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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Expert Elicitation for Tidal Energy Levelized Cost of Energy: Present and Future

In accordance with the Government Performance and Results Act (GPRA), H2O annually assesses marine energy technology development resulting from government-funded research and development programs and strategy. For GPRA reporting, H2O uses the levelized cost of energy (LCOE) - which represents the total system cost per unit of energy produced - to measure the progression of marine energy technology development, assess the impact of their research and development programs, and identify future research priorities. To support H2O's GPRA reporting requirements and inform future strategy, the National Laboratory of the Rockies conducted a tidal energy LCOE expert elicitation study to estimate present and future LCOE[AB2.1]. This report describes the motivation and background for the elicitation study, the methodology used to conduct the study, and the study results. It also provides future recommendations for accelerated tidal energy LCOE reduction based on feedback from study participants.

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

Assessing the levelized cost of energy in South Korea

This study evaluates the levelized cost of energy (LCOE) for various energy technologies in the Republic of Korea (Korea) from 2023 to 2050, highlighting cost trajectories and potential crossovers among competing technologies. The analysis projects that, based on our set of assumptions, utility-scale photovoltaic systems achieve lower LCOEs than nuclear by 2030, while fixed offshore wind is expected to become cost-competitive with coal-fired generation around the same time. Floating offshore wind is projected to reach cost parity with coal in the late 2030s. Co-firing with natural gas and green hydrogen is identified as the highest-cost generation option due to high natural gas and green fuel costs and declining capacity utilization. This study further examines the potential for hybrid systems that integrate renewable energy with energy storage to serve as flexible, cost-effective, zero-emission alternatives to green hydrogen-based generation. Spatial LCOE assessments indicate that near-shore offshore wind sites may achieve lower costs despite modest capacity factors, contingent on site-specific factors such as grid integration and social acceptance. The findings indicate that renewable energy technologies are expected to experience continued cost declines, with solar photovoltaic becoming the most competitive energy source in Korea by 2030–2035. Incorporating social costs accelerates this shift from conventional alternatives.

Green hydrogen↗
DOE OSTI2026

Project 1: COLLECTS Project and Project 2: M&V for Saputo Cheese Project: Cooperative Research and Development (Final Report)

Project 1: Combined Power's Hyperlight Energy and NLR will collaborate on the DOE Concentrating Optics for Lower Levelized Energy CosTS (COLLECTS) project, DE-FOA-0001268. COLLECTS funding opportunity announcement (FOA) seeks to further concentrated solar power (CSP) system technologies by soliciting disruptive, transformative projects for the concentrating solar collectors in the CSP plant. These innovative projects will seek to surpass the targets set out in the SunShot Vision Study, enabling CSP to be cost-competitive with conventional forms of electric power generation. Projects will target the design and manufacturing of novel solar collectors with the ability to significantly reduce the solar field contribution to the overall levelized cost of energy (LCOE) of the CSP plant, and which have not been previously specifically targeted by CSP FOAs. Project 2: Hyperlight will perform measurement and verification (M&V) of Green House Gases and NLR will evaluate energy consumption reduction.

14 SOLAR ENERGY↗
DOE OSTI2023

Modeling Annual Electricity Production and Levelized Cost of Energy from the US East Coast Offshore Wind Energy Lease Areas

Offshore wind energy development along the East Coast of the US is proceeding quickly as a result of large areas with an excellent wind resource, low water depths and proximity to large electricity markets. Careful planning of wind turbine deployments in these offshore wind energy lease areas (LA) is required to maximize power output and to minimize wake losses between neighboring wind farms as well as those internal to each wind farm. Here, we used microscale wind modeling with two wake parameterizations to evaluate the potential annual energy production (AEP) and wake losses in the different LA areas, and we developed and applied a levelized cost of energy (LCoE) model to quantify the impact of different wind turbine layouts on LCoE. The modeling illustrated that if the current suite of LA is subject to deployment of 15 MW wind turbines at a spacing of 1.85 km, they will generate 4 to 4.6% of total national electricity demand. The LCoE ranged from $68 to $102/MWh depending on the precise layout selected, which is cost competitive with many other generation sources. The scale of the wind farms that will be deployed greatly exceed those currently operating and mean that wake-induced power losses are considerable but still relatively poorly constrained. AEP and LCoE exhibited significant dependence on the precise wake model applied. For the largest LA, the AEP differed by over 10% depending on the wake model used, leading to a $10/MWh difference in LCoE for the wind turbine layout with 1.85 km spacing.

