show that optimally-designed and controlled behind - the- meter resources can reduce the lifecycle cost of electrified rental centers by an average 41 % and reduce peak grid demand by 64 %, deferring the need for distribution upgrades or potentially avoiding it altogether.

battery storage↗

DOE OSTI2025

Load-Shifting Strategies for Cost-Effective Emission Reductions at Wastewater Facilities

Significant hourly variation in the carbon intensity of electricity supplied to wastewater facilities introduces an opportunity to lower emissions by shifting the timing of their energy demand. This shift could be accomplished by storing wastewater, biogas from sludge digestion, or electricity from on-site biogas generation. However, the life cycle emissions and cost implications of these options are not clear. Here, we present a multiobjective optimization framework for comparing cost- and emission-minimizing load-shifting strategies at a California case study facility with a relatively low carbon intensity grid and high spread in peak and off-peak electricity prices. We evaluate cost and emission trade-offs from the optimal flexible operation of both existing infrastructure and optimally sized energy flexibility upgrades. We estimate energy-related emission reductions of up to 9.0% with flexible operation of existing infrastructure and up to 16.8% with optimally sized storage upgrades. Only a fraction of these potential savings are realized under actual industrial energy tariffs and the EPA’s recommended social cost of carbon. Energy flexibility may hold promise as a short-term emission-saving solution for the wastewater sector, but the extent of savings is heavily dependent on the cost of carbon, electricity tariffs, and emission intensity of the regional electricity grid.

climate↗

DOE OSTI2024

NPD Hydro

This tool, the Non-Powered Dam Hydropower Development and Ranking Opportunity Tool (NPD HYDRO), allows users to prioritize or rank NPD sites for future development based on user-defined priorities. Benefits can be evaluated in several categories: the grid, community, industry, and environment (represented by the GCIE impact scores in the tool. In addition, the tool provides the user with a qualitative measure for the feasibility of adding energy storage during NPD conversion, specifically battery, hydrogen electrolysis, and pumped-storage hydropower (PSH). By taking a holistic approach to the potential range of benefits provided by NPD conversions with results tailored to the user’s priorities, NPD HYDRO provides the opportunity for national-level screening and enables users to focus on the sites that are most closely aligned with their interests.

Woodruff, Nathan↗

NASA NTRS1983

The treatment of convected vortices in compressible potential flow

A method is described for incorporating line vortices into the three dimensional compressible potential flow equation. A modified Biot-Savart law is used to compute a vortical velocity field, which is added to the gradient of the potential to form a total velocity. A rapidly converging approximate factorization (AFZ) scheme is then used to compute a potential such that the modified potential flow equation as well as the appropriate boundary conditions, based on total velocity, are satisfied. As part of a coupled iteration procedure, the positions of the line vortices are computed so that they convect with the total flow. The method is used to compute the field due to a single line vortex convecting past a wing. This represents an approximation of the effect of a canard or other lifting surface ahead of the wing, which sheds a tip vortex. It is seen that the flow field is substantially modified by the passage of the vortex. Unlike Euler equation schemes, which are also used to compute these flows, the solutions exhibit no numerical diffusion: The convected vortices retain their initial upstream width. Euler solutions, on the other hand, involve a vorticity which is numerically convected in an Eulerian frame and, unless extensive adaptive grid refinement is used they result in vortices with spread as they convect. Also, the potential flow method requires approximately two orders of magnitude less computing time and much less computer storage than the Euler methods.

Steinhoff, J.↗

NASA NTRS1984

Multigrid applications to three-dimensional elliptic coordinate generation

The multigrid algorithm was applied to solve the coupled set of elliptic quasilinear partial differential equations associated with three-dimensional coordinate generation. The results indicate that the multigrid scheme is more than twice as fast as conventional relaxation schemes on moderate-size grids. Convergence factors of order 0.90 per work unit were achieved on 36,000-point grids. The paper covers the form of transformation, develops the set of generation equations, and gives details on the multigrid approach used. Included are a development of the full-approximation storage scheme, details of the smoothing-rate analysis, and a section devoted to rational programming techniques applicable to the multigrid algorithm.

Thames, F. C.↗

NASA NTRS1993

Application of the multigrid solution technique to hypersonic entry vehicles

A multigrid solution procedure has been incorporated in a version of the Langley Aerothermodynamic Upwind Relaxation Algorithm. The multigrid scheme is based on the Full Approximation Storage approach and uses Full Multigrid to obtain a well defined fine mesh starting solution. Predictions were obtained using standard transfer operators and a 'V-cycle' was used to control grid sequencing. Computed hypersonic flow solutions compared with experimental data for a 15 degree sphere cone, blended-wing body, and shuttle-like geometries are presented. It is shown that the algorithm accurately predicts heating rates, and when compared with the single grid algorithm computes solutions in one-third the computational time.

