The 2019 ATB characterization for land-based wind updates the Base Year and future wind technology cost and performance estimates from years past to align with current expectations for wind energy costs over the coming decades. This year's ATB characterization for land-based wind relies on a new bottoms-up engineering approach for 2030 turbine and plant technology that is used to inform cost and performance characterizations through 2030. This new approach was developed based on persistent feedback since the release of the Wind Vision report (DOE & NREL, 2015) and the System Management of Atmospheric Resource through Technology (SMART) strategies wind plant analysis (Dykes et al., 2017) , from the wind industry original equipment manufacturer (OEM) and stakeholder community that noted the wind ATB mid case assumptions to be overly conservative. Based on this feedback and observations of substantial technology gains in recently commercialized turbine offerings an array of industry experts now anticipate wind energy LCOEs of 2-2.5 cent/kWh by the mid-2020s, depending on specific financing terms and conditions. In terms of technology gains, the most noteworthy has been the substantial and rapid scaling of wind turbines from the 2-MW to 4-MW with increases in rotor size from approximately 100 m to 150 m. These gains in scale are allowing modern technology to capture turbine level economies of scale and balance of plant efficiencies while placing the turbine in better resource regimes at greater heights above ground level.
To better align with the OEM and industry stakeholder cost reduction expectations NREL redefined the methodology used for estimating future energy costs. Specifically, for this year's ATB NREL used expert input to define one of many potential turbine technology pathways for a Mid and Low scenario in 2030. Bottom-up engineering cost and performance analysis were then executed to obtain the future cost reduction trajectories (Stehly, Beiter, Heimiller, & Scott, 2020) . Although this method has resulted in a cost reduction pathway that maintains and could even accelerate recent significant cost reduction gains, these results are believed to be more in line with wind industry analyst and OEM expectations. There is substantial focus throughout the global wind industry on driving down costs and increasing performance due to fierce competition from within as well as among several power generation technologies including solar PV and natural gas-fired generation.
Representative technologies for land-based wind for the base year (2017) and 2030 assume a 50-MW to 100-MW facility, consistent with current project sizes (Wiser & Bolinger, 2018) . Our base year characterization is extracted from wind turbines installed in the United States in 2017 which were, on average, 2.3-MW turbines with rotor diameters of 113 m and hub heights of 86 m (Wiser & Bolinger, 2018) . Our 2030 representative technology assumes a 4.5-MW turbine with a rotor diameter of 167 m and a hub height of 110 m. Notably turbines that are nearly of this scale (i.e., 4-MW, 150 m rotor and 80-m to 110-m hub height are commercially available today and expected to be installed in facilities in the U.S. in the early 2020s.
Wind resource is prevalent throughout the United States but is concentrated in the central states. Total land-based wind technical potential exceeds 10,000 GW (almost tenfold current total U.S. electricity generation capacity), which would use the wind resource on 3.5 million km2 of land area but would disrupt or exclude other uses from a fraction of that area. This technical potential does not include standard exclusions-lands such as federally protected areas, urban areas, and water. Resource potential has been expanded from approximately 6,000 GW (DOE & NREL, 2015) by including locations with lower wind speeds to provide more comprehensive coverage of U.S. land areas where future technology may improve economic potential.
Renewable energy technical potential, as defined by Lopez et al. (2012) , represents the achievable energy generation of a particular technology given system performance, topographic limitations and environmental and land-use constraints. The primary benefit of assessing technical potential is that it establishes an upper-boundary estimate of development potential. It is important to understand that there are multiple types of potential, including resource, technical, economic, and market potential (see NREL: "Renewable Energy Technical Potential").
The resource potential is calculated by using more than 130,000 distinct areas for wind plant deployment that cover more than 3.5 million km2. The potential capacity is estimated to total more than 10,000 GW if a power density of 3 MW/km2 is assumed.