58 GEOSCIENCES↗
DOE OSTI2026

Solar Photovoltaics Resilient Fasteners Levelized Cost of Energy (LCOE) Tool

Solar photovoltaics (PV) module fasteners are one of the most common structural failure points on PV systems, particularly in high winds and coastal areas with ocean spray. Some fastener types have been shown to survive these conditions at higher rates than others. The fastener type, material, quantity, and placement all impact performance. Fasteners that fail less often typically have a higher upfront cost, but this investment can pay off in savings from less frequent torque audits (which reduces O&M costs), reduced system damage, and decreased system downtime. We developed an Excel-based tool to evaluate different module fasteners for a PV system - either a new or retrofit project - and compare differences in upfront and outyear costs to determine the expected life cycle costs and simple payback periods of different fastener options. The tool is site-specific, with inputs including system attributes (such as system size, location, price of power) and fastener attributes (such as design, washer type, nut type, use of locking hardware, materials, installation time, and torque audit requirements). A baseline fastener scenario can be compared to up to four proposed fastener scenarios. In addition to presenting expected life cycle cost implications of the different fastener options, the tool produces results showing the reductions in outyear costs needed to offset any initial cost premiums for more reliable fasteners across four categories: preventative O&M, avoided damage, reduced downtime, and reduced insurance premiums. These numbers can serve as decision aids for users when considering fastener options on new or existing projects. This poster will present the tool, methodology, and scenarios using example sites to highlight the tool capabilities and how it can inform different fastener decisions on different projects. Future work includes incorporating lifetime expected damage costs by embedding damage function curves that the authors are developing from field data.

14 SOLAR ENERGY↗
DOE OSTI2023

United States Utility-Scale PV Supply Curves 2023

This data packet contains supply curves, hourly generation profiles, and a composite siting exclusion TIFF for utility-scale PV across the contiguous United States. The supply curves offer comprehensive metrics such as capacity (MW), generation (MWh), levelized cost of energy (LCOE), levelized cost of transmission (LCOT), and more for each reV site (~60,000 sites). Hourly generation profiles are available for each reV site and can be matched to the available capacity in the supply curve (refer to the Jupyter Notebook). The composite exclusion TIFF is a single file that delineates areas where PV installations are permissible based on various siting assumptions. This data packet contains information for the Reference and Limited siting scenarios. For further details and citation, please refer to the publication linked below: Lopez, Anthony, Pavlo Pinchuk, Michael Gleason, Wesley Cole, Trieu Mai, Travis Williams, Owen Roberts, Marie Rivers, Mike Bannister, Sophie-Min Thomson, Gabe Zuckerman, and Brian Sergi. 2024. Solar Photovoltaics and Land-Based Wind Technical Potential and Supply Curves for the Contiguous United States: 2023 Edition. Golden, CO: National Renewable Energy Laboratory. NREL/TP-6A20-87843.

2023↗
DOE OSTI2023

United States Land-based Wind Supply Curves 2023

This data packet contains supply curves, hourly generation profiles, and a composite siting exclusion TIFF for land-based wind across the contiguous United States. The supply curves offer comprehensive metrics such as capacity (MW), generation (MWh), levelized cost of energy (LCOE), levelized cost of transmission (LCOT), and more for each reV site (~60,000 sites). Hourly generation profiles are available for each reV site and can be matched to the available capacity in the supply curve (refer to the Jupyter Notebook). The composite exclusion TIFF is a single file that delineates areas where wind installations are permissible based on various siting assumptions. This data packet contains information for the Reference and Limited siting scenarios. The turbine parameters used were a hub-height of 115 meters and a rotor diameter of 170 meters, as obtained from the Annual Technology Baseline (ATB) 2022. For further details and citation, please refer to the publication linked below: Lopez, Anthony, Pavlo Pinchuk, Michael Gleason, Wesley Cole, Trieu Mai, Travis Williams, Owen Roberts, Marie Rivers, Mike Bannister, Sophie-Min Thomson, Gabe Zuckerman, and Brian Sergi. 2024. Solar Photovoltaics and Land-Based Wind Technical Potential and Supply Curves for the Contiguous United States: 2023 Edition. Golden, CO: National Renewable Energy Laboratory. NREL/TP-6A20-87843.

