US Wind Research Articles

Critical material requirements and recycling opportunities for US wind and solar power generation

AbstractThe deployment of renewable energy generation technologies, driven primarily by concerns over catastrophic climate change, is expected to increase rapidly in the United States. Rapid increases in the deployment of wind and solar energy will translate to increases in critical material requirements, causing concern that demand could outstrip supply, leading to mineral price volatility and potentially slowing the energy transition. This study presents a detailed demand‐side model for wind and solar in the United States using dynamic material flow analysis to calculate the requirements for 15 elements: Cr, Zn, Ga, Se, Mo, Ag, Cd, In, Sn, Te, Pr, Nd, Tb, Dy, and Pb. Results show that transitioning to a completely decarbonized US energy system by 2050 could require a five‐to‐sevenfold increase in critical material flow‐into‐use compared with business as usual (BAU), with some materials requiring much larger increases. Rare earth elements (REEs) could require 60–300 times greater material flows into the US power sector in 2050 than in 2021, representing 13%–49% of the total global REE supply. Te requirements for reaching net zero by 2050 could exceed current supply, posing challenges for widespread deployment of cadmium‐telluride solar. We also investigate several strategies for reducing material requirements, including closed‐loop recycling, material intensity reduction, and changing market share of subtechnologies (e.g., using crystalline silicon solar panels instead of cadmium telluride). Although these strategies can significantly reduce critical material requirements by up to 40% on average, aggressive decarbonization will still require a substantial amount of critical material.

The value of wake steering wind farm flow control in US energy markets

Abstract. Wind farm flow control represents a category of control strategies for achieving wind-plant-level objectives, such as increasing wind plant power production and/or reducing structural loads, by mitigating the impact of wake interactions between wind turbines. Wake steering is a wind farm flow control technology in which specific turbines are misaligned with the wind to deflect their wakes away from downstream turbines, thus increasing overall wind plant power production. In addition to promising results from simulation studies, wake steering has been shown to successfully increase energy production through several recent field trials. However, to better understand the benefits of wind farm flow control strategies such as wake steering, the value of the additional energy to the electrical grid should be evaluated – for example, by considering the price of electricity when the additional energy is produced. In this study, we investigate the potential for wake steering to increase the value of wind plant energy production by combining model predictions of power gains using the FLOw Redirection and Induction in Steady State (FLORIS) engineering wind farm flow control tool with historical electricity price data for 15 existing US wind plants in four different electricity market regions. Specifically, for each wind plant, we use FLORIS to estimate power gains from wake steering for a time series of hourly wind speeds and wind directions spanning the years 2018–2020, obtained from the ERA5 reanalysis dataset. The modeled power gains are then correlated with hourly electricity prices for the nearest transmission node. Through this process we find that wake steering increases annual energy production (AEP) between 0.4 % and 1.7 %, depending on the wind plant, with average increases in potential annual revenue (i.e., annual revenue of production, ARP) 4 % higher than the AEP gains. For most wind plants, ARP gain was found to exceed AEP gain. But the ratio between ARP gain and AEP gain is greater for wind plants in regions with high wind penetration because electricity prices tend to be relatively higher during periods with below-rated wind plant power production, when wake losses occur and wake steering is active; for wind plants in the Southwest Power Pool – the region with the highest wind penetration analyzed (31 %) – the increase in ARP from wake steering is 11 % higher than the AEP gain. Consequently, we expect the value of wake steering, and other types of wind farm flow control, to increase as wind penetration continues to grow.