For each of the 130,000 distinct areas, an LCOE is estimated taking into consideration site-specific hourly wind profiles. Representative wind turbines derived from annual installation statistics are associated with a range of average annual wind speed based on actual historical wind plant installations. This method is described by Moné (2017) and summarized below:
For representation in the ATB, the full resource potential, reflecting the 130,000 individual areas, was divided into 10 techno-resource groups (TRGs). The capacity-weighted average CAPEX, O&M, and capacity factor for each group is presented in the ATB. ATB Base Year costs for land-based wind are calibrated to NREL's 2017 Cost of Wind Energy Review (Stehly, Beiter, Heimiller, & Scott, 2018).
Focusing on future costs, this year's ATB characterization represents an update relative to years past in order to realign with current expectations for costs over the next decade. Three different projections were developed for scenario modeling as bounding levels:
In last year's ATB, the mid case cost projections were informed by the expert survey that reported expected LCOE changes in percentage terms relative to 2014 baseline values (Wiser et al., 2016) . Prior mid case projections were estimated using the entire sample size from the survey work (163 experts) which included strategic, system-level thought leaders with wind technology, costs, and/or market expertise. However, the survey also identified a smaller group – deemed "leading experts" through a deliberative process by a core group of International Energy Agency (IEA) Wind Task 26 members. This leading experts group (22 leading experts) generally expected more aggressive wind energy cost reductions. Recent wind industry data focused on price points more than 3-5 years into the future indicate that costs are falling more quickly than the full sample predicted and more in line with the leading Experts predictions. This year's ATB mid case is informed both by this leading group of experts' predictions as well as the expert input and bottom-up engineering pathways analysis referenced previously.
The Low case is primarily informed by the wind program's Atmosphere to Electrons (A2e) applied research initiative that advances the fundamental science necessary to drive innovation and the realization of the SMART wind power plant of the future (Dykes et al., 2017) . This research in addition to ongoing Wind Energy Technologies Office (WETO) projects including Big Adaptive Rotors (DOE, 2018) , Lightweight Drivetrains (DOE EERE, 2019) , and Tall Towers (2019 Wind Energy Technologies Office Funding Opportunity Announcement, 2019) support the wind industry's ongoing scaling activities and manufacturing improvements and were combined to assess additional potential pathways and related projected cost impacts for each LCOE component.
As done in the expert survey work (Wiser et al., 2016) historical LCOE estimates were compared to the LCOE projections of the Mid and Low scenarios. The LCOE projections were found to require continued sizable cost reductions consistent with and potentially somewhat greater than the historical LCOE trends. Possible justifications for maintaining recent rates of high cost reduction and potentially even going beyond long-term historical LCOE learning include stiff competition from around the globe as well as a highly capitalized industry with annual expenditures on the order of $100 billion. Accordingly, the revised Mid scenario is now considered representative of the reference case for land-based wind. The Low cost scenario projections are derived from the same methodology as the Mid case but applying additional cost reduction potentials from a collection of intelligent and novel technologies that comprise next-generation wind turbine and plant technology and characterized as System Management of Atmospheric Resource through Technology, or SMART strategies (Dykes et al., 2017) . In both scenarios, the overall LCOE reductions resulting from these analyses were used as the basis for the ATB projections. Accordingly, all three cost elements – CAPEX, O&M, and capacity factor – should be considered together; individual cost element projections are derived.
Capital expenditures (CAPEX) are expenditures required to achieve commercial operation in a given year. These expenditures include the wind turbine, the balance of system (e.g., site preparation, installation, and electrical infrastructure), and financial costs (e.g., development costs, onsite electrical equipment, and interest during construction) and are detailed in CAPEX Definition. In the ATB, CAPEX reflects typical plants and does not include differences in regional costs associated with labor, materials, taxes, or system requirements. The related Standard Scenarios product uses Regional CAPEX Adjustments. The range of CAPEX demonstrates variation with wind resource in the contiguous United States.