2023↗
DOE OSTI2026

Prioritizing Transformative Energy Efficiency Technologies in the Pulp and Paper Sector Through Levelized Cost of Conserved Energy

This presentation explores how the U.S. pulp and paper sector can prioritize energy efficiency (EE) technologies using the Levelized Cost of Conserved Energy (LCCE) metric. As mills face market shifts and rising costs, technologies such as advanced drying, membrane concentration, waste heat recovery, and recovery boiler replacements offer potential savings but face economic barriers. LCCE enables consistent comparison of technologies by calculating cost per unit of energy saved, including capital, operating, and potentially non-energy benefits like productivity, maintenance, and safety improvements. Preliminary findings show economies of scale significantly influence recovery boiler replacement feasibility, with larger systems achieving lower LCCE values. Ongoing work incorporates non-energy benefits to provide a more comprehensive cost-effectiveness assessment and guide research, development, and deployment priorities for underutilized and emerging technologies.

Kamath, Dipti [ORNL] (ORCID:0000000278739994)↗
DOE OSTI2024

Levelized Cost of Energy Comparison of Floating Wind Farms With and Without Shared Anchors

As part of the Innovative Deep-Water Mooring Systems for Floating Wind Farms (DeepFarm) R&D project, led by Principle Power Inc., the National Renewable Energy Laboratory (NREL) performed an LCOE analysis to compare the changes in LCOE between floating wind farms with individual anchors versus shared anchors. This report presents a comparative analysis of the LCOE of two different wind farms with different mooring systems: one with taut mooring lines each connected to individual suction pile anchors, and one with taut mooring lines connected to shared anchors. A brief description of the methodology employed to conduct the LCOE comparison is given, including the underlying assumptions. Then, results are presented with a compilation of key findings.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

A Clean Energy Deployment Baseline for the Energy Community and Low-Income Tax Credit Bonuses [Slides]

The Inflation Reduction Act of 2022 introduced, for the first time, place-based federal tax incentives for projects sited in “Energy Communities,” potentially changing the economic calculus of where projects are best sited. Storage projects can qualify for a 10-percentage-point bonus to the Investment Tax Credit (e.g., from 30% to 40%), while wind and solar projects may qualify for either the ITC bonus or a 10% bonus to the Production Tax Credit (e.g., from $\$27.5$ to $\$30.25$/MWh). Energy Communities are areas with historical ties to fossil fuel industries and above average unemployment levels (FFEU), with closed coal mines or power plants, or contaminated properties. They seek to identify locations across the US that could especially benefit from economic revitalization. This report explores how the new federal tax credit incentives are impacting clean energy deployment patterns and establishes historical baselines against which future changes can be compared. We include a few case studies of clean energy projects going specifically to areas that were recently impacted by coal power plant closures to provide concrete examples of investments in Energy Communities. However, this publication does not assess how much of the incentive benefits pass from clean energy developers to hosting communities, nor does it offer a comprehensive view of the economic effects of clean energy deployment on Energy Communities. Key highlights include: - As clean energy projects take multiple years to conceptualize and develop, it is likely too early to see shifts towards Energy Community locations either among newly built projects or those that entered interconnection queues in 2023. - Approximately 35% of onshore wind, 50% of solar, and 60% of storage capacity built in 2023 and the first half of 2024 are located in Energy Communities, making them likely eligible for bonus incentives. While these bonus incentives were not available to projects coming online before 2023, we used 2023 Energy Community definitions to classify whether past projects were built in what is now considered an Energy Community. The deployment levels for 2023-2024 are similar to recent years (2020-2022) for solar and storage but slightly lower for wind. - Clean energy capacity has surged in the interconnection queues over the last few years, with about 45-50% of both recently proposed and total queued capacity being located in Energy Communities. While the amount of capacity in Energy Communities has also grown, its relative share is either stable (solar and storage) or slightly lower (wind) among projects that entered the queue in 2023. - Clean energy projects can be built at lower costs in Energy Communities. The levelized cost of energy after incentives was on average $\$9$/MWh (24%) lower for solar projects and $\$2$/MWh (6%) lower for wind projects built in 2023, relative to projects not located in Energy Communities. Wholesale electricity values at Energy Community locations relative to the rest of the market vary by region. The average value was often higher for wind projects (-$\$3$ to $\$11$/MWh) but lower for solar projects (-$\$6$ to 0/MWh). - Distributed solar that is owned by commercial entities is eligible for the Energy Community bonus and also, potentially, a Low-Income Community bonus. Residential solar installations in qualifying Energy Communities that are third-party owned represent about 10% of the total residential market. Larger commercial and industrial solar installations in Energy Communities make up 17% of the total market in 2023. Nearly 2 GW of distributed solar was built in areas qualifying as Low-Income Communities in 2023, exceeding the available annual program cap of 700 MW. Continued tracking of these trends will be important for system planners, investors, and local communities.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Future Wind Energy Resources and Cost Uncertainties Across the United States

