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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

Retail Electricity Price and Cost Trends: 2024 Update [Slides]

Berkeley Lab’s "Retail Electricity Price and Cost Trends" summarizes recent trends in retail electricity price levels and price drivers in the United States. This report is intended to serve as a reference document for the diverse set of decision-makers impacted by changes in retail electricity prices and to provide a factual basis for assessing recent changes in retail electricity prices and key underlying drivers. National, regional, and state trends are reported for 2019 through 2023 using publicly-available data for: -Average retail electricity prices, retail sales, and utility revenues -Utility capital expenditures, operations and maintenance costs, and fuel and purchased power costs -Retail electricity sales impacts from behind-the-meter resources The report also includes qualitative case studies highlighting recent and/or regionally-specific issues contributing significantly to retail electricity price trends

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Cost of saving natural gas through efficiency programs funded by utility customers: 2012–2017

This study estimates the cost of saving a therm of natural gas from energy efficiency programs funded by utility customers during the period 2012 to 2017. Berkeley Lab researchers compiled and analyzed efficiency program data reported by investor-owned utilities and other program administrators in a dozen states representative of the four U.S. Census regions — Arkansas, California, Connecticut, Iowa, Massachusetts, Michigan, Minnesota, New Jersey, New York, Oklahoma, Rhode Island and Utah. Depending on the year, the dataset accounts for about 50 percent to 70 percent of annual national spending on natural gas efficiency programs. The estimated cost of saving natural gas during the study period is $0.40 per therm. The analysis also includes estimates of the program administrator cost of saved energy for three core sectors for natural gas: commercial and industrial, residential, and low-income households. It aggregates these sectors to provide regional and national values. Our metrics include savings-weighted averages, unweighted medians, and interquartile ranges (25th and 75th percentiles) of the levelized program administrator cost of saving gas, in constant 2017 dollars. In addition, the study analyzes cost trends during the study period, finding that average program costs trended downward. The U.S. Department of Energy’s Building Technologies Office supported this work.

03 NATURAL GAS↗
DOE OSTI2023

Electrical Infrastructure Cost Model for Marine Energy Systems

The National Renewable Energy Laboratory's Electrical Infrastructure Cost Model is an Excel-based tool designed to estimate the electrical infrastructure costs of marine energy components and subsystems. It incorporates data collected from offshore wind projects, utility projects, and other relevant sources to provide accurate and comprehensive cost projections. With its user-friendly interface, the model allows users to input various parameters related to the system array, electrical cables, and substations. By leveraging industry data, cost trends, and technological advancements, the model generates outputs that include system array sizing, electrical cable specifications and costs, substation specifications and costs, and total electrical infrastructure costs. One of the notable strengths of the model is its flexibility in covering multiple-orders-of-magnitude scaled systems, accommodating projects ranging from proof-of-concept or pilot-scale installations to large-scale offshore systems. By collecting data largely from offshore wind reports and utility projects, the model incorporates real-world conditions and accounts for industry-specific factors. It incorporates cost trends and sizing relationships to deliver cost estimations for electrical infrastructure components, such as electrical cables and substation equipment.

16 TIDAL AND WAVE POWER↗
DOE OSTI2026

Carbon fiber design improvements based on economic models

Circular fiber geometries are predominant in commercial carbon fiber material systems, but the use of this fiber shape has numerous limitations. Circular geometries have continuous symmetry, which is helpful for various processing considerations, but also have the largest possible maximum diffusion thickness for a given fiber area. This characteristic means that circular carbon fibers always have the highest material processing cost and lowest production throughput compared to any other fiber shape with the same area and tow count. To quantify material cost and other benefits for non-circular carbon fiber geometries, process models for polyacrylonitrile based carbon fiber production are developed in relationship to the carbon fiber shape, size, and tow count. For a given fiber shape, precursor production costs are shown to favor maximizing fiber size while conversion costs are minimized by the smallest fiber size. These competing cost trends result in a numerically optimal fiber size for a given shape and tow count, while both cost components are decreased by increasing tow count. Cost–performance tradeoffs for three lobe fiber geometries are studied by supplementing the cost trends with a numerical failure model to predict compressive strength for discrete shape variants. The shape selection is shown to be more sensitive to variations in cost than compressive strength while suboptimal shape designs can improve manufacturing robustness and achievable fiber volume fractions. Finally, an optimal three lobe carbon fiber is identified that balances the set of considerations while reducing costs and embodied energy and increasing production throughput compared to a commercial carbon fiber.