A database of hourly wind speed and modeled generation for US wind plants based on three meteorological models

In 2022, wind generation accounted for ~10% of total electricity generation in the United States. As wind energy accounts for a greater portion of total energy, understanding geographic and temporal variation in wind generation is key to many planning, operational, and research questions. However, in-situ observations of wind speed are expensive to make and rarely shared publicly. Meteorological models are commonly used to estimate wind speeds, but vary in quality and are often challenging to access and interpret. The Plant-Level US multi-model WIND and generation (PLUSWIND) data repository helps to address these challenges. PLUSWIND provides wind speeds and estimated generation on an hourly basis at almost all wind plants across the contiguous United States from 2018–2021. The repository contains wind speeds and generation based on three different meteorological models: ERA5, MERRA2, and HRRR. Data are publicly accessible in simple csv files. Modeled generation is compared to regional and plant records, which highlights model biases and errors and how they differ by model, across regions, and across time frames.

Mass determination and model prediction of retired blades from wind turbine repowering or dismantling using a GIS database

Existing estimations of waste from wind energy infrastructure that is headed for, flowing through, or having reached the terminus of various post-processing pathways have primarily relied on reported capacity to extrapolate the material weight of turbine components. This data can be used to project future streams of composite blade material coming from wind farm repowering and decommissioning and inform policies to optimize or improve certain blade End of Life (EoL) options. However, rated capacity alone is insufficient to quantify or characterize the dynamics of US wind fleet retirement, since turbines are often repowered with new blades but their capacity remains the same. This research demonstrates an alternative method, comparing various mass estimation techniques and identifying blade models that have been retired or are soon to enter waste pathways due to turbine repowering by spatiotemporal comparison of periodic versions of the United States Geological Survey (USGS) Wind Turbine Database (USWTDB). These analyses are used to compile a list of turbine and blade models that will be at the forefront of national repowering and decommissioning movements in the near future. Mass of future waste flows are totalled and can help inform protocols and frameworks for blade material EoL processes.

Explaining the decline of US wind output power density

US wind power generation has grown significantly over the last decades, in line with the number and average size of operating turbines. However, wind power density has declined, both measured in terms of wind power output per rotor swept area as well as per spacing area. To study this effect, we present a decomposition of US wind power generation data for the period 2001–2021 and examine how changes in input power density and system efficiency affected output power density. Here, input power density refers to the amount of wind available to turbines, system efficiency refers to the share of power in the wind flowing through rotor swept areas which is converted to electricity and output power density refers to the amount of wind power generated per rotor swept area. We show that, while power input available to turbines has increased in the period 2001–2021, system efficiency has decreased. In total, this has caused a decline in output power density in the last 10 years, explaining higher land-use requirements. The decrease in system efficiency is linked to the decrease in specific power, i.e. the ratio between the nameplate capacity of a turbine and its rotor swept area. Furthermore, we show that the wind available to turbines has increased substantially due to increases in the average hub height of turbines since 2001. However, site quality has slightly decreased in this period.

