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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Evolving Competitive Markets in SAPP: Leveraging Competitive Wholesale Electricity Markets to Drive Renewable Generation Capacity in the Southern African Power Pool (SAPP)

The SADC region has significant natural resource potential to increase renewable energy generation, improve electricity reliability, and support economic development. This research finds an apparent lack of confidence from electricity infrastructure investors in SAPP wholesale electricity markets, which increases risk perception and lowers the likelihood of capital deployment. With respect to free market fundamentals, competitive market obstacles and renewable energy development obstacles are characterized. Stakeholders identified the top obstacles to well-functioning competitive markets as insufficient transmission infrastructure for interconnection and regional movement of electricity, dominance of national single-buyer markets, and lack of or weak nation-state regulatory frameworks. Stakeholders prioritized the top three obstacles for renewable energy development as a lack of viable commercial arrangements for variable renewable energy (VRE) balancing, lack of functional and consistent nation-level regulations, and higher project costs related to reliance on imported equipment. With respect to potential solution options, stakeholders prioritized the development of new cost allocation and finance methods to facilitate new transmission expansion, training to educate new or potential new market entrants on SAPP processes, as well as modeling and analysis of regional SAPP participation benefits disaggregated to the nation-state level. From these perspectives, this research identified strategy options for consideration including transitioning SAPP to a regional transmission operator (RTO) for operation and planning of cross-border transmission facilities and market administration, shifting operations of SAPP member transmission systems to Independent System Operators (ISOs), establishing a regional regulatory authority and enhancing market data transparency. Implementing these reforms is expected to be challenging, but not insurmountable, given the domestic political, legal, and jurisdictional complexities of the SADC region.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Hourly Load Profile Dataset for Electric Airport Ground Support Equipment in the United States

Currently, there are limited data on the magnitude and timing of electricity demand from electric ground support equipment (eGSE) across U.S. airports. To address this gap, this study presents a modeling approach for estimating hourly annual electricity demand from eGSE at the 50 largest U.S. commercial airports. These datasets, accessible at data.nrel.gov/submissions/279, provide critical insights into the potential grid impacts and electricity demand associated with eGSE adoption.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Design, Manufacturing, and Validation of an Optimized Electric Machine Enabled by 3D Printing

The collaboration between the National Laboratory of the Rockies (NLR) and LaunchPoint Electric Propulsion Solutions, Inc. (LaunchPoint) focuses on manufacturing and additive design of electric machines enabled by DOE’s program for three-dimensional printing (MADE3D) as applied to advanced drivetrains and their impact on turbine capital cost and lifetime energy production. Initial efforts will focus on the rotor structure and rotor core of the drivetrain including the active materials (electrical steel and magnets) and could later expand to the stator. The verification activities will be conducted with an instrumented electric machine and a small dynamometer.

17 WIND ENERGY↗
DOE OSTI2026

Power Lane County Electric Grid Handbook

In 2024, Lane Couty was selected to participate in the U.S. Department of Energy’s Energy to Community program. Through the program, National Laboratory researchers from Lawrence Berkeley National Laboratory, Pacific Northwest National Laboratory, and the National Laboratory of the Rockies provide three years of technical assistance to Lane County and their project partners: the Center for Rural Livelihoods, Springfield Utility Board, and Emerald People’s Utility District. The project, named Power Lane County, aims to improve local electric system affordability, reliability and resilience in the face of natural hazards and potentially rising loads. The Power Lane County Electric Grid Handbook establishes a foundational understanding of the energy landscape and electric grid in Lane County to inform community engagement, education, and analysis in future project phases. This document synthesizes public data and utility and stakeholder engagement, including utility interviews to give the reader a comprehensive view of the challenges facing Lane County's electric system and the opportunities to address them