The CAPEX improvements for future land-based wind projects may be realized through many technology pathways to achieve LCOE reductions. It is also important to note that CAPEX improvements are not the only pathway to LCOE reductions as LCOE is also influenced by capacity factor, financing, O&M, and project life. For the purpose of reducing the vast combinations of future pathways NREL analysts defined a single future turbine configuration in 2030 to conduct the bottom-up cost analysis for the Mid and Low scenarios. The specific 2030 turbine configuration for the Mid scenario assumes a nameplate capacity of 4.5 MW with a rotor diameter of 167 m placed on a 110 m tower. Additional turbine configurations explored that resulted in LCOEs that were within 10% (or less) of the current Mid scenario included turbines with nameplate capacity ratings of 3-MW and 4-MW, rotor diameters down to 150 m, and hub heights up to 140 m. The relatively low sensitivity of LCOE to these changes in turbine configuration is indicative of the array potential pathways and solutions to the LCOE values estimated in this year's ATB.
The defined turbine characteristics were then used to estimate the total system CAPEX of a theoretical commercial scale (e.g., 100-MW) project. Although the relatively low observed sensitivity to significantly different turbine configurations for a single reference site indicate some uncertainty need for and value of wind turbine tailoring for varied site conditions, it is generally expected that over the long-term wind turbine designs will be optimized for a specific plant's site conditions. In this year's ATB, this site-specific design optimization process which is often reflected in different CAPEX values across TRGs was not included. Instead we assumed the single turbine configuration across all 10 TRGs. This simplification was applied due to limited resources and lack of necessary data to robustly characterize CAPEX variation across the 10 TRGs. Nevertheless, the ability to assess and tailor turbine configurations and CAPEX estimates for each TRG is expected to be reimplemented in future iterations of the ATB.
Capital expenditures (CAPEX) are expenditures required to achieve commercial operation in a given year.
For the ATB, and based on a capital cost estimates report from EIA (2016) and the System Cost Breakdown Structure defined by Moné et al. (2015), the wind plant envelope is defined to include:
CAPEX can be determined for a plant in a specific geographic location as follows:
Regional cost variations and geographically specific grid connection costs are not included in the ATB (CapRegMult = 1; GCC = 0). In the ATB, the input value is overnight capital cost (OCC) and details to calculate interest during construction (ConFinFactor).
ATB CAPEX, O&M, and capacity factor assumptions for the Base Year and future projections through 2050 for Constant, Mid, and Low technology cost scenarios are used to develop the NREL Standard Scenarios using the ReEDS model. See ATB and Standard Scenarios.
CAPEX in the ATB does not represent regional variants (CapRegMult) associated with labor rates, material costs, etc., but the ReEDS model does include 134 regional multipliers (EIA, 2016).
The ReEDS model determines the land-based spur line (GCC) uniquely for each of the 130,000 areas based on distance and transmission line cost.
Operations and maintenance (O&M) costs depend on capacity and represent the annual fixed expenditures required to operate and maintain a wind plant, including:
The following figure shows the Base Year estimate and future year projections for fixed O&M (FOM) costs. Three cost scenarios are represented. The estimate for a given year represents annual average FOM costs expected over the technical lifetime of a new plant that reaches commercial operation in that year.
The FOM of $44/kW-yr in the Base Year was estimated in the 2017 Cost of Wind Energy Review (Stehly, Beiter, Heimiller, & Scott, 2018); no variation of FOM with TRG (or wind speed) was assumed. The following chart shows sample historical data for reference.
Future FOM is assumed to decline by approximately 25% by 2050 in the Mid case and 45% in the Low case. These values are informed by recent work benchmarking work for wind power operating costs in the United States (Wiser, Bolinger, & Lantz, 2019).
A detailed description of the methodology for developing future year projections is found in Projections Methodology.
Technology innovations that could impact future O&M costs are summarized in LCOE Projections.