Greene, Francis A.↗

NASA NTRS2017

Use of Schema on Read in Earth Science Data Archives

Traditionally, NASA Earth Science data archives have file-based storage using proprietary data file formats, such as HDF and HDF-EOS, which are optimized to support fast and efficient storage of spaceborne and model data as they are generated. The use of file-based storage essentially imposes an indexing strategy based on data dimensions. In most cases, NASA Earth Science data uses time as the primary index, leading to poor performance in accessing data in spatial dimensions. For example, producing a time series for a single spatial grid cell involves accessing a large number of data files. With exponential growth in data volume due to the ever-increasing spatial and temporal resolution of the data, using file-based archives poses significant performance and cost barriers to data discovery and access. Storing and disseminating data in proprietary data formats imposes an additional access barrier for users outside the mainstream research community. At the NASA Goddard Earth Sciences Data Information Services Center (GES DISC), we have evaluated applying the schema-on-read principle to data access and distribution. We used Apache Parquet to store geospatial data, and have exposed data through Amazon Web Services (AWS) Athena, AWS Simple Storage Service (S3), and Apache Spark. Using the schema-on-read approach allows customization of indexing spatially or temporally to suit the data access pattern. The storage of data in open formats such as Apache Parquet has widespread support in popular programming languages. A wide range of solutions for handling big data lowers the access barrier for all users. This presentation will discuss formats used for data storage, frameworks with This presentation will discuss formats used for data storage, frameworks with support for schema-on-read used for data access, and common use cases covering data usage patterns seen in a geospatial data archive.

cloud applications↗

DOE OSTI2024

Coupling thermal energy storage with a thermally anisotropic building envelope for building demand-side management across various US climate conditions

Here, the thermally anisotropic building envelope (TABE) is a novel active building envelope that enhances energy efficiency and thermal comfort in buildings by transferring heat and cold between building envelopes and hydronic loops. When coupled with thermal energy storage (TES) units, the TABE + TES enables the storage of both heat and cold energy captured by the TABE roof or exterior walls. This stored energy can be later released by the TABE floor for indoor heating and cooling, benefiting both the grid and the end user. This paper evaluates the merits of TABE + TES for building demand-side management across various US climate conditions, focusing on peak load shaving, annual energy savings, and cost savings under time-of-use (TOU) electric rate schedules. Simulations were conducted by integrating time-of-day–informed, rule-based control strategies in MATLAB, TABE components and TES units in COMSOL Multiphysics, and whole-building energy analysis in EnergyPlus. A case study using the US Department of Energy’s prototype single-family detached house model in Birmingham, Alabama; Los Angeles, California; Oak Ridge, Tennessee; and Denver, Colorado, showed that the TABE + TES system achieved (1) 70 % peak load shaving in Los Angeles and Denver and 20 % in Birmingham and Oak Ridge; (2) significant peak electricity savings of 351–497 kWh, reducing peak energy consumption by 38 %–78 %; and (3) annual heating cost savings of 0.79 $\$$/m2–1.17 $\$$/m 2 and cooling cost savings of 0.60 $\$$/m 2 –1.17 $\$$/m 2 using a normal utility rate or low-TOU rate. The benefits of employing the TABE + TES system are even more significant under high TOU rates.

25 ENERGY STORAGE↗

DOE OSTI2022

Hydrogen 101: Frequently Asked Questions About Hydrogen for Decarbonization

Hydrogen is emerging across the world as a potential low-carbon energy carrier that can provide an alternative to fossil fuels. With the increasing deployment of renewable energy, the role of low-carbon power generation in hydrogen production through electrolysis is expected to increase. Hydrogen can also play a role in reducing carbon emissions in several strategic sectors such as chemicals, iron, steel, and long-haul transport like heavy-duty trucks and shipping. As a result of these possibilities, many countries have included hydrogen as a central part of their energy strategies. This growing interest has led to many questions among various stakeholders, including policymakers, planners, regulators, system operators, utilities, and investors. This fact sheet provides answers to some of the most frequently asked questions related to hydrogen production, transportation, storage, cross-sectoral utilization, and its role in power sector decarbonization.

