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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 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Analysis of Energy Justice and Equity Impacts from Replacing Peaker Plants with Energy Storage

Transitions to low-carbon energy systems are essential to mitigating and adapting to climate change. Energy storage systems are a key component in achieving a viable decarbonized electric grid. However, decarbonization alone does not guarantee a fairer, more inclusive, or socially just energy system. Energy equity and justice should be integrated in energy system transitions to ensure benefits and burdens are shared equitably. In this paper, we discuss the relationship between energy storage and social equity by assessing the use of energy storage to replace natural gas-fired (NG) peaker plants. Peaker plants are disproportionately located near disadvantaged communities and tend to be older and high emitters of health-affecting fine particulate matter and other pollutants. This paper investigates the equity implications of NG peaker plant replacements with battery energy storage in the context of Washington State’s peaker plants to highlight the human-centered values of retiring the plants. The study performed production cost simulations using the latest Western Electric Coordinating Council Anchor Dataset 2030 case and found that total generation cost, locational marginal price, and total annual emissions were reduced with the replacements. These reductions will have equity benefits on local communities including access to clean air, enhanced health outcomes, and energy burden reductions.

Tarekegne, Bethel W.↗
DOE OSTI2024

2022 Component Innovation Awardee: Pecos Wind Power

Distributed wind energy systems supply electricity for nearby homes and businesses, often in remote and rural regions. Systems capable of capturing energy in areas with low wind speeds make it possible to deploy these clean energy systems in many geographic locations. Pecos Wind Power's 85-kilowatt (kW) horizontal-axis PW85 wind turbine shows potential to reduce the levelized cost of energy by approximately 55% when compared to typical small wind systems while achieving utility-scale capacity factors of more than 40% in areas with lower wind speeds. To maximize cost competitiveness, the Pecos Wind Power turbine needs a blade optimized for low wind speeds. Through its 2022 Competitiveness Improvement Project (CIP) award, Pecos Wind Power and partner Wetzel Wind Energy Services will model, optimize, fabricate, and validate a 14.5-meter wind turbine blade made specifically for these applications. Three prior CIP awards supported Pecos Wind Power's initial development of the PW85 turbine.

CIP↗
NASA NTRS1980

Cost projections for Redox Energy storage systems

A preliminary design and system cost analysis was performed for the redox energy storage system. A conceptual design and cost estimate was prepared for each of two energy applications: (1) electric utility 100-MWh requirement (10-MW for ten hours) for energy storage for utility load leveling application, and (2) a 500-kWh requirement (10-kW for 50 hours) for use with a variety of residential or commercial applications, including stand alone solar photovoltaic systems. The conceptual designs were based on cell performance levels, system design parameters, and special material costs. These data were combined with estimated thermodynamic and hydraulic analysis to provide preliminary system designs. Results indicate that the redox cell stack to be amenable to mass production techniques with a relatively low material cost.

Michaels, K.↗
DOE OSTI2025

Optimal sizing of battery energy storage systems for peak shaving and demand response using a degradation-aware Bayesian Optimization-Mixed-Integer Linear Programming framework

The increasing integration of renewable energy and rising electricity demand highlight the importance of battery energy storage systems for peak shaving and demand response. Unlike prior approaches that overlook operational impacts on degradation, this study proposes a Bayesian Optimization–Mixed Integer Linear Programming framework for optimal battery energy storage system sizing. In this framework, Mixed Integer Linear Programming determines short-term scheduling while a calibrated electrochemical model iteratively evaluates degradation. The central hypothesis is that the framework can efficiently identify optimal sizes that yield realistic and economically robust outcomes. The method is tested across three scenarios: peak shaving, peak shaving with energy-reduction demand response, and peak shaving with power-reduction demand response. Results show that the framework converge to the optimum within 20 iterations out of 150 possible sizes. Under baseline conditions, the framework consistently selects the smallest feasible system, minimizing unnecessary degradation costs from oversized storage. Sensitivity analyses reveal that larger systems are favored as demand rates or incentives increase. Comparisons of demand response programs indicate that power-reduction demand response offers greater economic benefits than energy-reduction demand response, although demand savings from peak shaving remain the dominant contributor to overall performance. This study demonstrates that the proposed framework balances computational tractability with degradation fidelity, identifies critical economic thresholds for investment, and offers a practical, flexible tool to guide industrial stakeholders in cost-effective battery energy storage system deployment.