This dataset contains results estimating projections of change of annual capacity factors and levelized cost of energy for several turbine technologies in the 2024 Annual Technology Baseline (ATB). Projections of change are based on downscaled earth system model (ESM) data from Sup3rCC. There has been evidence of reductions in average wind speeds over land in North America since the 1980s, and several models project that average wind speeds will continue to decrease. Concurrently, the cost of wind energy systems in the United States has been decreasing since around 2010, a trend also projected to continue. There is considerable uncertainty in these future projections, with quantitative estimates of future wind resource and system costs varying widely. To study this, we run land-based wind energy models with a range of possible future system costs, turbine designs, and meteorological inputs from multiple downscaled earth system models over the contiguous United States to estimate critical system performance metrics such as annual energy production (AEP) and levelized cost of energy. Where multiple earth system models agree, changes in mean AEP from the time period 2000-2019 to 2040-2059 can be as high as +10% in South Texas or as low as -20% in Iowa. Several additional states in the Midwest that currently have considerable wind generation capacity show the possibility of substantial decreases in AEP by mid-century. Larger turbines and moderate reductions in system costs can offset even the largest projected decreases in wind resource, but much uncertainty remains in the extent to which wind resources will actually change into the future and to what extent wind energy systems can drive down future costs. An analysis of variance shows, in several states in the Midwest, the uncertainty in future wind resource can be almost as important for future changes in the cost of wind energy as the uncertainty in future system costs.

17 WIND ENERGY↗
DOE OSTI2025

Hydrogen-Battery Hybrid Energy System on Repurposed Offshore Platforms for Efficient Clean-Energy Transition

