ABSTRACT Wind power is a growing source of energy generation that relies on complex global atmospheric and earth system processes. 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 wind energy models with possible future system costs, turbine designs, and meteorological inputs from multiple downscaled earth system models over the contiguous United States. Changes in mean annual energy production from 2000–2019 to 2040–2059 can be as high as +10% in South Texas or as low as −20% in Iowa. Larger turbines and moderate reductions in system costs can offset the largest projected decreases in wind resource, but much uncertainty remains in the extent to which wind resources will change and to what extent system costs can be reduced. An analysis of variance shows, in several states in the Midwest, uncertainty in future wind resources can influence the cost of wind energy nearly as much as uncertainty in future system costs.

To achieve national decarbonization goals, U.S. annual deployment of wind energy will need to increase by at least fivefold compared to the recent past. Modeling and analysis frameworks can help inform where and how wind energy deployment might occur and thereby help enable the achievement of decarbonization goals. However, most prior wind energy modeling and analysis studies rely on generalized representations of wind energy technologies. Since wind energy technology advancements are expected to increase the competitiveness of wind energy, it is important to incorporate more detailed representations of turbine technology into wind energy modeling. Here we present a new method that incorporates wind turbine choice into the technology representation of land-based wind energy in long-term planning models. Our method integrates three previously published modeling and analysis capabilities: 1) bottom-up cost modeling to estimate future technology costs, 2) geospatial modeling to represent siting decisions, and 3) power sector modeling to evaluate potential deployment. We refer to this approach as a "customized turbine choice" methodology because it creates a composite turbine scenario by choosing from multiple wind turbine technologies - using site-specific optimized turbine layout and selecting the least-cost technology at each location. We demonstrate the capabilities of this new modeling pipeline by examining how the selection of four different wind turbine configurations might evolve from 2021 through 2040. Our results show that using our customized turbine choice methodology could lead to higher estimates for wind future deployment, which indicates that more simplified modeling might underestimate the role that wind energy could play in meeting decarbonization goals. Future research is needed to further explore the implications of turbine choice and to better inform technology researchers, original equipment manufacturers, and other wind industry stakeholders about the market potential of different wind turbine technologies.

Task 26 - 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.

This analysis uses representative utility-scale and distributed wind energy projects to estimate the levelized cost of energy (LCOE) for land-based, offshore, and distributed wind power in the United States. Data and results detailed here are derived from 2021 commissioned plants and representative industry data as well as state-of-the-art modeling capabilities. Modeling is conducted to provide more granular detail on specific cost categories. This study represents the 11th annual installment and is intended to provide insight into current component-level costs as well as a basis for understanding variability in wind energy LCOE across the country.

The 12th annual Cost of Wind Energy Review, now presented in slide deck format, uses representative utility-scale and distributed wind energy projects to estimate the levelized cost of energy (LCOE) for land-based and offshore wind power plants in the United States.

Wind energy is recognized worldwide as cost-effective and environmentally friendly and is among the fastestgrowing sources of electrical energy. To further decrease the cost of wind energy, wind turbines are being designed at ever larger scales, which is challenging due to greater structural loads and deflections. Large-scale systems such as modern wind turbines increasingly require a control co-design approach, whereby the system design and control design are performed in a more integrated fashion. We overview a two-bladed downwind morphing rotor concept that is expected to lower the cost of energy at wind turbine sizes beyond 13 megawatts (MW) compared with continued upscaling of traditional three-bladed upwind rotor designs. We describe an aero-structural-control co-design process that we have used in designing such extreme-scale wind turbines, and we discuss how we were able to achieve a 25% reduction in levelized cost of energy for our final turbine design compared to a conventional upwind three-bladed rotor design.

the sake of comparison (on a $/kW basis) to other wind turbine sizes. An alternative to the spread-foot foundation for residential-scale turbines is a slab foundation (large blocks), which is similar in price.

The costs of wind power have declined to levels on par with or below those of conventional sources in many parts of the world. Wind power has become one of the fastest-growing sources of new electricity generation. We take stock of wind power cost evolution over the past 20 years, review methodologies commonly used for cost assessment, discuss the potential for continued cost reduction, and identify anticipated cost and value drivers. Our scope includes both onshore and offshore wind technologies. We draw from a vast body of literature on these topics to highlight key trends, approaches, and limitations. Furthermore, we discuss strategies for wind power assets to enhance their marginal economic value to the broader power system and consumers. We identify a myriad of factors that are expected to influence the future cost and value of wind power, including siting, project scale, turbine size, operational synergies, commodity prices, advancements in turbine technologies, enhanced management of the wind resource, and novel control technologies that provide value for the electricity grid. Because the common methods for forecasting future costs each have their own strengths and weaknesses, we find the best insights are elicited from a combination of methods. Overall, researchers and analysts anticipate further sizable cost reductions for onshore and offshore wind. Midrange forecasts for levelized cost of energy in 2050 are generally between $20 and $30/MWh for onshore wind and $40 and $60/MWh for offshore wind, a reduction to approximately half of today's levels. Optimistic forecasts anticipate these levels as early as 2030. This article is categorized under: Wind Power > Economics and Policy