On the Clock: Gulf of Mexico Enters the Offshore Wind Development Race

_ Offshore wind farms could in the next decade find a home in the Gulf of Mexico (GOM), more than 8 decades after the first oil flowed from its first offshore field. The Bureau of Ocean Energy Management in July identified the first two draft wind energy areas (WEAs)—one off the coast of Louisiana, the other off Texas—that could harness the Gulf’s steady breezes. Offshore wind is a key piece in President Biden’s strategy of addressing climate change by transitioning the US onto renewable energy. His administration in March 2021 set a target of deploying 30 GW of offshore wind capacity by 2030, “enough to power 10 million homes with clean energy, support 77,000 jobs, and spur $12 billion per year in private investment in offshore wind projects”, according to the announcement. This is the equivalent to more than 2% of the US utility-scale electricity generating capacity and about 25% of the total US wind electricity generating capacity, according to a Congressional Research Service report. In 2020 the country’s total generating capacity was about 1,212 GW, with about 119 GW of that produced from wind energy resources—virtually all onshore. Currently, the US has only two commercial offshore wind farms bringing the US total of offshore wind capacity to 42 MW. The five-turbine Block Island Wind Farm off the Rhode Island coast has a capacity of 30 MW, and the two-turbine Coastal Virginia Offshore Wind Project has a current capacity of 12 MW. New Energy, Historic Basin Interest in the Gulf’s offshore wind potential has increased in recent months as development efforts off the country’s East and West Coasts continue to advance and the Biden administration has pledged hundreds of millions of dollars in federal funding. One of the Gulf’s WEAs is located about 24 nautical miles (nm) off the coast of Galveston, Texas. The area under review totals 546,645 acres and has the potential to power 2.3 million homes with clean wind energy. The other WEA is located about 56 nm off the coast of Lake Charles, Louisiana, totaling 188,023 acres and has the potential to power 799,000 homes. This stretch of the Gulf Coast is historically significant as the location of the first free-standing platform to produce oil from the Gulf’s Creole field, installed about 1.5 miles offshore Cameron, Louisiana, in 1938. The GOM oil and gas industry has grown from humble beginnings to become one of the country’s most important energy resource and infrastructure regions. It is its energy infrastructure—its ports, its vessels, and its skilled workforce—that offshore wind developers find attractive. While the Gulf’s winds are not as strong as Atlantic and Pacific winds—about 7.5 to 8.5 m/s as compared to 8.0 to 10 m/s—this proximity to the oil and gas supply chain that can be leveraged and a milder climate that decreases operating costs and increases turbine access are considered its strongest advantages, according to the National Renewable Energy Laboratory (NREL).

Modelling of cost indicators for wind turbines of multimegawatt class in various sizes

The choice of wind turbines to fit various specific wind conditions for the purpose of ensuring maximum generation of electric power at least investment expenditures is among the wind power sector overarching challenges. Solving this task involves the evaluation of cost indices for wind turbines of various sizes. A well-known and rather popular with investigators model, made by the National Renewable Energy Laboratory (USA) has been improved for the first time with the aim of determining the cost of wind turbines of various sizes on the basis of their main parameters (rated power, rotor diameter, hub height) for current conditions of application. The established correlation relationships between the cost of wind turbine and its main parameters made possible the transformation of a well-known complex model into a model with linear equations and minimization of computations. Based on the research studies of the evolution of wind turbines main parameters and an average (global) cost of 1 MW of their power, the authors have suggested the first-ever original linear mathematical models that enable evaluating the wind turbine cost for any year of research. In illustration of application of the first ever developed technique, we have made the assessment of operating efficiency of the US wind farms from 2010 to 2019. The results obtained convincingly indicate the high quality of the developed model.

Simulation-based environmental-impact assessment of glycerol-to-hydrogen conversion technologies

Abstract This simulation-based comparative assessment aims to quantify the environmental and human-health impacts of greener hydrogen (H2) production via three glycerol-based technologies, including: supercritical water reforming (SCWR), aqueous-phase reforming (APR) and autothermal reforming (ATR). The GaBi (2018 edition) life-cycle assessment (LCA) platform is used to develop cradle-to-gate product system models for these technologies and the TRACI 2.1 methodology is used to quantify their midpoint impact categories. Aspen HYSYS (v11) process-simulation software is used to generate the life-cycle inventory (LCI) primary data required to produce 1 kg of H2 via each of the indicated glycerol-reforming technologies. Per ISO 14040:2006 reporting requirements for the LCA results interpretation step, three base case (BC) scenarios and four sensitivity scenarios (SS) are developed and quantified to compare the effects of different process electricity sources (US grid mix versus wind power) and thermal energy sources (natural gas versus biogas) on the LCA results. The high operating pressure (viz. 240 bar) of SCWR enabled assessment of the impact of in situ electricity generation to offset some of electricity required for this technology. The major insights from this research are as follows: (i) per 1 kg of produced H2, APR reduces CO2 emissions by ≈95% compared to ATR and by ≈92% compared to SCWR, (ii) for BC scenarios, the primary energy consumption (in MJ/kg of produced H2) is in the following order from highest to lowest: ATR > SCWR > APR and (iii) H2 production via glycerol APR is more environmentally sustainable than SCWR and ATR, and thus offers a promising path for greener H2 production. Future environmental sustainability studies should focus on expanding the scope of this study to include H2 production via water electrolysis using renewable electricity sources and via solar and nuclear-driven thermochemical water splitting.