08 HYDROGEN↗

DOE OSTI2022

Liquid Crystal‐Based Detection of Antigens with ELISA Sensitivity

Abstract A highly sensitive label‐free liquid crystal (LC)‐based technique is presented for detecting Immunoglobulin G (IgG) antigens used to uncover viral infections. The effectiveness, sensitivity, and selectivity of this detection method is demonstrated with goat IgG antigen at concentrations as low as 100 pg ml −1 , which is comparable to the sensitivity of the current enzyme‐linked immunosorbent assay (ELISA). The sensor is fabricated by decorating a transmission electron microscopy grid immobilized glass surfaces with antibodies; the target antigen is detected by a liquid crystal suspended onto the grid. This is different from previous methods where the antigen is detected either at the LC‐aqueous interface or in an LC sandwich cell with an antibody/antigen‐decorated substrate. This new approach has advantages such as easy sample preparation, higher sensitivity, and better storage capabilities. Binding the target antigen to the antibody results in a reorientation of the LC director that is detected optically. In addition to demonstrating the sensitivity, the physical principle of the detection is also discussed. This technique may apply to detect virtually any antigen of interest.

36 MATERIALS SCIENCE↗

DOE OSTI2022

The impact of energy-efficiency upgrades and other distributed energy resources on a residential neighborhood-scale electrification retrofit

We report ambitious targets for carbon emissions reductions are highlighting new challenges for electrification strategies, leading to an increased focus on building load flexibility and energy management to complement the variability inherent in renewable energy generation. Over the next decade millions of existing homes could undergo electrification retrofits, and there is an urgent need to understand the potential impacts of electrifying major residential loads such as water and space heating on community load characteristics, resident energy bills, and the utility's distribution system. Behind-the-meter distributed energy resources (DERs), including efficiency measures, photovoltaics (PV), battery storage, managed electric vehicle (EV) charging, and controls such as home energy management systems (HEMS), can significantly alter a neighborhood's load profile and provide benefits to both the residents and the grid. We present a novel approach to characterizing the impact of a hypothetical neighborhood-scale residential retrofit program on individual homes' energy use profiles, associated utility bills, and the local distribution system. We modeled a mixed-fuel community of 30 single-family homes in Denver, Colorado, and compared the effects of retrofit scenarios ranging from conventional energy-efficiency upgrades to full electrification with and without more advanced DER technologies. We analyzed which packages of DERs most reliably enable demand flexibility in response to a time-of-use (TOU) rate for this and similar neighborhoods. Our buildings-to-grid co-simulation framework includes a generic secondary distribution feeder model to capture voltage profiles, transformer loading, and other grid impacts in each case. We also calculated the carbon emissions associated with energy use in the community. The methodology developed here can be broadly applied to community-scale beneficial electrification studies in other regions, climates, utility infrastructures, and building typologies to make specific, targeted recommendations based on quantified projections of energy demand in any given community. Our findings indicate that residential electrification can be achieved without negatively impacting the monthly utility bill, and that a combination of conventional energy-efficiency measures, PV, battery, controls, and managed EV charging to maximize a community's demand flexibility is a promising strategy. Adding DERs (especially PV) as part of efficient electrification produces much bigger savings than efficient electrification without DERs. A key barrier is that upgrades require upfront costs, and modest utility bill savings result in long payback periods.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Comprehensive assessment of deep reinforcement learning approaches for economic dispatch in nuclear-driven microgrids

As the electrical grid integrates more variable renewable energy sources such as wind and solar, the demand for distributed and flexible systems to address this increased variability becomes critical. Nuclear-driven microgrids provide a promising solution by offering stable generation to complement intermittent renewables, ensuring grid reliability and operating efficiency. This paper proposes a recurrent deep reinforcement learning framework for optimal economic dispatch in a nuclear-powered microgrid integrating renewable energy sources, small modular reactors, battery storage systems, and balance-of-plant dynamics. A three-agent control architecture is developed, where demand and renewable energy agents act as forecasters, and a reinforcement learning-based dispatch agent performs real-time energy allocation. A nonlinear programming formulation is first used to generate an optimal baseline for benchmarking. The proposed dispatch controller, based on Proximal Policy Optimization enhanced with Long Short-Term Memory networks, exploits temporal correlations in system dynamics by taking advantage of the time series used as inputs to improve policy robustness under uncertainty. Comparative analysis against established deep reinforcement learning methods, including Proximal Policy Optimization with a feedforward architecture, Soft Actor-Critic, and Twin Delayed Deep Deterministic Policy Gradient, demonstrates superior performance. Numerical results indicate that the proposed controller achieves a 0.39% cost reduction relative to the nonlinear programming benchmark and outperforms other learning-based methods by generating additional revenue of up to 0.35%. All reinforcement learning controllers compute dispatch actions in less than 0.3 s, resulting in a computational speedup of more than three orders of magnitude over the nonlinear programming baseline. The findings of this paper highlight their applicability for real-time operation and control in nuclear-integrated microgrids under volatile operating conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Net-zero CO 2 by 2050 scenarios for the United States in the Energy Modeling Forum 37 study

