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Assessment of the Economic Potential of Distributed Wind in Colorado, Minnesota, and New York
This work seeks to identify current and future spatial distributions of economic potential for behind-the-meter distributed wind, serving primarily rural or suburban homes, farms, and manufacturing facilities in Colorado, Minnesota, and New York. These states were identified by technical experts based on their current favorability for distributed wind deployment. We use NREL's Distributed Wind Market Demand Model (dWind) (Lantz et al. 2017; Sigrin et al. 2016) to identify and rank counties in each of the states by their overall and per capita potential. From this baseline assessment, we also explore how and where improvements in cost, performance, and other market sensitivities affect distributed wind potential.
Interactions of Wind Energy Project Siting, Wind Resource Potential, and the Evolution of the U.S. Power System
The interactions of wind energy project siting, resource potential, and power system evolution are critical to understand given interest in high renewable energy systems, particularly as wind costs have fallen and grid operators implement solutions to manage variable generation. This study applies an integrative approach that combines spatially-explicit resource potential analysis with high spatial resolution U.S. electricity system modeling. Multiple wind supply curves, representing variations in siting regimes that account for interactions with built infrastructure, regulatory, physical, and social land use factors, are evaluated to determine how siting could influence prospective wind development. Different siting regimes lead to variations in future wind capacity, with the greatest impacts observed under scenarios with high demand for clean energy. With the tightest emissions limit modeled, 2050 onshore wind capacity varied by +7% (49 GW) in the least-restrictive siting regime to a decrease of 37% (270 GW) under the most-constrained case. More-stringent siting restrictions lead to higher electricity prices and emissions that should be weighed with local impacts. Under restrictive siting regimes, wind deployment is also sensitive to transmission availability and wind plant design. Overall, the findings highlight the importance of local land use considerations in regional and national power system planning.
2016-2017 Status Assessment and Update on the Wind Vision Roadmap: Findings from Topical Working Sessions, April 2016 - March 2017
IIn March 2015, the U.S. Department of Energy (DOE) released Wind Vision: A New Era for Wind Power in the United States (DOE 2015), which explores a scenario in which wind provides 10 percent of U.S. electricity in 2020, 20 percent in 2030, and 35 percent in 2050. The Wind Vision report also includes a roadmap of recommended actions aimed at pursuit of the vision and its underlying wind-deployment scenario. The roadmap was compiled by the Wind Vision project team, which included representatives from the industrial, electric-power, government-laboratory, academic, environmental-stewardship, regulatory, and permitting stakeholder groups. The roadmap describes high-level activities suitable for all sectors with a stake in wind power and energy development. It is intended to be a 'living document,' and DOE expects to engage the wind community from time to time to track progress.
Extreme Wind and Waves in U.S. East Coast Offshore Wind Energy Lease Areas
The Outer Continental Shelf along the U.S. east coast exhibits abundant wind resources and is now a geographic focus for offshore wind deployments. This analysis derives and presents expected extreme wind and wave conditions for the sixteen lease areas that are currently being developed. Using the homogeneous ERA5 reanalysis dataset it is shown that the fifty-year return period wind speed (U50) at 100 m a.s.l. in the lease areas ranges from 29.2 to 39.7 ms -1 . After applying corrections to account for spectral smoothing and averaging period, the associated pseudo-point U50 estimates are 34 to 46 ms -1 . The derived uncertainty in U50 estimates due to different distributional fitting is smaller than the uncertainty associated with under-sampling of the interannual variability in annual maximum wind speeds. It is shown that, in the northern lease areas, annual maximum wind speeds are generally associated with intense extratropical cyclones rather than cyclones of tropical origin. Extreme wave statistics are also presented and indicate that the 50-year return period maximum wave height may substantially exceed 15 m. From this analysis, there is evidence that annual maximum wind speeds and waves frequently derive from the same cyclone source and often occur within a 6 h time interval.