Using the United States Wind Turbine Database to Identify Increasing Turbine Size, Capacity and Other Development Trends

The purpose of this article was to analyze data associated with advances in wind energy across the United States. While governments, academia, and the private sector generally know patterns of wind turbine development (i.e. turbine size and capacity growing in recent years), there is no known independent, reliable, and/or updated summary of these variables. Using data collected by the Lawrence Berkeley National Laboratory and partners, this study used descriptive statistics to show turbine development and growth patterns from 1981-2019. The newly created United States Wind Turbine Database (USWTDB) represents the most comprehensive account of wind turbine information and was updated in January 2020. Variables I am interested in here are turbine manufacturer, state of project, turbine and project capacity, and turbine size. Findings provide empirical evidence to support the common, yet previously unrefined statements that wind turbines are growing larger in number, size and capacity. This growth is varied over spatial and temporal scales. I also provide evidence to show patterns of turbine manufacturing, with GE Wind dominating much of the US wind energy landscape today. I hope this work provides a timely resource for those interested in a variety of questions surrounding wind energy development in the United States. Perhaps more importantly, this analysis will hopefully inspire others to use what the USWTDB provides and answer larger questions surrounding wind energy futures.

Forecast of short-term wind power based on a novel hybrid method

Short-term wind power forecasting plays an important role in power generation, because it prevents the power system operation from its uncertain and intermittent nature. This article proposes a novel method for short-term wind power forecasting, which combines the wavelet transform, particle swarm optimization dynamic gray model and Lyapunov exponent prediction method. First, the approach decomposes the wind power curve into the high-frequency and low-frequency curves by wavelet transform, which represent the detail and tendency signals, respectively. Then, we use the proposed particle swarm optimization dynamic gray model to forecast the low-frequency curve with its smooth and periodic outline. Moreover, Lyapunov exponent prediction method is used to predict high-frequency curves, which possess the chaos characteristics. Finally, we obtain the wind power forecasting result from the combination of the predicted low and high frequencies. The experiment of four seasons in an US wind farm validates that the proposed method is effective in solving the short-term wind power forecasting problem. The obtained results, discussed comprehensively, show that the hybrid method has better prediction accuracy than the other methods, such as artificial neural network, persistence, and autoregressive integrated moving average model, with the lowest average mean absolute percentage error is 8.07% and the average root mean square error is 0.8164 over four seasons.

A reversal in global terrestrial stilling and its implications for wind energy production

Wind power, a rapidly growing alternative energy source, has been threatened by reductions in global average surface wind speed, which have been occurring over land since the 1980s, a phenomenon known as global terrestrial stilling. Here, we use wind data from in situ stations worldwide to show that the stilling reversed around 2010 and that global wind speeds over land have recovered. We illustrate that decadal-scale variations of near-surface wind are probably determined by internal decadal ocean–atmosphere oscillations, rather than by vegetation growth and/or urbanization as hypothesized previously. The strengthening has increased potential wind energy by 17 ± 2% for 2010 to 2017, boosting the US wind power capacity factor by ~2.5% and explains half the increase in the US wind capacity factor since 2010. In the longer term, the use of ocean–atmosphere oscillations to anticipate future wind speeds could allow optimization of turbines for expected speeds during their productive life spans.