The capacity factor represents the expected annual average energy production divided by the annual energy production, assuming the plant operates at rated capacity for every hour of the year. It is intended to represent a long-term average over the lifetime of the plant. It does not represent interannual variation in energy production. Future year estimates represent the estimated annual average capacity factor over the technical lifetime of a new plant installed in a given year.
The capacity factor is influenced by hourly wind profile, expected downtime, and energy losses within the wind plant. The specific power (ratio of machine rating to rotor swept area) and hub height are design choices that influence the capacity factor.
The following figure shows a range of capacity factors based on variation in the resource for wind plants in the contiguous United States. Historical data from wind plants operating in the United States in 2015, according to the year in which plants were installed, is shown for comparison to the ATB Base Year estimates. The range of Base Year estimates illustrate the effect of locating a wind plant in sites with high wind speeds (TRG 1) or low wind speeds (TRG 10). Future projections are shown for Constant, Mid, and Low technology cost scenarios.
Actual energy production from about 90% of wind plants operating in the United States since 2007 is shown in box-and-whiskers format for comparison with the ATB current estimates and future projections. The historical data illustrate capacity factor for projects operating in 2017, shown by year of commercial online date. As reported in the 2017 DOE Wind Technologies Market Report (Wiser & Bolinger, 2018).
Most installed U.S. wind plants generally align with ATB estimates for performance in TRGs 5-7. High wind resource sites associated with TRGs 1 and 2 as well as very low wind resource sites associated with TRGs 8-10 are not as common in the historical data, but the range of observed data encompasses ATB estimates.
To calculate the Base Year capacity factors the 2017 turbine characteristics (Wiser & Bolinger, 2018) are input into the System Advisor Model, or SAM and run for each of the weighted average wind speeds in each TRG.
The capacity factor is referenced to an 80-m, above-ground-level, long-term average hourly wind resource data from AWS Truepower (2012).
Projections for capacity factors implicitly reflect technology innovations such as larger rotors and taller towers that will increase energy capture at the same location (without specifying precise tower height or rotor diameter changes). Improvements in plant performance through lower losses and increased availability are also included implicitly. In practice future turbine designs will be optimized for a specific site with attempts to maximize capacity factor. This optimization is not captured in this analysis since one turbine configuration is defined for each of the TRGs. Analysts hope to enhance the ability to define site-specific turbine configurations for each TRG in future iteration of the ATB.
Increased energy capture through turbine scaling and wind plant optimization are the two primary factors influencing wind plant capacity factor. The introduction of novel control mechanisms will continue to increase energy capture with more-precise control of the flow through the entire wind plant. These technology advancements are expected to increase capacity factor for all TRGs, with a more rapid rate of increases in capacity factor through 2030 and a slower rate of increase through 2050. This analysis is illustrative of one of many capacity factor improvement pathways for LCOE reduction. Of course, as was the case for CAPEX there are many different pathways to a given capacity factor. Turbine rotor diameter, specific power, and hub height can each be traded off to achieve a given capacity factor, depending on site conditions and relative costs for pursuing one approach or the other; plant layout and operational strategies that impact losses are additional levers that may be used to achieve a given capacity factor.
A detailed description of the methodology for developing future year projections is found in Projections Methodology.
Technology innovations that could impact future O&M costs are summarized in LCOE Projections.
ATB CAPEX, O&M, and capacity factor assumptions for the Base Year and future projections through 2050 for Constant, Mid, and Low technology cost scenarios are used to develop the NREL Standard Scenarios using the ReEDS model. See ATB and Standard Scenarios.
The ReEDS model output capacity factors for wind and solar PV can be lower than input capacity factors due to endogenously estimated curtailments determined by scenario constraints.
ATB projections were derived from two different sources for the Mid and Low cases:
Projections of the cost of wind energy from the literature provide context for the ATB Constant, Mid, and Low technology cost projections. The ATB Mid cost projection results in LCOE reductions that are higher than other scenarios that are in median range of the literature ((Shreve, 2018), (BNEF, 2018)), and lower than ((Kost, Shammugam, Julch, Huyen-Tran, & Schlegl, 2018), (Wiser et al., 2016)). The ATB Low cost projection, which corresponds to the NREL bottom-up cost analysis, is relatively in line with the leading experts prediction (Wiser et al., 2016).
