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DOE OSTI2016

Deployment of Wind Turbines in the Built Environment: Risks, Lessons, and Recommended Practices

Built-environment wind turbine (BEWT) projects are wind energy projects that are constructed on, in, or near buildings. These projects present an opportunity for distributed, low-carbon generation combined with highly visible statements on sustainability, but the BEWT niche of the wind industry is still developing and is relatively less mature than the utility-scale wind or traditional distributed wind sectors. The findings from this report cannot be extended to wind energy deployments in general because of the large difference in application and technology maturity. This paper investigates the current state of the BEWT industry by reviewing available literature on BEWT projects as well as interviewing project owners on their experiences deploying and operating the technology. The authors generated a series of case studies that outline the pertinent project details, project outcomes, and lessons learned. This paper integrates those information sources into recommended practices that can be utilized by future stakeholders to evaluate the feasibility of BEWTs for their unique applications and sites.

17 WIND ENERGY↗
DOE OSTI2014

Wind Technologies & Evolving Opportunities (Presentation)

This presentation covers opportunities for wind technology; wind energy market trends; an overview of the National Wind Technology Center near Boulder, Colorado; wind energy price and cost trends; wind turbine technology improvements; and wind resource characterization improvements.

17 WIND ENERGY↗
DOE OSTI2025

Quantifying Uncertainties in Modeling Wind Resource Data from Different PBL Schemes in the WRF Model: A Case Study Over the Puerto Rico Region

This study examines the modeling uncertainty of wind resource data stemming from the use of various planetary boundary layer (PBL) parameterizations available in the Weather Research and Forecasting (WRF) model. WRF-based wind simulations spanning 20 years at 3-km resolution using 11 different PBL schemes are used to objectively investigate the uncertainty in modeling wind speed for land-based wind (LBW) and offshore wind (OSW) locations in Puerto Rico. The uncertainty in the wind modeling for the 20-year dataset is quantified using the spread index (SI) and standard deviation (SD). For virtual LBW and OSW sites, the SI and SD values are analyzed as calculated across various spatial and temporal scales. Because the PBL's atmospheric stability conditions can be characterized into two dominant categories, the study focuses on analyzing the SI and SD for daytime (mainly unstable PBL conditions) and nighttime (mainly stable PBL conditions). For wind shear (10 m-200 m) at the OSW and LBW sites, WRF-based numerical experiments indicate the following SI (or SD) ranges: 39%-94% (0.74 m/s-1.44 m/s) during the daytime for OSW, 50%-75% (0.68 m/s-1.19 m/s) during the daytime for LBW, 37%-60% (0.73 m/s-1.12 m/s) during the nighttime for OSW, and 57%-143 % (0.65 m/s-1.43 m/s) during the nighttime for LBW. While a high SI is observed when modeling LBW during the nighttime, there are notable modeling uncertainties during the daytime on the leeward side of the orographic barriers for Puerto Rico.

17 WIND ENERGY↗
DOE OSTI2017

OC5 Project Phase II: Validation of Global Loads of the DeepCwind Floating Semisubmersible Wind Turbine

This paper summarizes the findings from Phase II of the Offshore Code Comparison, Collaboration, Continued, with Correlation project. The project is run under the International Energy Agency Wind Research Task 30, and is focused on validating the tools used for modeling offshore wind systems through the comparison of simulated responses of select system designs to physical test data. Validation activities such as these lead to improvement of offshore wind modeling tools, which will enable the development of more innovative and cost-effective offshore wind designs. For Phase II of the project, numerical models of the DeepCwind floating semisubmersible wind system were validated using measurement data from a 1/50th-scale validation campaign performed at the Maritime Research Institute Netherlands offshore wave basin. Validation of the models was performed by comparing the calculated ultimate and fatigue loads for eight different wave-only and combined wind/wave test cases against the measured data, after calibration was performed using free-decay, wind-only, and wave-only tests. The results show a decent estimation of both the ultimate and fatigue loads for the simulated results, but with a fairly consistent underestimation in the tower and upwind mooring line loads that can be attributed to an underestimation of wave-excitation forces outside the linear wave-excitation region, and the presence of broadband frequency excitation in the experimental measurements from wind. Participant results showed varied agreement with the experimental measurements based on the modeling approach used. Modeling attributes that enabled better agreement included: the use of a dynamic mooring model; wave stretching, or some other hydrodynamic modeling approach that excites frequencies outside the linear wave region; nonlinear wave kinematics models; and unsteady aerodynamics models. Also, it was observed that a Morison-only hydrodynamic modeling approach could create excessive pitch excitation and resulting tower loads in some frequency bands.