Determination of a probability distribution for pressure scanner noise and digitization uncertainty reporting

This paper proposes a probability distribution for the discrete noise on a pressure scanner system commonly used in major US wind tunnel facilities. The level of granularity allows for a close relation between the measurement process and the imparted uncertainty. The distribution selection methodology accounts for current discussions regarding uncertainty reporting, especially the error-bound definition recently proposed. Such an error-bound definition benefits from the relationship to the measurement process and provides information to a practitioner responsible for data collection methods to assist in uncertainty reduction resource allocation. A discretized four-parameter beta distribution is fitted to satisfy the requirements for reporting the sensor noise and analog-digital conversion uncertainty.

Microclimate effects of wind farms on local crop yields

This paper considers a novel spillover effect of wind farms - microclimate impacts on neighboring crop yields. Using US county-level crop and wind capacity data, I examine the effects of wind energy development on crop yields, controlling for time-invariant county characteristics and state-level annual shocks. I find robust evidence that counties with increased wind power development have also experienced increased corn and other crop yields, such that an additional 100 MW of wind capacity increases county yields by roughly 1%. At recent prices, this implies a more than $5 dollar per megawatt-hour local benefit, corresponding to several hundred million dollars in annual benefits.

Explaining technological change in the US wind industry: Energy policies, technological learning, and collaboration

This paper examines the drivers of technological change in the US wind industry from perspectives of technological learning, collaboration, and energy policies. Using a panel of 576 utility-scale wind farms between 2001 and 2012, this paper estimates the impacts of different learning mechanisms—learning through research and development in wind turbine manufacturing, learning from a wind farm operator or a turbine manufacturer's previous project experience, learning through collaboration among wind project participants, and knowledge spillovers—on technological change of wind power, measured as improved capacity factor. Empirical findings suggest that a wind farm's performance has improved over time as the project operator accumulates more experience. Moreover, its collaboration with turbine manufacturers and the transmission system operator leads to greater performance improvement, particularly when the transmission system is coordinated by an independent system operator or a regional transmission organization (ISO/RTO). This finding supports the institutional change in the US electricity market deregulation—the creation of ISO/RTOs. The ISO/RTO-governed transmission networks promote wind power integration through regional collaboration and coordination. In addition, evidence of knowledge spillovers on wind farm operation at the state level provides justifications for state energy policies that subsidize wind power generation.

Wind “drought” poses problems for US wind turbines

Wind “drought” poses problems for US wind turbines

Non-market strategies that affect industry conditions

This paper investigates how resources internal to the firm are used to influence the external political environment regarding the adoption of new technology. Drawing from the non-market strategies literature, this study investigates if lobbying efforts, through corporate political activities, are affective at changing legislation involving the approval of wind farms. Using the US wind industry as the context, empirical tests are performed to determine if campaign contributions lead to favourable policy changes which subsequently increase the probability of wind farm adoption. This study confirms extant research by empirically illustrating that corporate political activities do not directly lead to beneficial legislative policy creation but can hasten the innovation adoption cycle in renewable energy via other mechanisms.