Due to the rising global energy demand and enhanced awareness of the environmental impact of fossil fuels, the Gulf of Mexico, traditionally known for oil extraction, offers a distinct chance to repurpose the existing offshore infrastructure. With the depletion of oil reserves, it is feasible to adapt previously utilized floating platforms for extraction to generate renewable energy, specifically through wind-generated power and hydrogen production. This adaptation seeks to promote a transport system that is more ecologically friendly in the future. Offshore wind turbines serve as the main energy source, with help from battery storage and hydrogen production to enhance the overall system performance, hydrogen creation, fuel, and electricity delivery for sustainable energy production. The system is divided into two distinct cases, each evaluated for cost, performance, and feasibility, with a focus on minimizing both the Levelized Cost of Energy (LCOE) and the Levelized Cost of Hydrogen (LCOH). The first case examines the integration of offshore wind turbines with hydrogen production. Excess electricity generated by wind turbines is directed toward hydrogen production via electrolysis. The hydrogen produced can be used as fuel for vehicles or transported to the shore via pipelines. The second case investigates a technology that combines wind turbines with battery storage. The batteries possess an ability to supply electricity for a continuous duration of 4 hours maximum each day. The main objective is to reduce the LCOE by considering the battery's charging and discharging cycles, together with the uncertain attributes of wind power and battery deterioration. The produced energy can be distributed for onshore applications or utilized for the purpose of offsetting offshore loads such as subsea oil and gas production, transportation, etc. The offshore hydrogen-battery hybrid system is improved via three advanced algorithms, Particle Swarm Optimization (PSO), and Grey Wolf Optimizer (GWO). In Case 1, PSO improves hydrogen production by efficiently managing the electrolyzer’s power consumption, decreasing production costs significantly. Particle Swarm Optimization (PSO) is applied to improve the efficiency of the electrolyzer, reducing production costs and achieving an optimized CAPEX of $240.00 million (from an initial $300.00 million) and OPEX of $9.60 million per year. This system produces 4,720,000 kg of hydrogen annually, with a Levelized Cost of Hydrogen (LCOH) of $6.40/kg and an annual profit of $9.27 million. In Case 2, GWO effectively reduces the overall energy cost by improving the charge-discharge management of batteries, which extends battery life and optimizes their use. The second case focuses on integrating battery storage, optimized using the Grey Wolf Optimizer (GWO), which enhances battery charge-discharge cycles, extending battery life and lowering costs. This system achieves an optimized CAPEX of $204.80 million (from an initial $256.00 million) and OPEX of $9.29 million per year, producing 310883.39 MWh of electricity annually at a Levelized Cost of Energy (LCOE) of $86.13/MWh, with an annual profit of $6.25 million. The implementation of a comprehensive strategy results in a substantial reduction in costs, improved energy efficiency, and a dependable supply of both electric power and hydrogen, emphasizing the benefits of converting offshore oil platforms for clean energy transition. This study explores a clean strategy to enable cost-effective repurposing of offshore O&G platforms. Both cases highlight the economic and technical feasibility of transitioning offshore oil platforms to clean energy systems, demonstrating substantial cost reductions and reliable energy and hydrogen supplies for sustainable energy production.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Energy–Performance Trade-offs in Privacy-Preserving Federated Learning on SmartNIC-Enabled HPC Systems

Federated learning (FL) is increasingly deployed on accelerator-rich high-performance computing (HPC) systems, yet the system-level energy cost of privacy-aware FL remains poorly understood, particularly across heterogeneous networking and server-placement options. We present a measurement-driven study of energy–performance trade-offs for FL on GH200-class nodes across three deployment configurations: CPU-Ethernet, CPU-InfiniBand (RDMA-capable), and a DPU-hosted FL server over InfiniBand using a BlueField-3 SmartNIC/DPU. Using NVIDIA FLARE (NVFLARE), we align node-level power telemetry with per-round timing extracted from NVFLARE logs to quantify time-to-solution (TTS), energy-to-solution (ETS), energy-delay product (EDP), and synchronization behavior for three transformer models (ALBERT, DistilBERT, BERT), trained with and without differential privacy (DP). We find that interconnect choice is the dominant driver of runtime and energy: host-managed InfiniBand consistently reduces communication overhead versus Ethernet, yielding lower TTS/ETS/EDP. In contrast, in our NVFLARE deployment, placing the FL server on the DPU does not consistently match CPU-InfiniBand performance and can be slower—especially for larger models—highlighting that server placement alone is not sufficient to guarantee end-to-end gains. Finally, under our fixed-round protocol, DP increases per-round cost and runtime variance; ETS increases largely in proportion to TTS because average node power remains relatively stable across configurations.

Kotevska, Olivera [ORNL] (ORCID:0000000316772243)↗
NASA NTRS1986

The Jet Propulsion Laboratory low-cost solar array project, 1974-1986

The overall objective of the photovoltaic program is to ensure that photovoltaic conversion systems play a significant role in the nation's energy supply by stimulating an industry capable of providing approximately 50 GWe of installed electricity generating capacity by the year 2000. In order to achieve this overall objective, several time-phased program goals have been defined. Near-term goals are to achieve photovoltaic flat-plate module or concentrator array prices of $2 per peak watt (1975 dollars) at an annual production rate of 20 peak megawatts in 1982. At this price level, energy costs should range from 100 to 200 mills/kwh. Mid-term goals are to achieve photovoltaic flat-plate module or concentrator array prices of $0.50 per peak watt (in 1975 dollars), and an annual production rate of 500 peak megawatts in 1986. Studies project that photovoltaic systems will begin to compete for both distributed and larger load-center utility-type applications and thereby open up significant markets for large-scale photovoltaic systems. Far term goals are to achieve the photovoltaic flat-plate module or concentrator array price goal of $0.10 to $0.30 per peak watt in 1990 (in 1975 dollars), and an annual production rate of 10 to 20 peak gigawatts in 2000. At this price range, energy cost should be in the range of 40 to 60 mills. kwh and be cost effective for utility applications. Achievement of these goals can make photovoltaic systems economically competitive with other energy sources for dispersed on-site applications as well as for central power generation.