17 WIND ENERGY↗
DOE OSTI2020

Longitudinal coherence and short-term wind speed prediction based on a nacelle-mounted Doppler lidar

The spatial structure of turbulence in atmospheric boundary layer flows is highly relevant to wind energy. In particular, wind turbine control strategies based on inflow preview measurements require knowledge of the longitudinal evolution of turbulent flow as it approaches the rotor. These upstream measurements are usually obtained with nacelle-mounted wind lidars. In contrast to traditional in situ anemometry, lidars collect measurements within a probe volume which varies in size depending on the technology of the commercial system being used. Here, we address two issues related to the use of wind lidar to measure the incoming flow to a wind turbine: (i) whether existing longitudinal coherence models can be used to predict flow at the rotor, based on measurements performed at a distance away from the rotor; and (ii) what effect probe-volume averaging has on the inflow predictions. These two questions are critical to the design and implementation of robust wind turbine control strategies. To address these questions, we perform field measurements and large-eddy simulations to determine which incoming flow structures can be readily predicted with existing coherence models, and which require additional corrections to account for lidar volumetric averaging effects. Results reveal that the wind turbine induction zone has a negligible impact on the longitudinal coherence and first-order turbulence quantities, such as the standard deviation of velocity fluctuations. However, the phase of the signal, from which advection time periods of the turbulent structures are derived, is affected by the rotor blockage effect.

17 WIND ENERGY↗
DOE OSTI2017

Disturbance accommodating control design for wind turbines using solvability conditions

In this study, solvability conditions for disturbance accommodating control (DAC) have been discussed and applied on wind turbine controller design in above-rated wind speed to regulate rotor speed and to mitigate turbine structural loads. DAC incorporates a predetermined waveform model and uses it as part of the state-space formulation, which is known as the internal model principle to reduce or minimize the wind disturbance effects on the outputs of the wind turbine. An asymptotically stabilizing DAC controller with disturbance impact on the wind turbine being totally canceled out can be found if certain conditions are fulfilled. Designing a rotor speed regulation controller without steady-state error is important for applying linear control methodology such as DAC on wind turbines. Therefore, solvability conditions of DAC without steady-state error are attractive and can be taken as examples when designing a multitask turbine controller. DAC controllers solved via Moore-Penrose Pseudoinverse and the Kronecker product are discussed, and solvability conditions of using them are given. Additionally, a new solvability condition based on inverting the feed-through D term is proposed for the sake of reducing computational burden in the Kronecker product. Applications of designing collective pitch and independent pitch controllers based on DAC are presented. Recommendations of designing a DAC-based wind turbine controller are given. A DAC controller motivated by the proposed solvability condition that utilizes the inverse of feed-through D term is developed to mitigate the blade flapwise once-per-revolution bending moment together with a standard proportional integral controller in the control loop to assist rotor speed regulation. Simulation studies verify the discussed solvability conditions of DAC and show the effectiveness of the proposed DAC control design methodology.

17 WIND ENERGY↗
DOE OSTI2013

Wind Resource Assessment Report: Mille Lacs Indian Reservation, Minnesota

The U.S. Environmental Protection Agency (EPA) launched the RE-Powering America's Land initiative to encourage development of renewable energy on potentially contaminated land and mine sites. EPA collaborated with the U.S. Department of Energy's (DOE's) National Renewable Energy Laboratory (NREL) and the Mille Lacs Band of Chippewa Indians to evaluate the wind resource and examine the feasibility of a wind project at a contaminated site located on the Mille Lacs Indian Reservation in Minnesota. The wind monitoring effort involved the installation of a 60-m met tower and the collection of 18 months of wind data at multiple heights above the ground. This report focuses on the wind resource assessment, the estimated energy production of wind turbines, and an assessment of the economic feasibility of a potential wind project sited this site.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2014