Electricity↗
DOE OSTI2022

Energy Impacts of Electric Aircraft: An Overview

Commercial aviation represents approximately 2% of the global emissions of greenhouse gases, yet presently relies exclusively on fossil fuels as a source of energy. This paper evaluates to what extent an all-electric aircraft can provide an alternative. First, three classes of aircraft are modeled at various timelines in the future: 50/100/150 passenger capacity in 2030/2040/2050. Technology is assumed to improve over time, especially with regards to battery specific energy, resulting in aircraft with increased range. A database of all domestic flights in the US in 2019 is then used to filter and aggregate flights suited for replacement by electric aircraft. In the short term (2030), no viable aircraft can meet the requirements of each class. By 2040, a third of the flights can be done by an all-electric aircraft, but only short ones, as the range does not exceed 500 mi, resulting in 3% of total passenger-miles. By 2050, owing to the most optimistic technology assumptions, a quarter of all passenger-miles can be flown by electric airplanes. The resulting displaced jet fuel is also calculated.

Aviation sustainability↗
DOE OSTI2024

Negative Medium-Voltage Direct Current Discharges in Air under Simulated Sub-Atmospheric Pressures for All-Electric Aircraft

The increase in the global temperature due to greenhouse gas emissions is a major concern to the world. To achieve the goal of zero emissions by 2050 in the USA the practical realization of all-electric vehicles, particularly all-electric aircraft (AEA), is important. For the design of electrical power systems (EPSs) in all-electric aircraft, a bipolar medium-voltage direct current (MVDC) system of ±5 kV is being investigated. However, several challenges manifest when using such voltages in a low-pressure environment. One of the main challenges is the partial discharge (PD) behavior of the insulation. It is important to study the PD behavior of the insulation by simulating the aviation environment in the lab. This work aimed to study the partial discharge behavior of air under a negative DC voltage in a needle-to-plane electrode geometry by simulating the aviation pressures in the lab. The partial discharge inception voltage (PDIV) and the breakdown voltage (BDV) show an obvious pressure-dependent variation. Regression analysis was performed to better understand the relationship between the PDIV and pressures. Plots were drawn for the average discharge current at each voltage step until breakdown. This paper’s findings can provide valuable insight into the design of EPS for an AEA. To the best of our knowledge, such a study has not been carried out to date.

air discharge↗
DOE OSTI2023

Verification of a Modeling Toolkit for the Design of Building Electrical Distribution Systems

DC electrical distribution systems offer many potential advantages over their AC counterparts. They can facilitate easier integration with distributed energy resources, improve system energy efficiency by eliminating AC/DC converters at end-use devices (e.g., laptop chargers), and reduce installation material, time, and cost. However, DC electrical distribution systems present additional design considerations, largely resulting from potentially greater magnitude and variation in cable losses. Modeling and simulation are rarely used to design such systems. However, the greater dependency of DC system energy efficiency on design choices such as distribution voltages, architecture, and integration of PV and BESS suggests that modeling and simulation may be required. Such system performance analysis is currently not a standard practice, in part due to limited availability and validation of capable software tools. This paper characterizes the accuracy of a Modelica-based Building Electrical Efficiency Analysis Model (BEEAM) toolkit, as a precursor for validating its use to perform system performance analysis and inform design decisions. The study builds upon previous verification research by characterizing complete systems comprised of commercially available equipment, and providing a more detailed analysis of simulation results. Five lighting systems with varying electrical distribution architectures were designed using market-available equipment, installed in a laboratory environment, modeled using BEEAM, and simulated using three Modelica integrated development environments (IDEs). Simulated and measured results were compared to characterize toolkit accuracy. Initial results revealed that simulated performance was mostly within ±5% of measured system-level and device-level performance. While simulation results were not found to be dependent on the IDE, some Modelica compiler interoperability issues were identified. Although the BEEAM toolkit showed promise for the targeted use case, further work is needed to determine whether the demonstrated 5% accuracy is sufficient for making real-world design decisions, and for BEEAM to advance from an interesting research tool to one that can impact real-world building projects.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

An Environmental and Societal Analysis of the US Electrical Energy Industry Based on the Water–Energy Nexus