Batteries↗
DOE OSTI2026

X-ray observation of individual Ti-6Al-4V spherical powder particle impact in an in-situ operando laser directed energy deposition system

Understanding the particle capture mechanism in the laser directed energy deposition additive manufacturing process provides a foundation for improving productivity and reducing material loss. Capturing this phenomenon is challenging due to its highly transient time interval. To analyze the impact behavior of spherical Ti-6Al-4V powder, a custom laser directed energy deposition system was designed to control the deposition of individual particles. Synchrotron X-ray imaging at 24 kHz monitored the impact dynamics of individual powder particles. A multi-physics model based on the Smoothed-Particle Hydrodynamics scheme supported the analysis by providing the temperature and velocity fields of the molten pool. Results revealed that in laser directed energy deposition, surface tension forces dominated the powder–molten pool interaction. Hydrophobic Ti-6Al-4V powder particles had an equilibrium contact angle of 121 degrees with their molten state. Furthermore, Ti-6Al-4V powder particles required a high impact velocity (6 to 12 m/s) to transition from oscillation to submergence behavior. Lastly, oscillating powder particles that impacted near the location of the laser beam exhibited faster melting, highlighting the contribution of the laser beam to the melting mechanism. This work lays the foundation for investigations of powder particle impact in laser directed deposition and supports the validation of numerical models of powder–molten pool interactions.

36 MATERIALS SCIENCE↗
NASA NTRS1975

Considerations for performance evaluation of solar heating and cooling systems

One of the many factors which must be considered in performance evaluation of solar energy systems is the relative merit of a given solar energy system when compared to a standard conventional system. Although initial and operational costs will be dominant factors in the comparison of the two types of systems and will be given prime consideration in system selection, sufficient data are not yet available for a definitive treatment of these variables. It is possible, however, to formulate relationships between the nonsolar energy requirements of the solar energy systems and the energy requirements of a conventional system in terms of the primary performance parameters of the systems. Derivations of such relationships, some parametric data for selected ranges of the performance parameters, and data with respect to limiting conditions are presented.

Littles, J. W.↗
DOE OSTI2020

A Comprehensive System of Energy Intensity Indicators for the U.S.: Methods, Data and Key Trends

This report describes a comprehensive system of energy intensity indicators for the United States that has been developed for the Department of Energy’s Office of Energy Efficiency and Renewable Energy (EERE) over the past decade. This system of indicators is hierarchical in nature, beginning with detailed indexes of energy intensity for various sectors of the economy, which are ultimately aggregated to an overall energy intensity index for the economy as a whole. The aggregation of energy intensity indexes to higher levels in the hierarchy is performed with a version of the Log Mean Divisia index (LMDI) method. Based upon the data and methods in the system of indicators, the economy-wide energy intensity index shows a decline of about 16% in 2014 relative to a 1985 base year. Discussion of energy intensity indicators for each of the broad end-use sectors of the economy—residential, commercial, industrial, and transportation—is presented in the report. An analysis of recent changes in the efficiency of electricity generation in the U.S. is also included. A detailed appendix describes the data sources and methodology behind the energy intensity indicators for each sector.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

A Comprehensive System of Energy Intensity Indicators for the U.S.: Methods, Data and Key Trends

This report describes a comprehensive system of energy intensity indicators for the United States that has been developed for the Department of Energy’s Office of Energy Efficiency and Renewable Energy (EERE) over the past decade. This system of indicators is hierarchical in nature, beginning with detailed indexes of energy intensity for various sectors of the economy, which are ultimately aggregated to an overall energy intensity index for the economy as a whole. The aggregation of energy intensity indexes to higher levels in the hierarchy is performed with a version of the Log Mean Divisia index (LMDI) method. Based upon the data and methods in the system of indicators, the economy-wide energy intensity index shows a decline of about 16% in 2014 relative to a 1985 base year. Discussion of energy intensity indicators for each of the broad end-use sectors of the economy—residential, commercial, industrial, and transportation—is presented in the report. An analysis of recent changes in the efficiency of electricity generation in the U.S. is also included. A detailed appendix describes the data sources and methodology behind the energy intensity indicators for each sector.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Leadership and Community Engagement in Chile: Deploying Net-Zero Technologies and Solutions

The report presents the 2023 Net Zero World Chile program results from activities of the the four program workstreams: 1) energy-system wide modeling LEAP modeling and analysis results including accelerated Net Zero scenarios with aggressive energy efficiency improvements, fuel switching, and electrification across demand sector; 2) district energy chapter provides thermal district energy systems modeling results of the Recoleta-Independencia pilot project and comparative analysis of district energy systems' potential versus competing technologies in Chile; 3) just transition action steps for the creation of a sister city relationship between Tocopilla and a US counterpart city; and 4) power decarbonization capacity building activities focused on the selection and adoption of grid-enhancing technologies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Optimal Power Management of Battery Energy Storage Systems via Ensemble Kalman Inversion