Carbon fiber↗
DOE OSTI2023

IEA Wind TCP Task 26: Wind Technology, Cost, and Performance Trends for Denmark, Germany, Ireland, Japan, Norway, Sweden, the European Union, and the United States 2016-2019

The Cost of Wind Energy represents an international collaboration dedicated to exploring the historical and future cost of wind energy in addition to the investigating the market value wind energy may provide. The countries that are currently represented by participating organizations in IEA Wind TCP Task 26 included in this report are Denmark, Germany, Ireland, Japan, Norway, Sweden, the European Union, and the United States. This manuscript documents technology and cost trends from 2008 through 2019 and discusses the trends from 2016 through 2019 that affected the cost of land-based wind energy within each country. The cost of wind energy during this period is compared with the market value of wind energy in the respective electricity market for each country.

17 WIND ENERGY↗
DOE OSTI2025

Documenting 15 Years of Reductions in U.S. Solar Photovoltaic System Costs

The U.S. Department of Energy's (DOE) Solar Energy Technologies Office (SETO) has played a key role in reducing PV system costs by supporting essential and high-impact research, development, and deployment (RD&D) activities. SETO's efforts go beyond improving technology and hardware innovations to tackle soft costs like installation labor, permitting, and customer acquisition. This holistic focus ensures that solar energy remains a viable, scalable solution for combating climate change and achieving the nation's clean energy goals. This National Renewable Energy Laboratory's (NREL) report highlights over a decade of transformative advancements in PV system technology and its cost reductions from 2010 to 2024, documenting a remarkable trajectory in line with the goals set forth by SETO. By analyzing benchmark configurations across different photovoltaic (PV) sectors over years, this work provides industry stakeholders with a comprehensive understanding of cost trends and their impact on Levelized Cost of Energy (LCOE) targets established under the 2010 SunShot Initiative.

14 SOLAR ENERGY↗
DOE OSTI2023

U.S. Solar Photovoltaic System and Energy Storage Cost Benchmarks, With Minimum Sustainable Price Analysis: Q1 2023

The U.S. Department of Energy's (DOE's) Solar Energy Technologies Office (SETO) aims to accelerate the advancement and deployment of solar technology in support of an equitable transition to a decarbonized economy no later than 2050, starting with a decarbonized power sector by 2035. Its approach to achieving this goal includes driving innovations in technology, hardware, and soft cost reductions to make solar affordable and accessible for all. As part of this effort, SETO must track solar cost trends so it can focus its research and development (R&D) on the highest-impact activities. The benchmarks in this report are bottom-up cost estimates of all major inputs to PV and energy storage system installations. Bottom-up costs are based on national averages and do not necessarily represent typical costs in all local markets. Like last year's report, this year's report includes two distinct sets of benchmarks: minimum sustainable price (MSP) benchmarks and modeled market price (MMP) benchmarks. MSP benchmarks can be interpreted as the minimum price a company needs to charge to remain financially solvent in the long term based on the minimum sustainable prices of all inputs including minimum sustainable profit margins. MMP benchmarks can be interpreted as the actual cash sales price a company charges in the given benchmark period. These simplified estimates are useful for tracking technological progress, but they do not reflect all experiences. In fact, no individual estimate under any approach can reflect the diversity of the PV and storage manufacturing and installation industries. Our residential MMP benchmark ($2.90 per watt direct current [Wdc]) is 24% higher than the MSP benchmark ($2.34/Wdc) and 9% lower than our MMP benchmark ($3.18/Wdc) from Q1 2022 in 2022 U.S. dollars (USD). For community solar, our MMP benchmark ($1.75/Wdc) is 18% higher than our MSP benchmark ($1.49/Wdc). Our Q1 2022 benchmark report has no community solar system for comparison. For utility-scale systems with one-axis tracking, our MMP benchmark ($1.17/Wdc) is 22% higher than our MSP benchmark ($0.96/Wdc) and 10% higher than its counterpart ($1.07/Wdc) in Q1 2022 in 2022 USD.