To meet rising energy demands, power plant operations will expand, influencing the interactions between the water–energy nexus and society. However, a major challenge is integration of social dimensions within electricity generation. To address this, we generate a baseline dataset using US public data (2014–2019) from the Energy Information Administration and US Bureau of Labor Statistics. We identify the rate of energy consumed, CO 2 , SO 2 and NO x emissions generated, and water used per MWh net electricity as well as employee wellbeing per unit MW capacity during electricity generation. Rates of energy consumption (MMBtu/MWh) decreased 4.9%, but water consumption and withdrawal (m 3 /MWh) both increased 0.93% and 0.31%, respectively. Emissions of CO 2 , SO 2 and NO x decreased 22.64%, 75% and 25% MT/MWh, respectively. Thermoelectric cooling withdrawal and consumption is led by natural gas (50.07%, 38.31%), coal (29.61%, 25.07%), and nuclear energies (13.55%, 18.99%). Electric power generation contributes 0.06 injuries–illnesses/TWh and 0.001 fatalities/TWh, of which fossil fuels contributed 70% and 15%, respectively. Fossil fuels led in average annual employment (0.02 employees/MW) with low cost salaries (USD 0.09/MW) likely due to high collective capacity, which is declining. Estimated rates in this study and framework will aid power industry transition and operational decision makers.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

A Modeling Toolkit for Comparing AC and DC Electrical Distribution Efficiency in Buildings

Recently, there has been considerable research interest in the potential for DC distribution systems in buildings instead of the traditional AC distribution systems. Due to the need for performing power conversions between DC and AC electricity, DC distribution may provide electrical efficiency advantages in some systems. To support comparative evaluations of AC-only, DC-only, and hybrid AC/DC distribution systems in buildings, a new modeling toolkit called the Building Electrical Efficiency Analysis Model (BEEAM) was developed and is described in this paper. To account for harmonics in currents or voltages arising from nonlinear devices, the toolkit implements harmonic power flow, along with nonlinear device behavioral descriptions derived from empirical measurements. This paper describes the framework, network equations, device representations, and an implementation of the toolkit in an open source software package, including a component library and graphical interface for creating circuits. Simulations of electrical behavior and device and system efficiencies using the toolkit are compared with experimental measurements of a small office environment in a variety of operating and load configurations. A detailed analysis of uncertainty estimation is also provided. Key findings were that a comparison of predicted versus measured efficiencies and power losses in the validation testbed using the initial toolkit implementation predicted device- and system-level efficiencies with reasonably good accuracy under both balanced and unbalanced AC scenarios. An uncertainty analysis also revealed that the maximum estimated error for system efficiency across all scenarios was 3%, and measured and modeled system efficiency agreed within the experimental uncertainty in approximately half of the scenarios. Based on the correspondence between simulation and measurement, the toolkit is proposed by the authors as a potentially useful tool for comparing efficiency in AC, DC, and hybrid AC/DC distribution systems in buildings.

DC distribution↗
DOE OSTI2020

Understanding the Charging Flexibility of Shared Automated Electric Vehicle Fleets

The combined anticipated trends of vehicle sharing (ride-hailing), automated control, and powertrain electrification are poised to disrupt the current paradigm of predominately owner-driven gasoline vehicles with low levels of utilization. Shared, automated, electric vehicle (SAEV) fleets offer the potential for lower cost and emissions and have garnered significant interest among the research community. While promising, unmanaged operation of these fleets may lead to unintended negative consequences. One potentially unintended consequence is a high quantity of SAEVs charging during peak demand hours on the electric grid, potentially increasing the required generation capacity. This research explores the flexibility associated with charging loads demanded by SAEV fleets in response to servicing personal mobility travel demands. Travel demand is synthesized in four major United States metropolitan areas: Detroit, MI; Austin, TX; Washington, DC; and Miami, FL. In each of these four cities, SAEV simulations are performed using local projected electricity prices from the Regional Energy Deployment System (ReEDS) for a handful of supply side scenarios. A coordinated charging model is introduced that seeks to reduce fleet charging costs in response to time-varying electricity prices and increasing shares of personal trip demand served (between 1% and 25% of all metro trips served by the SAEV fleet). Simulation results are presented across various scenarios assuming fleetwide coordination to minimize charging energy costs while constrained by offering adequate mobility service to fleet customers. The results indicate that the SAEV charging load is highly flexible; energy costs were shown to reduce between 13% and 46% across a wide range of simulated scenarios. In addition, these savings were realized without detrimentally impacting the fleet’s ability to service trips.