Optimal power management of battery energy storage systems (BESS) is crucial for their safe and efficient operation. Numerical optimization techniques are frequently utilized to solve the optimal power management problems. However, these techniques often fall short of delivering real-time solutions for large-scale BESS due to their computational complexity. To address this issue, this paper proposes a computationally efficient approach. We introduce a new set of decision variables called power-sharing ratios corresponding to each cell, indicating their allocated power share from the output power demand. We then formulate an optimal power management problem to minimize the system-wide power losses while ensuring compliance with safety, balancing, and power supply-demand match constraints. To efficiently solve this problem, a parametrized control policy is designed and leveraged to transform the optimal power management problem into a parameter estimation problem. We then implement the ensemble Kalman inversion to estimate the optimal parameter set. The proposed approach significantly reduces computational requirements due to 1) the much lower dimensionality of the decision parameters and 2) the estimation treatment of the optimal power management problem. Finally, we conduct extensive simulations to validate the effectiveness of the proposed approach. The results show promise in accuracy and computation time compared with explored numerical optimization techniques.

Farakhor, Amir↗
NASA NTRS1985

Assessing Energy-Generating Systems

Economics of user specified thermal and electrical systems analyzed. OMEGA finds normative prices and break-even values of system parameters. Applies to electrical and thermal energy generation systems owned by utility, business or consumer.

Chamberlain, R. G.↗
NASA NTRS1991

Final prototype of magnetically suspended flywheel energy storage system

A prototype of a 500 Wh magnetically suspended flywheel energy storage system was designed, built, and tested. The authors present the work done and include the following: (1) a final design of the magnetic bearing, control system, and motor/generator, (2) construction of a prototype system consisting of the magnetic bearing stack, flywheel, motor, container, and display module, and (3) experimental results for the magnetic bearings, motor, and the entire system. The successful completion of the prototype system has achieved: (1) manufacture of tight tolerance bearings, (2) stability and spin above the first critical frequency, (3) use of inside sensors to eliminate runout problems, and (4) integration of the motor and magnetic bearings.

Anand, D. K.↗
DOE OSTI2024

Introduction to Engage: NASA Training Session

Welcome to Engage! Engage is a capacity expansion modeling tool supported by the National Renewable Energy Laboratory and based on the Calliope open-source capacity expansion model developed by the ETH Zurich University, maintained at the TU Delft University. Engage is an accessible (free, open-access, web-hosted) and flexible web-based energy system planning application for rapid multiple-energy-form energy system scenario exploration. Its cloud-based, collaborator-sharable data model, intuitive interface and visualization capabilities facilitate collaboration and communication among teams, with experts, and among diverse stakeholder groups exploring energy system implications from district to national-scale models. This training session was presented to the National Aeronautics and Space Administration (NASA) to help them understand how capacity expansion modeling can help them develop single site/distribution analysis of energy to regional airports.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

NREL is Delivering Integrated Solutions for an Affordable and Secure Energy Future

The National Renewable Energy Laboratory (NREL) is the U.S. Department of Energy's primary national laboratory for energy systems research and development. As the energy systems laboratory, NREL's unique strength lies in developing and integrating a broad array of energy technologies into robust, resilient systems - bridging foundational research with practical applications to lower energy costs, drive economic growth, bolster national security, and deliver abundant and reliable energy.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Best Practices for Plug Load Management Using a Building Energy Management System

The University of California San Diego (UCSD) successfully integrated PLCs with their BEMS, which resulted in 66% energy savings over one week across 25 plug loads (K. Chia et al. 2023). UCSD documented each step of this effort, highlighting best practices along the way, in their 10-page brief, "Best Practices for Plug Load Management Using a Building Energy Management System" (also referred to as "brief" in this document). This fact sheet provides highlights and key takeaways from UCSD's brief. The reader is encouraged to read UCSD's full brief if they wish to move forward with implementing PLC integration with their BEMS.

Building Energy Management System Integration↗
DOE OSTI2020

Stochastic Home Energy Management Systems with Varying Controllable Resources

This paper studies the performance of a model predictive control (MPC) algorithm in a home energy management system (HEMS) as the set of controllable resources varies and under both a constant and a time-of-use (TOU) electricity price structure. The set of controllable resources includes residentially-owned photovoltaic (PV) panels, a home battery system (HBS), an electric vehicle (EV), and a home heating, ventilation, and air conditioning (HVAC) system. The HEMS optimally schedules the set of controllable resources given user preferences such as indoor thermal comfort and electricity cost sensitivity. The home energy management system is built on a chance constrained, MPC-based algorithm, where the chance constraint ensures the indoor thermal comfort is satisfied with a high probability given uncertainty in the outdoor temperature and solar irradiance forecasts. Simulation results for varying sets of controllable resources under two different electricity price structures demonstrate the variation in the HEMS control with respect to HBS operation, electricity cost, and grid power usage.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