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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 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 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

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)↗
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↗
DOE OSTI2025

Determining the profitability of energy storage over its life cycle using levelized cost of storage

Levelized cost of storage (LCOS) can be a simple, intuitive, and useful metric for determining whether a new energy storage plant would be profitable over its life cycle and to compare the cost of different energy storage technologies. However, researchers and industry decision makers still use conflicting definitions of LCOS. For example, some include charging cost, while others only include round trip efficiency (RTE) losses. Additionally, inputs to the existing formulations are not specific enough to generate repeatable results across studies, which reduces trust in the metric. To push for standardization in economic assessment of batteries and other energy storage devices, the authors review existing definitions of LCOS and identify the desired characteristics for a standard. They then propose a new definition and demonstrate that it fits these characteristics very well relative to other prominent options. Unit analysis is applied to this proposed definition to provide a deeper understanding of the equations and to demonstrate its effectiveness. Finally, the sensitivity of LCOS to different input parameters is investigated to help users understand how to compare analyses from literature to their own. The authors also provide a spreadsheet and a Python script to streamline adoption of the proposed definition.

25 ENERGY STORAGE↗
DOE OSTI2025

Benchmark of numerical modeling approaches on the systematic performance evaluation of wave energy converters

Different numerical modeling methods have been developed and applied to evaluate a variety of performance indicators of wave energy converters (WECs), including the power performance, structural loads, levelized cost of energy, etc. Based on the modeling fidelity, the commonly used numerical modeling approaches can be classified as linear modeling, weakly nonlinear modeling and fully nonlinear modeling approaches. Each method differs in accuracy and computational efficiency, making them suitable for different stages of WEC design. However, the selection of modeling approach could significantly impact evaluation outcomes. For instance, simplified linear models may underestimate structural loads or overestimate energy production in some operational conditions, potentially leading to less cost-effective designs. Given the widespread utilization of these models, it is essential to understand the uncertainties brought by them in performance evaluations. This work is dedicated to benchmarking different linear-potential-flow-based numerical models for evaluating the systematic performance of WECs. Three representative numerical modeling approaches are considered in this work, including linear frequency-domain modeling, statistically linearized spectral-domain modeling and Cummins equation-based nonlinear time-domain modeling. A generic point absorber WEC is considered as the research reference in this work, and different sea sites are taken into account. The numerical models are utilized to predict critical performance indicators, including power performance, the annual energy production, the capacity factor, the levelized cost of energy and the PTO fatigue loads. By comparing the results, this work identifies the uncertainties associated with different modeling approaches in evaluating WEC performance.

Fatigue↗
DOE OSTI2025

The levelized cost of exergy: a technoeconomic framework for energy system comparison

While the levelized costs of electricity and heat have been quantified before, these two metrics cannot be directly compared, due to the different exergy content of heat and work. To address this, we develop a levelized cost of exergy (LCOEx) framework that enables direct comparisons between energy sources and processes. We find that moderate- and high-grade heat have an LCOEx that is comparable to electricity (5–10 ¢ per kWh ex ), while low-grade heat sources have much higher LCOEx values (>50 ¢ per kWh ex ). The LCOEx of a system's output is affected by (i) the LCOEx of the system input, (ii) the CAPEX of the system, and (iii) the exergetic efficiency of the system. We use our framework to identify which processes are already achieved with relatively high cost effectiveness (production of fuels, hydrogen, and ammonia) and which have room for improvement (dehumidification, food production).

08 HYDROGEN↗
DOE OSTI2025

Characterization of Performance Degradation Mechanisms in Low-Cost High Throughput DI-O3 Layer for Passivated Contact Silicon Solar Cells

Characterization and mitigating performance limiting defects in Silicon (Si) PV is one of key areas to be addressed to improve PV hardware costs and energy yield in order to lower the levelized cost of energy (LCOE) of installed PV cost to $0.02/kWh. As Si PV cells efficiencies have surpassed 22% and approaching 23%, the recombination at the metal contacts have become the focus point to be addressed. Passivated contact technologies—having a heterojunction with a band-gap larger than silicon between the metal and silicon—have emerged as a great potential for future highand ultrahigh-efficiency solar cells, as it concurrently reduces recombination and increases carrier selectivity, by incorporating thin films within the contact structure. Passivated contact Si solar cell technologies use a wide variety of tunnel layers—playing a crucial role to passivate metal contacts and tunnel charge carriers—including stoichiometric silicon oxide (SiO 2 ) grown by thermal oxidation and Low-Pressure Chemical Vapor Deposition (LPCVD) technique and silicon oxide (SiO x ) by hot nitric acid. However, thorough investigations on understanding the failure and performance degradation mechanisms associated with tunnel layers are still limited to date. Unlocking those degradation characteristics in crucial tunnel layers could improve the reliability and energy yield of passivated contact Si solar cells. Besides, the technique of growing aforementioned tunneling layers are low throughput, and requires high temperature processes and/or a vacuum environment. In this project, we investigated the performance degradation mechanisms of a low-cost high-throughput ozonated oxide (DI-O 3 ) tunnel layer for the passivated contact Si solar cells.