Assessment of Ports for Offshore Wind Development in the United States

As offshore wind energy develops in the United States, port facilities will become strategic hubs in the offshore wind farm supply chain because all plant and transport logistics must transit through these facilities. Therefore, these facilities must provide suitable infrastructure to meet the specific requirements of the offshore wind industry. As a result, it is crucial that federal and state policy-makers and port authorities take effective action to position ports in the offshore wind value chain to take best advantage of their economic potential. The U.S. Department of Energy tasked the independent consultancy GL Garrad Hassan (GL GH) with carrying out a review of the current capability of U.S. ports to support offshore wind project development and an assessment of the challenges and opportunities related to upgrading this capability to support the growth of as many as 54 gigawatts of offshore wind installed in U.S. waters by 2030. The GL GH report and the open-access web-based Ports Assessment Tool resulting from this study will aid decision-makers in making informed decisions regarding the choice of ports for specific offshore projects, and the types of investments that would be required to make individual port facilities suitable to serve offshore wind manufacturing, installation and/or operations.

17 WIND ENERGY↗
DOE OSTI2015

2014 Wind Technologies Market Report

Wind power capacity additions in the United States rebounded in 2014, and continued growth through 2016 is anticipated. Recent and projected near-term growth is supported by the industry’s primary federal incentive—the production tax credit (PTC)—which is available for projects that began construction by the end of 2014. Wind additions are also being driven by recent improvements in the cost and performance of wind power technologies, which have resulted in the lowest power sales prices ever seen in the U.S. wind sector. Growing corporate demand for wind energy and state-level policies play important roles as well. Expectations for continued technological advancements and cost reductions may further boost future growth. At the same time, the prospects for growth beyond 2016 are uncertain. The PTC has expired, and its renewal remains in question. Continued low natural gas prices, modest electricity demand growth, and limited near-term demand from state renewables portfolio standards (RPS) have also put a damper on growth expectations. These trends, in combination with increasingly global supply chains, have limited the growth of domestic manufacturing of wind equipment. What they mean for wind power additions through the end of the decade and beyond will be dictated in part by future natural gas prices, fossil plant retirements, and policy decisions.

17 WIND ENERGY↗
DOE OSTI2014

2013 Wind Technologies Market Report

This report describes the status of the U.S. wind energy industry market in 2013, its trends, performance, market drivers and future outlook. Annual wind power capacity additions in the United States were modest in 2013, but all signals point to more-robust growth in 2014 and 2015. With the industry’s primary federal support—the production tax credit (PTC)—only available for projects that had begun construction by the end of 2013, the next couple years will see those projects commissioned. Near-term wind additions will also be driven by recent improvements in the cost and performance of wind power technologies. At the same time, the prospects for growth beyond 2015 are uncertain. The PTC has expired, and its renewal remains in question. Continued low natural gas prices, modest electricity demand growth, and limited near-term demand from state renewables portfolio standards (RPS) have also put a damper on industry growth expectations. These trends, in combination with increasingly global supply chains, continue to impact domestic manufacturing of wind equipment. What they mean for wind power additions through the end of the decade and beyond will be dictated in part by future natural gas prices, fossil plant retirements, and policy decisions. At the same time, recent declines in wind energy costs and prices and the potential for continued technological advancements have boosted future growth prospects.

17 WIND ENERGY↗
DOE OSTI2016

The Role of Surface Energy Exchange for Simulating Wind Inflow: An Evaluation of Multiple Land Surface Models in WRF for the Southern Great Plains Site Field Campaign Report

The Weather Research and Forecasting (WRF) model is used to investigate choice of land surface model (LSM) on the near-surface wind profile, including heights reached by multi-megawatt wind turbines. Simulations of wind profiles and surface energy fluxes were made using five LSMs of varying degrees of sophistication in dealing with soil-plant-atmosphere feedbacks for the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility’s Southern Great Plains (SGP) Central Facility in Oklahoma. Surface-flux and wind-profile measurements were available for validation. The WRF model was run for three two-week periods during which varying canopy and meteorological conditions existed. The LSMs predicted a wide range of energy-flux and wind-shear magnitudes even during the cool autumn period when we expected less variability. Simulations of energy fluxes varied in accuracy by model sophistication, whereby LSMs with very simple or no soil-plant-atmosphere feedbacks were the least accurate; however, the most complex models did not consistently produce more accurate results. Errors in wind shear also were sensitive to LSM choice and were partially related to the accuracy of energy flux data. The variability of LSM performance was relatively high, suggesting that LSM representation of energy fluxes in the WRF model remains a significant source of uncertainty for simulating wind turbine inflow conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Terminology Guideline for Classifying Offshore Wind Energy Resources