Atmosphere to Electrons: Enabling the Wind Plant of Tomorrow
The U.S. Department of Energy’s (DOE’s) Atmosphere to Electrons (A2e) research initiative is focused on improving the performance and reliability of wind plants by establishing an unprecedented understanding of how the Earth’s atmosphere interacts with the wind plants and developing innovative technologies to maximize energy extraction from the wind. The A2e initiative pursues an integrated research portfolio to coordinate and optimize advancements in four main research areas: 1) plant performance and financial risk assessment, 2) atmospheric science, 3) wind plant aerodynamics, and 4) next-generation wind plant technology. It offers an integrated systems approach to developing the next generation of System Management of the Atmospheric Resource by Turbines (SMART) wind plant technologies necessary to increase wind deployment.
A systematic evaluation of wind's capacity credit in the Western United States
Abstract The degree to which wind energy can contribute to the capacity needed to meet resource adequacy requirements, also known as capacity credit (CC), can be impacted by many factors. The CC varies regionally with wind resource and correlation to net load and may also vary with wind technology (land‐based versus offshore) and turbine specifications. We use a probabilistic resource adequacy tool to systematically assess the CC of multiple technologies for near‐term wind deployment across the Western US power system to help inform planning decisions. We find that wind CC varies by weather year and location but averages 16% for land‐based turbines and 41% for offshore turbines, with large regional variations. The average wind CC increases to 20% for land‐based and 53% for offshore when considering only the sites in the top 25th percentile of capacity factor. The CC of land‐based wind is generally lower than its capacity factor, which indicates a low correlation of generation to system needs. However, offshore wind shows a substantially higher CC, which is driven by not only a higher capacity factor but also a greater correlation with system needs.
Impacts of turbine and plant upsizing on the levelized cost of energy for offshore wind
Turbine and plant upsizing are major trends in offshore wind deployment, although the quantitative impact on project costs has not been well-characterized. The uncertain value of continued wind turbine and project growth limits the ability of the supply chain to prepare for future technology trends, leading to challenges in the realization of larger projects. This analysis explores the levelized cost of energy impacts of turbine ratings between 6 and 20 MW and plant capacities between 250 and 2,500 MW for fixed-bottom offshore wind using techno-economic cost models for foundation, electrical, installation, and operation and maintenance costs, along with annual energy production. We consider a nominal set of technology assumptions for all scenarios to isolate economies of size and scale without additional benefits from decreasing turbine capital costs, quantity discounts for larger projects, or optimized technology solutions. These results indicate that using a 20-MW wind turbine in a 2,500-MW power plant array can reduce the levelized cost of energy by over 23% relative to the global average turbine and plant size installed in 2019; primarily because of reductions in the balance-of-system and operation and maintenance costs. We also identify improved installation vessels, optimized export systems, and novel operation and maintenance strategies as additional cost reduction opportunities. These results suggest that upsizing represents a significant cost reduction opportunity for offshore wind energy and will continue to be a main factor in shaping the future of the sector.
Wake Effects in Lower Carbon Future Scenarios
In August 2022, the U.S. Congress passed the Inflation Reduction Act (IRA), which intended to accelerate U.S. decarbonization, clean energy manufacturing, and deployment of new power and end-use technologies. The National Renewable Energy Laboratory has examined possible scenarios for growth by 2050 resulting from the IRA and other emissions reduction drivers and defined several possible scenarios for large-scale wind deployment. These scenarios incorporate large clusters of turbines operating as wind farms grouped around existing or likely transmission lines which will result in wind farm wakes. Using a numerical weather prediction (NWP) model, we assess these wake effects in a domain in the U. S. Southern Great Plains for a representative year with four scenarios in order to validate the simulations, estimate the internal wake impact, and quantify the cluster wake effect. Herein, we present a validation of the ”no wind farm” scenario and quantify the internal waking effect for the ”ONE” wind farm scenario. Future work will use the “MID” scenario (more than 8000 turbines) and the “HI” scenario (more than 16,000 turbines) to quantify the effect of cluster wakes or inter-farm wakes on power production.