14 SOLAR ENERGY↗
DOE OSTI2023

Q1 2023 U.S. Solar Photovoltaic System and Energy Storage Cost Benchmarks With Minimum Sustainable Price Analysis Data File

The U.S. Department of Energy's (DOE's) Solar Energy Technologies Office (SETO) aims to accelerate the advancement and deployment of solar technology in support of an equitable transition to a decarbonized economy no later than 2050, starting with a decarbonized power sector by 2035. Its approach to achieving this goal includes driving innovations in technology, hardware, and soft cost reductions to make solar affordable and accessible for all. As part of this effort, SETO must track solar cost trends so it can focus its research and development (R&D) on the highest-impact activities. The benchmarks in this report are bottom-up cost estimates of all major inputs to PV and energy storage system installations. Bottom-up costs are based on national averages and do not necessarily represent typical costs in all local markets. Like last year's report, this year's report includes two distinct sets of benchmarks: minimum sustainable price (MSP) benchmarks and modeled market price (MMP) benchmarks. MSP benchmarks can be interpreted as the minimum price a company needs to charge to remain financially solvent in the long term based on the minimum sustainable prices of all inputs including minimum sustainable profit margins. MMP benchmarks can be interpreted as the actual cash sales price a company charges in the given benchmark period. These simplified estimates are useful for tracking technological progress, but they do not reflect all experiences. In fact, no individual estimate under any approach can reflect the diversity of the PV and storage manufacturing and installation industries.

14 SOLAR ENERGY↗
DOE OSTI2026

Gravity Well Commercial Economics Assessment: Potential Revenue and Cost: Cooperative Research and Development (Final Report)

In the Gravity Well Revenue Study, we evaluate the potential revenue from energy storage using historical energy-only electricity prices, forward-looking projections of hourly electricity prices, and actual reported revenue. This analysis examines the impact of storage duration and round-trip efficiency, as well as the location of the storage, on storage revenue within the current and projected U.S. power system. We also investigated the impact of round-trip efficiency on storage revenue. We found that the relationship between storage revenue and round-trip efficiency is nonlinear. The value of improved round-trip efficiency declines as round-trip efficiency increases. In the Gravity Well Future Cost Study, we applied learning curves to predict the future cost trajectory of Gravity Wells (GrWs). Two types of analysis were implemented. The first was a bottom-up analysis that used historical learning rates for cost components, such as motors and gearboxes, and cost categories (e.g., engineering and design, etc.) to determine the learning-by-doing based single-factor learning curve. The single factor learning curve expresses the relationship between the cost of GrW and the number of units deployed (or the cumulative capacity). In the second analysis, we predicted future GrW costs via a top-down approach. This approach accounts for historical cost trends in other renewable energy and storage technologies, which have similarities with GrWs. Using a multifactor learning curve that accounts for both intrinsic (cumulative capacity) and extrinsic (the elasticity in the price of steel) factors, we estimated the future cost of GrWs.

25 ENERGY STORAGE↗
DOE OSTI2024

Electric Vehicle Charging for Residential and Commercial Energy Codes: Technical Brief

Numerous studies show that sales of electric vehicles (EVs) have grown consistently over recent years in the U.S. The U.S. Energy Information Administration (EIA) estimated 3 million EVs were on the road in 2022, and the Edison Electric Institute (EEI) forecasts a total of 26.4 million EVs on the road by 2030. Based on this forecast, EEI projects the need for an additional 12.9 million EV charge ports by 2030. If EV charging infrastructure fails to keep pace with sales of EVs it could result in consumers stranded without options to power their vehicles. EVs are capable of providing substantial benefits to the consumers. EVs are less expensive to operate than conventional internal combustion engine vehicles, have lower maintenance costs, and have the convenience of fueling (charging) at home or work. Studies conducted in California show that costs associated with installing EV charging infrastructure can be substantially more expensive for retrofit scenarios compared to new construction, making inclusion of EV infrastructure in new construction codes a cost-effective policy option to increase infrastructure to meet growing demands. PNNL tracks adoption of mandatory EV provisions across the U.S. As of December 20, 2024, 12 states (California, Oregon, Washington, Colorado, New Mexico, Illinois, Maryland, Delaware, New Jersey, Rhode Island, Massachusetts and Vermont) and 53 local governments have added EV provisions to their building codes, local ordinances and zoning requirements. Originally published in 2022, this tech brief has been revised to align with recent model energy code committee discussions and published EV infrastructure code language. This technical brief summarizes market trends, costs and benefits, and provides sample code language for EV charging infrastructure for consideration to be included in model codes, such as the International Energy Conservation Code (IECC) and ANSI/ASHRAE/IES Standard 90.1, as well as directly by states and local governments in their building codes. The technical brief summarizes related efforts undertaken by states and local governments, and builds upon language considered during the 2021 and 2024 IECC development cycles.