autonomous vehicle↗
DOE OSTI2021

Relative Cost-Effectiveness of Electricity and Transportation Policies as a Means to Reduce CO2 Emissions in the United States: A Multi-Model Assessment

Two common energy policy instruments in the United States are tax incentives and technology standards. Although these instruments have been shown to be less cost-effective as a means to reduce CO2 emissions than direct emissions pricing mechanisms, it can be challenging to compare the CO2 emissions reduction costs of such policies across sectors, given the wide range in estimates for any given policy and inconsistencies in how such estimates are constructed across studies. This study addresses this analytical gap by simultaneously comparing the cost-effectiveness of policies across the electricity and transportation sectors using three publicly available US energy system models (EM-NEMS, ReEDS, and GCAM-USA). Four policies are explicitly compared: wind and solar tax credits, a renewable portfolio standard (RPS), a renewable fuel standard (RFS), and an electric vehicle (EV) tax credit. An economy-wide carbon tax is used as a benchmark for cost-effectiveness. Results from this study confirm prior insights about the cost-effectiveness of economy-wide carbon pricing relative to sectoral instruments but also reveal several novel insights about particular sectoral policies. Specifically, this study finds that (1) current electricity tax incentives provide uneven support for wind and solar technologies, (2) despite known inefficiencies, renewable energy policies in the electricity sector are less expensive than earlier estimates due to technology advancement and changes in market conditions, (3) within transportation, an expanded RFS with increasing advanced biofuel targets is more cost-effective than an EV tax credit extension under plausible assumptions, (4) EV incentives lead to a rebound in conventional vehicle fuel economy that further erodes cost-effectiveness, and (5) the change in policy costs over time is not known a priori, but the relative cost ordering among these policies does not depend on the timeframe of analysis. These results are largely robust to the underlying modeling framework, increasing the confidence with which they can be applied to climate policy evaluation.

economics↗
DOE OSTI2022

When Do Different Scenarios of Future Electricity Demand Start to Meaningfully Diverge?

Climate and population change are known to influence electricity demand, but what is the impact of uncertainty in climate and population projections on electricity demand in the United States (U.S.) over the next 30 years? This question has important implications for investment decisions in the energy sector, which are typically made using a 15- to 30-year time horizon. Simply put, if future climate and population scenarios do not lead to meteorological conditions and subsequent energy demands that are distinctly different within the first 30 years then, for the purposes of investment decisions, it may not matter which potential pathway we are most likely on. The Integrated, Multisector, Multiscale Modeling (IM3) project has generated a wide, yet plausible range of 21st century high-resolution climate and population scenarios for the U.S. The IM3 projections span two climate scenarios (Representative Concentration Pathways 4.5 and 8.5) and two population scenarios (Shared Socioeconomic Pathways 3 and 5). For each of the climate scenarios, we reflect a range of climate model uncertainty by using boundary conditions from a set of climate models that are hotter and colder than the multi-model mean. In total there are eight (2 x 2 x 2) IM3 scenarios. This work explores a basic question: When do future climate and energy outcomes start to meaningfully diverge across the eight scenarios? The analysis is done on both the raw meteorology time-series from each scenario as well as a time-series of projected total electricity demand generated using IM3's Total ELectricity Loads (TELL) model. We also explore the spatial heterogeneity of the divergence signal to identify regions of the country that may be more or less path dependent.