Texturizing Wind Turbine Towers to Reduce Bat Mortality
There is still a great need for the development of mitigation strategies that are economically viable and can be used alone or in combination with other options (e.g., operational minimization, acoustic deterrents) to ensure that bat fatalities are effectively reduced at wind facilities across the U.S. Our goal was to develop a wind turbine tower coating that 1) bats show little or no interest in approaching, 2) can be applied to currently deployed wind turbine towers and to towers as they are constructed, 3) is economically feasible to produce and apply, and 4) ultimately contributes to a reduction in bat mortality at utility-scale wind facilities. Wind turbine tower monopoles are large, smooth surfaces and numerous studies have reported bats making close investigative approaches at turbine tower surfaces that are suggestive of drinking and foraging behavior. We therefore hypothesized that such activity could be contributing to bat-wind turbine fatalities by increasing the amount of time that bats spend in or around the rotor-swept zone. We further hypothesized that a texturizing the tower might minimized bat activity at the towers and therefore reduce fatality risk. To explore this, we designed a series of experiments to characterize how bats interact with smooth and texture-treated surfaces in a controlled environment. We conducted 64 behavioral trials in a flight facility from 10 June to 25 September 2015 and an additional 76 behavioral trials from 9 June to 30 August 2016. The first set of trials showed that while bats did make contact with smooth surfaces, they did not make contact with textured surfaces. We ascertained that bat activity occurred at 0 to 1 m distances from surfaces, suggesting that the bats (used in this study) may need to be this close to a surface to accurately discern its texture. From the results were developed a texture coating. For the second set of trials, we tested the texture coating. Bats showed a >40% reduction in activity within 1 m of the textured surfaces in comparison to the smooth surfaces. Following these controlled experiments, we conducted field tests at Wolf Ridge Wind, LLC. We applied the texture coating to the midsection of turbine monopoles. The texture coating was manually applied to 2 turbine towers, although we noted during the application there was variation in texture coating between turbines. We considered that this variation could potentially impact bat behavior. We then conducted bat activity surveys at both texture-treated towers and 2 nearby control towers, over 55 nights from 24 June to 22 September, 2017. All species of bats known to be present at the site were detected in the acoustic recordings at these turbine towers. We found no significant differences in overall numbers of bats observed and levels of acoustic activity at the smooth and texture-treated towers. When we analyzed the experimental pairs separately, however, we found that a greater proportion of the close range bat activity within Pair 1 occurred at the texture-treated tower and that much of this activity could be attributed to foraging behavior. In contrast at turbine Pair 2, we observed no difference in the proportion of close range bat activity between the smooth and texture-treated tower, with no clear differences in behavior at the two tower types. When we examined acoustic bat activity at the tower pairs separately, we found species-specific differences in activity that differed between the smooth and texture-treated towers within the pairs. For example, hoary bat acoustic activity was significantly higher at the texture-treated tower in Pair 1, but significantly lower at the texture-treated tower in Pair 2. Given the observational nature of the field test, our limited sample size (2 turbine pairs), variation in the texture-coating between the 2 turbine pairs, and different patterns of bat activity observed at the 2 turbine pairs, inferences from this one field test are limited at best. In conclusion, the results from the flight facility experiments were promising (i.e., we observed a significant decrease in bat activity at smooth compared to texture-treated surfaces); however, due to coating installation and application challenges prior to our field test, we were unable to collect sufficient information to understand how these coatings affect bat activity at operational wind turbine towers. Although the results from the field test are inconclusive, the lessons learned will be informative for future research into turbine surface materials that can modify the surface of the turbine tower and therefore alter how bats perceive wind towers. Thus, the outcomes of this research project may have a significant impact on wind energy operators, wind developers, and OEMs by contributing to future impact mitigation strategies. In future research we will test new ideas to improve the development, application, and evaluation of this mitigation technique.