Levelized cost of energy (LCOE) is a summary metric that combines the primary technology cost and performance parameters: CAPEX, O&M, and capacity factor. It is included in the ATB for illustrative purposes. The ATB focuses on defining the primary cost and performance parameters for use in electric sector modeling or other analysis where more sophisticated comparisons among technologies are made. The LCOE accounts for the energy component of electric system planning and operation. The LCOE uses an annual average capacity factor when spreading costs over the anticipated energy generation. This annual capacity factor ignores specific operating behavior such as ramping, start-up, and shutdown that could be relevant for more detailed evaluations of generator cost and value. Electricity generation technologies have different capabilities to provide such services. For example, wind and PV are primarily energy service providers, while the other electricity generation technologies provide capacity and flexibility services in addition to energy. These capacity and flexibility services are difficult to value and depend strongly on the system in which a new generation plant is introduced. These services are represented in electric sector models such as the ReEDS model and corresponding analysis results such as the Standard Scenarios.
The following three figures illustrate LCOE, which includes the combined impact of CAPEX, O&M, and capacity factor projections for land-based wind across the range of resources present in the contiguous United States. For the purposes of the ATB, the costs associated with technology and project risk in the U.S. market are represented in the financing costs but not in the upfront capital costs (e.g., developer fees and contingencies). An individual technology may receive more favorable financing terms outside the United States, due to less technology and project risk, caused by more project development experience (e.g., offshore wind in Europe) or more government or market guarantees. The R&D Only LCOE sensitivity cases present the range of LCOE based on financial conditions that are held constant over time unless R&D affects them, and they reflect different levels of technology risk. This case excludes effects of tax reform and tax credits, and changing interest rates over time. The R&D + Market LCOE case adds to these financial assumptions: (1) the changes over time consistent with projections in the Annual Energy Outlook and (2) the effects of tax reform and tax credits. The ATB representative plant characteristics that best align with those of recently installed or anticipated near-term land-based wind plants are associated with TRG 4. Data for all the resource categories can be found in the ATB Data spreadsheet; for simplicity, not all resource categories are shown in the figures.
The methodology for representing the CAPEX, O&M, and capacity factor assumptions behind each pathway is discussed in Projections Methodology. In general, the degree of adoption of technology innovation distinguishes the Constant, Mid, and Low technology cost scenarios. These projections represent trends that reduce CAPEX and improve performance. Development of these scenarios involves technology-specific application of the following general definitions:
To estimate LCOE, assumptions about the cost of capital to finance electricity generation projects are required, and the LCOE calculations are sensitive to these financial assumptions. Two project finance structures are used within the ATB:
A constant cost recovery period – or period over which the initial capital investment is recovered – of 30 years is assumed for all technologies throughout this website, and it can be varied in the ATB data spreadsheet.
The equations and variables used to estimate LCOE are defined on the Equations and Variables page. For illustration of the impact of changing financial structures such as WACC, see Project Finance Impact on LCOE. For LCOE estimates for the Constant, Mid, and Low technology cost scenarios for all technologies, see 2019 ATB Cost and Performance Summary.
In general, differences among the technology cost cases reflect different levels of adoption of innovations. Reductions in technology costs reflect the cost reduction opportunities that are listed below.
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Wiser, R., Jenni, K., Seel, J., Baker, E., Hand, M., Lantz, E., & Smith, A. (2016). Forecasting Wind Energy Costs and Cost Drivers: The Views of the World's Leading Experts (No. LBNL-1005717; p. 87 pp.). Retrieved from Lawrence Berkeley National Laboratory website: https://emp.lbl.gov/publications/forecasting-wind-energy-costs-and