2021 IECC↗
DOE OSTI2021

WOMBAT (Windfarm Operations and Maintenance cost-Benefit Analysis Tool) WISDEM® [SWR-21-68]

The windfarm operations and maintenance cost-benefit analysis tool (WOMBAT) is software to simulate the operations and maintenance phase of either onshore or offshore windfarms. WOMBAT is a medium-fidelity tool that is designed to model turbine, cable, and substation failures at the subassembly level, but is flexible enough that individual component or asset-level modeling can also be performed. WOMBAT enables users to model technological improvements, the use of a wide range of service equipment from drone repairs and remote resets to heavy lift vessels and crawler cranes, to analyze cost trends with varying trade-offs in conjunction with energy production, availability and a growing range of metrics. This library provides a tool to simulate the operation and maintenance phase (O&M) of distributed, land-based, and offshore windfarms using a discrete event simulation framework. WOMBAT is written around the SimPy discrete event simulation framework. Additionally, this is supported using a flexible and modular object-oriented code base, which enables the modeling of arbitrarily large (or small) windfarms with as many or as few failure and maintenance tasks that can be encoded. Please note that this is still heavily under development, so you may find some functionality to be incomplete at the current moment, but rest assured the functionality is expanding. With that said, it would be greatly appreciated for issues or PRs to be submitted for any improvements at all, from fixing typos (guaranteed to be a few) to features to testing. Also available at: https://pypi.org/project/wombat/

Cooperman, Aubryn↗
DOE OSTI2021

Offshore Wind Market Report: 2021 Edition

The Offshore Wind Market Report: 2021 Edition is intended to provide offshore wind policymakers, regulators, developers, researchers, engineers, financiers, supply chain participants, and other stakeholders with up-to-date quantitative information about the offshore wind market, technology, and cost trends in the United States and worldwide. This report details information on the domestic offshore wind industry to provide a U.S. context and help navigate technical and market barriers and opportunities.

17 WIND ENERGY↗
DOE OSTI2022

Offshore Wind Market Report: 2022 Edition

The 2022 edition of the Offshore Wind Market Report provides offshore wind policymakers, regulators, developers, researchers, engineers, financiers, supply chain participants, and other stakeholders with up-to-date quantitative information about the offshore wind market, technology, and cost trends in the United States and worldwide. The report covers the global offshore wind industry for the 2021 calendar year and the most significant U.S. domestic industry progress and events from January 1, 2021, through May 31, 2022.

17 WIND ENERGY↗
DOE OSTI2022

Offshore Wind Market Report: 2022 Edition

The 2022 edition of the Offshore Wind Market Report provides offshore wind policymakers, regulators, developers, researchers, engineers, financiers, supply chain participants, and other stakeholders with up-to-date quantitative information about the offshore wind market, technology, and cost trends in the United States and worldwide.

17 WIND ENERGY↗
DOE OSTI2022

GCAM Base Year Update

In FY21 we worked to update the Global Change Analysis Model (GCAM) to match historical energy consumption and technology cost trends and near-term economic growth expectations using available historical data out to 2019. We have done this in a way that builds the capacity to more easily update the model in the future to make GCAM a robust and readily updatable tool for decarbonization analysis.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Ensemble Simulation Techniques and Fast Randomized Algorithms

The major goals of the project were to develop and analyze new ensemble simulation techniques, including trajectory stratification and preconditioned MCMC techniques, as well as develop fast numerical linear algebra techniques closely related to ensemble simulation ideas. The trajectory stratification techniques involve simulating in parallel short trajectory fragments of a Markov process confined to a specific region of space‐time and then patching together the statistics gathered to assemble estimates of very general dynamical properties. We have also developed this approach for rare event simulation and extended the techniques to applications requiring a more general framework (such as electronic structure calculations). The preconditioned MCMC techniques involve simulating multiple Markov chains in parallel and then using information from the ensemble to speed the mixing of each individual chain. The fast randomized linear algebra methods are motivated by the diffusion Monte Carlo technique, but are applicable to finding the dominant eigenvalue of (almost) general matrices. For most non‐negative matrices, the schemes result in an error (compared to the power method) that is constant in the dimension of the problem. For more general matrices, we see a very clear sublinear cost trend in computational tests.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