Climate Change↗
DOE OSTI2023

GCAM-USA electricity demand results for National Climate Assessment 5

Overview This dataset includes GCAM-USA v 5.3 outputs for the percent change in electricity demand in the U.S. from 2020 to 2050 and from 2020 to 2100 for the thermodynamic global warming scenario "RCP8.5_hotter" and the SSP5 socioeconomic scenario. These results were produced as part of the Integrated Multisector, Multiscale Modeling (IM3) project. Detailed Information The electricity demand is calculated based on the IM3 GCAM-USA simulations. For the purpose of reproducibility, we provide the following data: 1. Raw data: the annual electricity demand for CONUS simulated by IM3 GCAM-USA for the scenario RCP8.5 Hotter - SSP5. 2. R scripts: process raw data, calculate percent change of electricity demand from 2020 to 2050 and from 2020 to 2100, and plot the data over CONUS. 3. Results: figures provided for NCA-5 and the corresponding data table from the R scripts.

Climate Change↗
DOE OSTI2026

Impact of Space Heating Options on Electricity Rates and Affordability

Electricity prices have increased in many regions of the U.S., with a national average of 18 cents/kWh projected for 2026, up from 16 cents/kWh in 2020. While the increases can be attributed to a number of factors, increasing electricity use in an efficient and strategic manner - with energy efficient building envelope upgrades and high performance HVAC systems - has the potential to increase revenue for utilities without significantly increasing electricity demand, and therefore could help moderate rate increases. This effect has been studied for electric vehicle charging[1] and dual-fuel heat pumps in Minnesota[2]. Leveraging a recently developed system cost methodology and FERC data on utility revenue, spending, and profits, this poster will present the direction and relative magnitude of rate impacts for efficient space heating upgrades in utility balancing areas across the contiguous U.S., using current prices and showing how the rate impacts would evolve under future grid scenarios.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Levelized Cost of Charging Electric Vehicles

This data set includes the levelized cost of charging (LCOC) and lifetime fuel cost savings (LFCS) values as reported in "Levelized Cost of Charging of Electric Vehicles in the United States." Values are reported at the state and national levels for battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs). The data set also includes the four annual direct current fast charging (DCFC) station load profiles used to approximate the levelized cost of DCFC charging. Each profile provides 15-min resolved power requirements for one full year. Borlaug, B., Salisbury, S., Gerdes, M., and Muratori, M., Levelized Cost of Charging Electric Vehicles in the United States, Joule (2020), https://doi.org/10.1016/j.joule.2020.05.013.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Automotive Power Electronics and Electric Machine Thermal Management

The transition to modular and scalable electrified vehicle transportation requires technologies to improve power density within cost and reliability constraints to maximize vehicle platform flexibility. Key research challenges arise due to the limited packaging space, coolant distribution, electrical connections, and ambient temperatures. Challenges include thermal management for compact power-dense electric machines and the associated power electronics for power management within the vehicle. High-temperature silicon and wide-bandgap (WBG) based power electronics systems are of interest to enable compact and efficient electric drive systems. The higher temperatures present packaging challenges for thermal management and reliability. In this work, we provide an overview of research for thermal characteristics of materials, packages and thermal management approaches for enabling compact power dense automotive electric drive systems.

DIRECT ENERGY CONVERSION↗
DOE OSTI2021

Data-driven estimation of energy consumption for electric bus under real-world driving conditions

Reliable and accurate estimation of an electric bus’s instantaneous energy consumption is critical in evaluating energy impacts of planning and control of electric bus operations. In this study, we developed machine learning-based long short-term memory (LSTM) and artificial neural network (ANN) models to estimate 1 Hz energy consumption of electric buses based on continuous monitoring data of electric buses in Chattanooga, Tennessee, in 2019 and 2020. We propose a data-partitioning algorithm to separate energy charging and discharging modes before applying data-driven estimation models. Here, a K-fold cross-validation-based model selection process was conducted to identify the optimal model structure and input variables in terms of prediction accuracy. The estimation results show the predicted mean absolute percentage error rates of LSTM and ANN models were 3% and 5%, respectively. We compared the proposed models with existing models in the literature based on the same testing data to demonstrate the predictability of our models.

Artificial neural network↗
DOE OSTI2023

At a Glance: Electric Vehicles

Electric vehicles (EVs) include all-electric vehicles - also referred to as battery electric vehicles (BEVs) - and plug-in hybrid electric vehicles (PHEVs).

ADVANCED PROPULSION SYSTEMS↗