Turbine scale and siting considerations in wind plant layout optimization and implications for capacity density
Improvements in wind energy technology, reduced costs, and ambitious clean energy goals have led to projections of high wind contribution in coming years. Developing methodologies to design wind plants with a variety of siting constraints and turbine sizes helps enable high wind penetration, and gain a better understanding of how wind plants are sensitive to setback constraints and turbine design. In this paper, we present a two-step optimization method to simultaneously determine the optimal number of turbines and their locations in a wind plant domain divided into many small, discrete parcels. We present the optimized performance metrics of a wind plant optimized with different turbine sizes and ratings, and with different siting restrictions within the wind plant. Our results indicate that taller and larger turbines are more sensitive to increasing siting constraints. We also compare the optimal wind plant layouts and performance for wind plants optimized for minimum COE and maximum profit. Wind plants optimized for profit had 130%-190% of the capacity of plants optimized for COE, which demonstrates that the optimal results are greatly affected by the objective function, which should be carefully considered. Finally, in this paper we demonstrate the effect of increasing siting constraints on wind plant capacity density, and how the results change when different land areas are used to calculate capacity density. When using the entire wind plant boundary area to determine capacity density, increasing siting constraints decreases the capacity density. However, when we only use the available area (the area left after removing the siting constraints) to calculate the capacity density, increasing the siting constraints increases capacity density. This is a critical insight because of how capacity density is typically defined and used in research, and has important implications for assessment of technical potential and capacity expansion modeling, as well as future wind deployment potential.
Microgrids, Infrastructure Resilience, and Advanced Controls Launchpad (MIRACL) Research: Controls
Advanced Turbine Control for Distributed Wind Deployments: The Microgrids, Infrastructure Resilience, and Advanced Controls Launchpad (MIRACL) research initiative is funded by the U.S. Department of Energy’s Wind Energy Technologies Office and led by researchers at the National Renewable Energy Laboratory (NREL) and Sandia National Laboratories (Sandia). The initiative’s controls research seeks to expand the benefits from distributed wind energy assets beyond solely providing low-cost power directly to consumers. To make these turbines operate more effectively, there is a need for more advanced ways to control them—allowing power companies, businesses, and energy consumers to take advantage of some of the unique technical characteristics of wind energy.
Offshore Wind Energy Resource Assessment for Alaska
This report quantifies Alaska's offshore wind resource capacity while focusing on its unique nature. It is a supplement to the existing U.S. Offshore Wind Resource Assessment, which evaluated the offshore wind resource for all other U.S. states. Together, these reports provide the foundation for the nation's offshore wind value proposition. Both studies were developed by the National Renewable Energy Laboratory. The analysis presented herein represents the first quantitative evidence of the offshore wind energy potential of Alaska. The technical offshore wind resource area in Alaska is larger than the technical offshore resource area of all other coastal U.S. states combined. Despite the abundant wind resource available, significant challenges inhibit large-scale offshore wind deployment in Alaska, such as the remoteness of the resource, its distance from load centers, and the wealth of land available for onshore wind development. Throughout this report, the energy landscape of Alaska is reviewed and a resource assessment analysis is performed in terms of gross and technical offshore capacity and energy potential.
Comparing Capacity Credit Calculations for Wind: A Case Study in Texas
The degree to which wind energy can contribute to the capacity needed to meet resource adequacy requirements, also known as capacity credit (CC), varies regionally with wind resource and correlation to net load. CC is an important metric widely used for resource planning and resource adequacy assessments. However, there are multiple methods for computing and estimating CC, depending on specific needs, access to data, and computational burden. It is unclear the extent to which the CC computation method may influence the result. To address this, we use a probabilistic resource adequacy tool and multiple approximation methods to systematically assess the CC of wind for near-term wind deployment under a case study in Texas. We find that proper consideration of transmission constraints is important; some approximation methods may overestimate the CC of wind due to a lack of consideration of transmission constraints, while other approximation methods may underestimate the CC by not capturing the ability of wind to be shipped to neighboring regions. In this case study, we find that several approximation methods do come close to the CC calculated by more robust probabilistic methods. However, the best approximation method may vary on a case-by-case basis, depending on system-specific considerations.