The purpose of this guideline is to establish a clear and consistent vocabulary for conveying offshore wind resource potential and to interpret this vocabulary in terms that are familiar to the oil and gas (O&G) industry. This involves clarifying and refining existing definitions of offshore wind energy resource classes. The terminology developed in this guideline represents one of several possible sets of vocabulary that may differ with respect to their purpose, data availability, and comprehensiveness. It was customized to correspond with established offshore wind practices and existing renewable energy industry terminology (e.g. DOE 2013, Brown et al. 2015) while conforming to established fossil resource classification as best as possible. The developers of the guideline recognize the fundamental differences that exist between fossil and renewable energy resources with respect to availability, accessibility, lifetime, and quality. Any quantitative comparison between fossil and renewable energy resources, including offshore wind, is therefore limited. For instance, O&G resources are finite and there may be significant uncertainty associated with the amount of the resource. In contrast, aboveground renewable resources, such as offshore wind, do not generally deplete over time but can vary significantly subhourly, daily, seasonally, and annually. The intent of this guideline is to make these differences transparent and develop an offshore wind resource classification that conforms to established fossil resource classifications where possible. This guideline also provides methods to quantitatively compare certain offshore wind energy resources to O&G resource classes for specific applications. Finally, this guideline identifies areas where analogies to established O&G terminology may be inappropriate or subject to misinterpretation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

Offshore Wind Initiatives at the U.S. Department of Energy

Coastal and Great Lakes states account for nearly 80% of U.S. electricity demand, and the winds off the shores of these coastal load centers have a technical resource potential twice as large as the nation’s current electricity use. With the costs of offshore wind energy falling globally and the first U.S. offshore wind farm installed off the coast of Block Island, Rhode Island in 2016, offshore wind has the potential to contribute significantly to a clean, affordable, and secure national energy mix. To support the development of a world-class offshore wind industry, the U.S. Department of Energy has been supporting a broad portfolio of offshore wind research, development, and demonstration projects since 2011 and released a new National Offshore Wind Strategy jointly with the U.S. Department of the Interior in 2016.

17 WIND ENERGY↗
DOE OSTI2016

Smooth Particle Hydrodynamics-based Wind Representation

As a result of the 2011 accident at the Fukushima Dai-ichi NPP and other operational NPP experience, there is an identified need to better characterize and evaluate the potential impacts of externally generated hazards on NPP safety. Due to the ubiquitous occurrence of high winds around the world and the possible extreme magnitude of the hazard that has been observed, the assessment of the impact of the high-winds hazard has been identified as an important activity by both NPP owner-operators and regulatory authorities. However, recent experience obtained from the conduct of high-winds risk assessments indicates that such activities have been both labor-intensive and expensive to perform. Additionally, the existing suite of methods and tools to conduct such assessments (which were developed decades ago) do not make use of modern computational architectures (e.g., parallel processing, object-oriented programming techniques, or simple user interfaces) or methods (e.g., efficient and robust numerical-solution schemes). As a result, the current suite of methods and tools will rapidly become obsolete. Physics-based 3D simulation methods can provide information to assist in the RISMC PRA methodology. This research is intended to determine what benefits SPH methods could bring to high-winds simulations for the purposes of assessing their potential impact on NPP safety. The initial investigation has determined that SPH can simulate key areas of high-wind events with reasonable accuracy, compared to other methods. Some problems, such as simulation voids, need to be addressed, but possible solutions have been identified and will be tested with continued work. This work also demonstrated that SPH simulations can provide a means for simulating debris movement; however, further investigations into the capability to determine the impact of high winds and the impacts of wind-driven debris that lead to SSC failures need to be done. SPH simulations alone would be limited in size and computation time. An advanced method of combing results from grid-based methods with SPH through a data-driven model is proposed. This method could allow for more accurate simulation of particle movement near rigid bodies even with larger SPH particle sizes. If successful, the data-driven model would eliminate the need for a SPH turbulence model and increase the simulation domain size. Continued research beyond the scope of this project will be needed in order to determine the viability of a data-driven model.