Consistent cost and performance data for various electricity generation technologies can be difficult to find and may change frequently for certain technologies. With the Annual Technology Baseline (ATB), the National Renewable Energy Laboratory annually provides an organized and centralized set of such cost and performance data. The ATB uses the best information from the Department of Energy national laboratories' renewable energy analysts. The ATB has been reviewed by experts and it includes the following electricity generation technologies: land-based wind, offshore wind, utility-scale solar photovoltaics (PV), commercial-scale solar PV, PV plus storage, residential-scale solar PV, concentrating solar power, geothermal power, hydropower, utility-scale battery storage, coal, and natural gas. EIA data for nuclear and conventional biopower are included for reference. This webinar presentation introduces the 2021 update to the ATB Electricity data and documentation.

This report uses representative utility-scale and distributed wind energy projects to estimate the levelized cost of energy (LCOE) for land-based and offshore wind power plants in the United States. Data and results detailed here are derived from 2020 commissioned plants and representative industry data as well as state-of-the-art modeling capabilities. Modeling is conducted to provide more granular detail on specific cost categories. This report represents the tenth annual installment and is intended to provide insight into current component-level costs as well as a basis for understanding variability in wind energy LCOE across the country.

This report uses representative utility-scale and distributed wind energy projects to estimate the levelized cost of energy (LCOE) for land-based and offshore wind power plants in the United States. Data and results detailed here are derived from 2019 commissioned plants and representative industry data as well as state-of-the-art modeling capabilities. Modeling is conducted to provide more granular detail on specific cost categories. This report represents the ninth annual installment and is intended to provide insight into current component-level costs as well as a basis for understanding variability in wind energy LCOE across the country.

Consistent cost and performance data for various electricity generation technologies can be difficult to find and may change frequently for certain technologies. With the Annual Technology Baseline (ATB), the National Renewable Energy Laboratory annually provides an organized and centralized set of such cost and performance data. The ATB uses the best information from the Department of Energy national laboratories' renewable energy analysts as well as information from the Energy Information Administration for fuel-based technologies. The ATB has been reviewed by experts and it includes the following electricity generation technologies: land-based wind, offshore wind, utility-scale solar photovoltaics (PV), commercial-scale solar PV, residential-scale solar PV, concentrating solar power, geothermal power, hydropower, utility-scale battery storage, coal, natural gas, nuclear, and conventional biopower. This webinar presentation introduces the 2019 ATB.

This report uses representative utility-scale projects to estimate the levelized cost of energy (LCOE) for land-based and offshore wind power plants in the United States. Data and results detailed here are derived from 2018 commissioned plants. Analysis detailed here relies on recent market data and state-of-the-art modeling capabilities to maintain an up-to-date understanding of wind energy cost trends and drivers. This report represents the eighth annual installment and is intended to provide insight into current component-level costs as well as a basis for understanding variability in LCOE across the country.

Consistent cost and performance data for various electricity generation technologies can be difficult to find and may change frequently for certain technologies. With the Annual Technology Baseline (ATB), the National Renewable Energy Laboratory annually provides an organized and centralized set of such cost and performance data. The ATB uses the best information from the Department of Energy national laboratories' renewable energy analysts as well as information from the Energy Information Administration for fuel-based technologies. The ATB has been reviewed by experts and it includes the following electricity generation technologies: land-based wind, offshore wind, utility-scale solar photovoltaics (PV), commercial-scale solar PV, residential-scale solar PV, concentrating solar power, geothermal power, hydropower, coal, natural gas, nuclear, and conventional biopower. This webinar presentation introduces the 2018 ATB.

The International Energy Agency Wind Technology Collaboration Programme (IEA Wind TCP) Task 26 - The Cost of Wind Energy represents an international collaboration dedicated to exploring the past, present, and future cost of wind energy. The countries that are currently represented by participating organizations in IEA Wind TCP Task 26 included in this report are Denmark, Germany, Ireland, Norway, Sweden, the European Union, and the United States. This report discusses trends from 2008 through 2016 that affected the cost of land-based wind energy in 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. This report builds from previous analysis conducted since the inception of Task 26 in 2009. Schwabe et al. (2011) explored differences in the cost of wind energy in 2008 among countries participating in Task 26 at that time. Vitina et al. (2015) presented turbine- and project-level trends in the wind industry from 2008 to 2012, including wind project size, turbine size, specific power and hub height, project performance, investment costs, operation and maintenance (O&M) costs, and project financing. These inputs are used to calculate the levelized cost of energy (LCOE), a widely recognized metric for understanding how technology performance, capital investment, operations, and financing impact the life cycle cost of building and operating a wind project. Both prior reports - as well as this report - used this metric to estimate the cost of wind energy.