Feasibility Assessment and Preliminary Design of a Low Cost, Modular Concrete, Suction Pile Support Structure and Heavy Lift Vessel Alternative (CRADA Final Report)
The project goal is to prove the feasibility and advance the development of a low-cost, modular concrete suction pile support structure and heavy lift vessel alternative for offshore wind deployment in the United States. These technology developments are critical to alleviating specific challenges faced by the United States market, including a limited number of Jones Act-compliant installation vessels and environmental restrictions associated with using conventional offshore wind foundations. The first phase of this project is a conceptual design and feasibility assessment of modular concrete substructure options for NREL’s 15 MW reference turbine.
Land-Based Wind Market Report: 2024 Edition
Wind power additions in the United States totaled 6.5 gigawatts (GW) of capacity in 2023. 1 Wind power growth has historically been supported by the industry’s primary federal incentive—the production tax credit (PTC)—as well as numerous state-level policies. Long-term improvements in the cost and performance of wind power technologies have also been key drivers for wind additions, yielding low-priced wind energy for utility, corporate, and other power purchasers. Nonetheless, 2023 was a slow year in terms of new wind deployment, the lowest since 2014. Elevated interest rates played a role in slowing deployment, as did interconnection and siting challenges.
Offshore Wind Composite Siting Exclusions Scenarios
This dataset consolidates criteria that restrict the siting of offshore wind energy installations, an update from Zuckerman et al. (2023). All scenarios exclude area from wind energy development due to legal or administrative restrictions (e.g., Marine Protected Areas), existing infrastructure, and technical constraints (e.g., 1,300 m bathymetry limit). A TIF data file and a PNG cartographic map of the data are provided for three scenarios ("Open", "Reference", and "Limited"), showing areas where offshore wind energy is restricted across the contiguous United States. The "Open" scenario only excludes areas with known preclusions for offshore wind deployment. The "Reference" scenario excludes all areas from the "Open" scenario, as well as additional best management practices such as known proposed protected areas, and state waters. The "Limited" scenario excludes all area from the "Reference" scenario. Additionally, it has more stringent siting criteria such as larger setbacks from shore and infrastructure, as well as shallower depth limits on floating technology. For further details and citation, please refer to the publication linked below: Zuckerman, Gabriel R., Anthony Lopez, Travis Williams, Rebecca Green, and Grant Buster. 2023. Impacts of Siting Considerations on Offshore Wind Technical Potential in the United States. Golden, CO: National Renewable Energy Laboratory. NREL/TP-6A20- 85088.
How low can you go? The importance of quantifying minimum generation levels for renewable integration
One of the significant limitations of solar and wind deployment is declining value caused by the limited correlation of renewable energy supply and electricity demand as well as limited flexibility of the power system. Limited flexibility can result from thermal and hydro plants that cannot turn off or reduce output due to technical or economic limits. These limits include the operating range of conventional thermal power plants, the need for process heat from combined heat and power plants, and restrictions on hydro unit operation. To appropriately analyze regional and national energy policies related to renewable deployment, these limits must be accurately captured in grid planning models. In this work, we summarize data sources and methods for U.S. power plants that can be used to capture minimum generation levels in grid planning tools, such as production cost models. We also provide case studies for two locations in the U.S. (California and Texas) that demonstrate the sensitivity of variable generation (VG) curtailment to grid flexibility assumptions which shows the importance of analyzing (and documenting) minimum generation levels in studies of increased VG penetration.