CFIUS post-Ralls: Ramifications for Sovereign Wealth Funds

Global capital is on the move and sovereign wealth funds, with significant assets, are uniquely positioned to take advantage of the increase in mergers and acquisitions activity, especially in the United States. At the same time, major acquisitions in the US by foreign investors, including sovereign wealth funds, face a key challenge in the Committee on Foreign Investment in the United States (CFIUS or the Committee). CFIUS vets foreign acquisitions of US businesses for national security concerns, and “national security” is a term that is not defined by CFIUS statute or regulation. With increased sovereign wealth fund investments in the US, it is important for policymakers and investors alike to understand the potential roadblock that the Committee presents to foreign investment and for investors and potential US targets to develop an appropriate strategy to approach CFIUS when contemplating an acquisition. In a recent appellate court decision, Ralls v. Committee on Foreign Investment in the United States, the US Court of Appeals for the District of Columbia Circuit held that the Ralls Corporation (a Chinese-owned and controlled company) had been deprived of its property without due process when the President (at the recommendation of CFIUS) ordered Ralls to divest its interests in certain US wind farm projects on national security grounds. The court held that under the Fifth Amendment Due Process Clause of the US Constitution, Ralls was entitled to receive both the unclassified evidence that was the basis for the government’s decision and an opportunity to respond to this evidence. The case is still ongoing at the time of this writing; thus, the full impact of the decision remains to be seen. It is noteworthy, however, as the first legal case ever brought against CFIUS, and because the court’s holding is relatively unusual in an area – national security – in which US courts traditionally defer to the executive branch. Part I of this article provides the history of CFIUS’s statutory and regulatory authority; how CFIUS determines jurisdiction over a particular transaction; and the review and investigation process, with special emphasis on the treatment of sovereign wealth fund transactions. Part II examines the recent D.C. Circuit Court decision in Ralls v. Committee on Foreign Investment in the United States and analyzes the decision’s implications for foreign investors, including sovereign wealth funds. It concludes by emphasizing that although the Ralls litigation is ongoing at the district court level, the proceedings should, at minimum, result in an opportunity for foreign investors to have increased engagement with CFIUS, which may lead to more informed decision-making by CFIUS. At the same time, as Part III discusses, the decision does not at present change the importance of certain strategies for sovereign wealth funds navigating the CFIUS process to maximize the opportunity for success.

Spatial Hedonic Analysis of the Effects of US Wind Energy Facilities on Surrounding Property Values

Rapid, large-scale U.S. deployment of wind turbines is expected to continue in the coming years. Because some of that deployment is expected to occur in relatively populous areas, concerns have arisen about the impact of turbines on nearby home values. Previous research on the effects of wind turbines on surrounding home values has been limited by small home-sale data samples and insufficient consideration of confounding home-value factors and spatial dependence. This study examines the largest set of turbine-proximal sales data to date: more than 50,000 home sales including 1,198 within 1 mile of a turbine (331 of which were within a half mile). The data span the periods well before announcement of the wind facilities to well after their construction. We use ordinary least squares and spatial-process difference-in-difference hedonic models to estimate the home-value impacts of the wind facilities, controlling for value factors existing prior to the wind facilities’ announcements, the spatial dependence of home values, and value changes over time. A series of robustness models provide greater confidence in the results. We find no statistical evidence that home values near turbines were affected in the turbine post-construction or post-announcement/pre-construction periods.

Gone With the Wind: The Ralls Transaction and Implications for Foreign Investment in the United States

In 2012, pursuant to a national security review conducted by the Committee on Foreign Investment in the United States (CFIUS), President Obama ordered the unwinding of Ralls Corporation's ("Ralls") acquisition of certain US wind farm companies. Ralls' legal challenge of the President's Order, and the court's opinions to date, highlight important considerations for both foreign investors and the national security community. This article contextualizes the case within a broader debate about how well CFIUS balances openness to foreign investment and protection of national security, points out important gaps in the national security review process, and considers opportunities for greater transparency.

Characterization of wind power resource in the United States

Abstract. Wind resource in the continental and offshore United States has been reconstructed and characterized using metrics that describe, apart from abundance, its availability, persistence and intermittency. The Modern Era Retrospective-Analysis for Research and Applications (MERRA) boundary layer flux data has been used to construct wind profile at 50 m, 80 m, 100 m, 120 m turbine hub heights. The wind power density (WPD) estimates at 50 m are qualitatively similar to those in the US wind atlas developed by the National Renewable Energy Laboratory (NREL), but quantitatively a class less in some regions, but are within the limits of uncertainty. The wind speeds at 80 m were quantitatively and qualitatively close to the NREL wind map. The possible reasons for overestimation by NREL have been discussed. For long tailed distributions like those of the WPD, the mean is an overestimation and median is suggested for summary representation of the wind resource. The impact of raising the wind turbine hub height on metrics of abundance, persistence, variability and intermittency is analyzed. There is a general increase in availability and abundance of wind resource but there is an increase in intermittency in terms of level crossing rate in low resource regions.