The Energy Modeling Forum (EMF) 37 study on deep decarbonization and high electrification analyzed a set of scenarios that achieve economy-wide net-zero carbon dioxide (CO 2 ) emissions in North America by mid-century, exploring the implications of different technology evolutions, policies, and behavioral assumptions affecting energy supply and demand. Here, for this paper, 16 modeling teams reported resulting emissions projections, energy system evolution, and economic activity. This paper provides an overview of the study, documents the scenario design, provides a roadmap for complementary forthcoming papers from this study, and offers an initial summary and comparison of results for net-zero CO 2 by 2050 scenarios in the United States. We compare various outcomes across models and scenarios, such as emissions, energy use, fuel mix evolution, and technology adoption. Despite disparate model structure and sources for input assumptions, there is broad agreement in energy system trends across models towards deep decarbonization of the electricity sector coupled with increased end-use electrification of buildings, transportation, and to a lesser extent industry. All models deploy negative emissions technologies (e.g., direct air capture and bioenergy with carbon capture and storage) in addition to land sinks to achieve net-zero CO 2 emissions. Important differences emerged in the results, showing divergent pathways among end-use sectors with deep electrification and grid decarbonization as necessary but not sufficient conditions to achieve net zero. These differences will be explored in the papers complementing this study to inform efforts to reach net-zero emissions and future research needs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

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 OSTI2025

Distribution System Blackstart and Restoration Using DERs and Dynamically Formed Microgrids

Extreme weather events have led to long-duration outages in the distribution system (DS), necessitating novel approaches to blackstart and restore the system. Existing blackstart solutions utilize blackstart units to establish multiple microgrids (MGs), sequentially energize non-blackstart units, and restore loads. However, these approaches often result in isolated MGs. In DERs-aided blackstart, the continuous operation of these MGs is limited by the finite energy capacity of commonly used blackstart units like battery energy storage (BES)-based gridforming inverters (GFMIs). To address this issue, this article proposes a holistic blackstart and restoration framework that incorporates synchronization between dynamic MGs and the entire DS with the transmission grid (TG). To support synchronization, we leveraged virtual synchronous generator-based control for GFMIs to estimate their frequency response to load pick-up events using only initial/final quasi-steady-state points. Subsequently, a synchronization switching condition is developed to model synchronizing switches, aligning them seamlessly with a linearized branch flow problem. Finally, we designed a bottomup blackstart and restoration framework that considers the switching structure of the DS, energizing/synchronizing switches, DERs with grid-following inverters, and BES-based GFMIs with frequency security constraints. In conclusion, the proposed framework is validated in IEEE-123-bus system, considering cases with two and four GFMIs under various TG recovery instants.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Considerations for Developing a Regulatory Roadmap for Distributed Energy Resource (DER) Integration in Colombia

The USAID-NREL Partnership in Colombia, in conjunction with SURE and USEA, selected four action plan teams from the Young Professionals Leadership Program to receive tailored NREL technical assistance to support action plan implementation. The four plans selected represent various aspects associated with planning for the efficient integration of DERs, including electric mobility, residential and commercial energy applications, distributed generation modeling, and regulatory considerations. In response to national grid modernization, decentralization, digitalization, and electrification trends, CREG is looking to update Colombia's electric distribution code, with an emphasis on the integration of electric vehicles and charging stations, but also energy storage systems, non-conventional sources of renewable energy, and other distributed energy resources (DERs). CREG aims to establish the general steps that must be carried out to update the distribution code for the integration of DERs, with a view to the design and development of new markets. The objective of the TA provided to CREG was to support them in identifying and outlining the general processes and approaches to consider when updating Colombia's distribution code for the integration of electric vehicles, distributed renewable energy systems, and energy storage systems, with a view to the design and development of new markets.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1992

The impact of global warming on river runoff

A global atmospheric model is used to calculate the annual river runoff for 33 of the world's major rivers for the present climate and for a doubled CO2 climate. The model has a horizontal resolution of 4 x 5 deg, but the runoff from each model grid box is quartered and added to the appropriate river drainage basin on a 2 x 2.5 deg resolution. The computed runoff depends on the model's precipitation, evapotranspiration, and soil moisture storage. For the doubled CO2 climate, the runoff increased for 25 of the 33 rivers, and in most cases the increases coincide with increased rainfall within the drainage basins. There were runoff increases in all rivers in high northern latitudes, with a maximum increase of 47 percent. At low latitudes there were both increases and decreases ranging from a 96 increase to a 43 percent decrease. The effect of the simplified model assumptions of land-atmosphere interactions on the results is discussed.

Miller, James R.↗