17 WIND ENERGY↗
DOE OSTI2019

Distributed Wind Resource Assessment Framework: Functional Requirements and Metrics for Performance and Reliability Modeling

The focus of the distributed wind resource assessment (DWRA) performance framework is to first clarify the key parameters that define the wind resource for any distributed wind turbine project and then describe the loss and uncertainty factors associated with long-term performance of wind turbine projects. Next it will identify and define the key parameters required to analyze the operational performance of a project. This framework could then be the foundation for understanding the predictability of the power and revenue from a project. Improving the predictability and reliability of wind power generation and operations will reduce costs and potentially establish a framework to attract new capital to the distributed wind industry sector. This report is the first part of a research effort to investigate the impact that improved resource assessment and energy estimation for distributed wind can have on consumer confidence, cost of capital, cost of ownership and operations, perception of financial risk, and levelized cost of energy.

17 WIND ENERGY↗
DOE OSTI2021

Aeroacoustic Assessment of Wind Plant Controls

The Aeroacoustic Assessment project aims to quantify changes in aeroacoustic noise generation by a utility scale wind turbine operating under imposed yaw offsets common for wake steering and wind plant control strategies. Active plant control utilizing wake deflection control strategies have been shown experimentally and computationally to reliably produce 1-2% of additional annual energy production (AEP) without significant changes in turbine structural loads, the potential impact on aeroacoustic emissions has yet to be quantified or completely understood. Yawed operation of a wind turbine changes the three-dimensional aerodynamic interaction between the rotor blades and the incoming atmospheric flow, leading to changes in noise generation. This work quantifies the extent to which active control induces additional aeroacoustic emissions from additional separation and other flow interaction dynamic effects. Given public concerns about wind turbine noise and the need for observational data required for regulators to establish noise restrictions, we must understand potential acoustic emissions resulting from active control prior to commercial deployment and the development of practical noise reduction methods and technologies. The work outlined in this report details the new aeroacoustic measurement capability developed at NREL and its application to making full-field observations of noise from a utility-scale wind turbine. Preliminary noise modeling with the aeroacoustics module in OpenFAST helped to establish the design of the experiment, specifically targeting the noise observed at observers distributed around the DOE-owned GE 1.5 MW wind turbine. Low-frequency and infrasound measurement capability implemented in this project establish an operational baseline for the wind turbine, setting the stage for future control, rotor blade, and turbine design research.

17 WIND ENERGY↗
DOE OSTI2022

Defining Wind Energy Experience

Since 2015, the U.S. wind installed capacity has grown from 73 to over 120 gigawatts, creating jobs across many sectors and educational levels. The growth of the wind workforce will need to continue to meet the goal of 20% wind by 2030, as well as the Biden administration's goals to reduce greenhouse gas pollution by 2030, reach 100% carbon-free electricity by 2035, and achieve net-zero greenhouse gas emissions no later than 2050. Despite the needed and anticipated growth, there are challenges to meeting this demand. Research has consistently shown that it has been a challenge finding qualified applicants for open wind industry jobs. Between 2012 and 2018, the difficulty of finding qualified applicants increased from 62% to 68% according to industry respondents. In 2017, educational institutions and training programs reported that 67% of their students did not enter the wind energy industry. Research conducted in 2020 showed that 83% of interested workers had some or great difficulty finding job opportunities. In exploring reasons for this gap, the researchers found that challenges were primarily influenced by education, experience, and geography. This difficulty for wind industry employers, educational institutions, and the potential workforce is known as the "wind energy workforce gap." This report further investigates the experience aspect of this gap.

17 WIND ENERGY↗
DOE OSTI2023

NOW-23: The 2023 National Offshore Wind Data Set

In this report, we present the latest wind resource data specifically tailored for offshore regions in the United States. The data set, known as the 2023 National Offshore Wind data set (NOW-23), has been developed by the National Renewable Energy Laboratory (NREL) and its partners, and surpasses the previous resource data set, the Wind Integration National Dataset (WIND) Toolkit, which was released approximately ten years ago, in its offshore component. The WIND Toolkit has been widely utilized by stakeholders involved in wind resource assessments across the continental United States. However, with significant advancements in numerical weather prediction modeling over the past decade, the NOW-23 data set incorporates the latest research and development progress to provide stakeholders with an updated and cutting-edge resource for offshore wind analysis.

17 WIND ENERGY↗