Maycock, P. D.↗
NASA NTRS1982

Economic viability of photovoltaic power for development assistance applications

This paper briefly discusses the development assistance market and examines a number of specific photovoltaic (PV) development assistance field tests, including water pumping/grain grinding (Tangaye, Upper Volta), vaccine refrigerators slated for deployment in 24 countries, rural medical centers to be installed in Ecuador, Guyana, Kenya and Zimbabwe, and remote earth stations to be deployed in the near future. A comparison of levelized energy cost for diesel generators and PV systems covering a range of annual energy consumptions is also included. The analysis does not consider potential societal, environmental or political benefits associated with PV power. PV systems are shown to be competitive with diesel generators, based on life cycle cost considerations, assuming a system price of $20/W(peak), for applications having an annual energy demand of up to 6000 kilowatt-hours per year.

Bifano, W. J.↗
NASA NTRS1991

Long-Lifetime Laser Materials For Effective Diode Pumping

Long quantum lifetimes reduce number of diodes required to pump. Pumping by laser diodes demonstrated with such common Nd laser materials as neodymium:yttrium aluminum garnet (Nd:YAG) and Nd:YLiF4, but such materials as Nd:LaF3, Nd:NaF.9YF3, and possibly Nd:YF3 more useful because of long lifetimes of their upper laser energy levels. Cost effectiveness primary advantage of solid-state laser materials having longer upper-laser-level lifetimes. Because cost of diodes outweighs cost of laser material by perhaps two orders of magnitude, cost reduced significantly.

Barnes, Norman P.↗
DOE OSTI2023

Estimating the Value of Worker Training: A System Reliability & LCOE Perspective

This workshop presentation briefly describes the labor standards required for large photovoltaic (PV) systems (>1MWac) to receive the full investment tax credit from the Inflation Reduction Act. The potential for labor standards to affect aspects other than upfront installation costs (such as energy generation or maintenance expenses) is analyzed using levelized cost of energy (LCOE) calculations. This considers benefits which may come from better training for workers, more productive workers, or improved installation quality, using NREL's simplified PV-specific LCOE calculator at pvlcoe.nrel.gov.

ENERGY PLANNING, POLICY, AND ECONOMY,SOLAR ENERGY↗
DOE OSTI2025

Low embodied energy and carbon, high lifetime silicon boules via a combined chemical vapor deposition/float zone process

This work evaluates a new process route to making float zone (Fz)-quality silicon wafers using a combination of computational fluid dynamics (CFD) modeling and technoeconomic analysis. Our analysis finds that the new process competes with Czochralski (Cz)-grown wafers on a levelized cost of energy system level. The new process also decreases embodied energy and carbon of silicon photovoltaics (PV) by ~6x circumventing the energy-costly Siemens process used in polycrystalline silicon (poly-Si) production plants to generate feedstock for Fz and Cz boules. Instead of using poly-Si from the Siemens process to feed crystallization, the new process uses the high-purity, trichlorosilane (TCS) precursor gas to grow a poly-Si feed rod in-situ during a modified Fz1,2 boule growth process. The gas-to-boule float zone process enables opportunity to produce high-purity (low metals and oxygen content), uniformly doped single crystal silicon boules and wafers with high bulk lifetimes (τ bulk > 15 ms) to enable higher efficiency cells (>27 %) with fewer known degradation mechanisms than Czochralski (Cz)-grown wafers. These benefits reduce the levelized cost of electricity (LCOE) of PV-produced electricity. Here we show the results of our CFD and chemical modeling of the process to prove feasibility and economic viability.

14 SOLAR ENERGY↗