14 SOLAR ENERGY↗
DOE OSTI2026

Advancing Concentrating Solar Thermal Modeling Using System Advisor Model (SAM)

Concentrating solar thermal (CST) technologies play a critical role in enabling dispatchable power and high-temperature industrial heat applications. Accurate and flexible modeling tools are essential for evaluating system performance, guiding technology research and development, and informing investment decisions. The National Laboratory of the Rockies's System Advisor Model (SAM) is a widely used techno-economic simulation platform for CST systems, providing detailed performance and financial modeling capabilities for multiple CST system configurations. SAM integrates physics-based performance models with financial analysis to simulate the behavior of complex energy systems under realistic operating conditions. For CST technologies (including tower, parabolic trough, and linear Fresnel), SAM enables hourly simulations using site-specific weather data that ensure feasible operating conditions and convergence of mass and energy between core system components (i.e., solar field, receiver, thermal energy storage, and power cycle). These capabilities allow researchers and developers to evaluate annual energy production, capacity factors, levelized cost of energy (LCOE), and system dispatch strategies. A key advantage of SAM lies in its flexibility for parametric analysis and large-scale computational studies. Users can vary system design parameters such as heliostat field layout, receiver dimensions, thermal energy storage capacity, power block sizing, and installation cost assumptions to investigate their impact on system performance and financial metrics. When combined with automated scripting through LK, SDKTool, or Python interfaces, SAM enables high-throughput simulation workflows that support sensitivity analysis, technology benchmarking, and optimization studies. These approaches are particularly valuable for next-generation CST concepts, where design spaces are large and system interactions are complex. Another important capability of SAM is its support for dispatch optimization and thermal energy storage modeling, which are central to the value proposition of CST technologies. The ability to simulate integrated storage and flexible power generation allows researchers to explore strategies that maximize grid value, improve capacity utilization, and enhance integration with variable resources such as photovoltaic and wind generation. This poster will present an overview of SAM's thermal system modeling capabilities including concentrating solar. Additionally, we will highlight new feature developments including: 1) implementing Google's OR-Tools optimization platform for faster and more robust dispatch optimization, 2) developing a new power load following controller for modeling behind-the-meter applications, 3) enabling direct modeling of CSP-PV hybrid systems with the inclusion of battery storage, and 4) developing a multi-receiver falling particle Gen3 system model.

14 SOLAR ENERGY↗
DOE OSTI2024

Consumer Benefits of Clean Energy: Energy Efficiency

Meeting national and state decarbonization goals requires a transition to clean energy technologies. Energy efficiency, demand flexibility, renewable energy and storage can reduce consumers’ electricity bills, lower total electricity system costs, and provide health and resilience benefits. Berkeley Lab developed a series of briefs that explore these consumer benefits of a clean energy transition. This brief focuses on energy efficiency benefits, and builds on prior analysis from Berkeley Lab’s Cost of Saved Energy database. We show that energy efficiency remains a low-cost energy and capacity resource; the levelized cost of saving energy for the programs included in the analysis is $\$0.02$/kilowatt-hour and the cost of saving peak demand is less $\$120$/kilowatt. Understanding the impact of the program mix, portfolio size, and duration of implementation for customer-funded energy efficiency portfolios can guide regulatory oversight of these programs, help utilities better utilize energy efficiency as a resource, and inform building energy decarbonization policies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Variable Curvature Pultruded Vertical Axis Wind Blades

XFlow Energy is developing a floating offshore vertical-axis wind turbine (VAWT) enabling a 70% reduction in the levelized cost of energy compared to floating horizontal-axis wind turbines (HAWTs). While the wind industry has historically been successful at lowering the cost of terrestrial wind systems, there are no scalable, economically viable floating wind solutions on the market with the levelized cost of energy (LCOE) of current floating offshore solutions is $200/MWh (Musial 2022). Low-cost blade production is one of the key technologies for realizing this target LCOE reduction. The proposed design uses a constant cross-section blade, enabling the use of pultrusion, a continuous, automated, mold-free production method. By employing blades with variable curvature, XFlow can minimize the bending stresses in the blades, allowing for light-weighting. Constant curvature pultrusion has been demonstrated on hollow sections. Variable curvature pultrusion has been demonstrated on solid sections. This project aims to develop a method of variable curvature pultrusion for hollow sections, as required for mass-optimal VAWT blades.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Variable Curvature Pultruded Vertical Axis Wind Blades

XFlow Energy is developing a floating offshore vertical-axis wind turbine (VAWT) enabling a 70% reduction in the levelized cost of energy compared to floating horizontal-axis wind turbines (HAWTs). While the wind industry has historically been successful at lowering the cost of terrestrial wind systems, there are no scalable, economically viable floating wind solutions on the market with the levelized cost of energy (LCOE) of current floating offshore solutions is $\$$200/MWh (Musial 2022). Low-cost blade production is one of the key technologies for realizing this target LCOE reduction. The proposed design uses a constant cross-section blade, enabling the use of pultrusion, a continuous, automated, mold-free production method. By employing blades with variable curvature, XFlow can minimize the bending stresses in the blades, allowing for light-weighting. Constant curvature pultrusion has been demonstrated on hollow sections. Variable curvature pultrusion has been demonstrated on solid sections. This project aims to develop a method of variable curvature pultrusion for hollow sections, as required for mass-optimal VAWT blades.

17 WIND ENERGY↗