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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Aerodynamic characterization of two tandem wind turbines under yaw misalignment control using actuator line model

Yaw control has proven to be promising in alleviating the wake effects that plague the efficiency of wind farms. In this work, the actuator line modeling (ALM) method is adopted to simulate the flows over two tandem turbines distanced by 3–7 rotor diameters, with the yaw angle of the upstream rotor varying from γ 1 = 0° to 50°. The aim is to provide a comprehensive aerodynamic characterization of this simple wind farm under yaw misalignment control. With increasing yaw angle, the power generated by the downstream rotor increases, compensating the power loss in the upstream rotor, and resulting in significantly higher total power of the two turbines than that without yaw control. The maximum power output is achieved as the upstream wake of the yawed rotor is redirected away from the downstream rotor plane. Behind the downstream rotor, the secondary steering phenomenon is observed, where the wake is also redirected from the centerline. The use of the actuator line model also reveal unsteady aerodynamic characteristics that cannot be captured by lower-fidelity models. For the upstream rotor, the yaw misalignment results in time-varying change in the local angle of attack on the blade, giving rise to unsteady loading. The downstream rotor is partially submerged in the deflected wake incurred by the yawed upstream rotor. As the blade revolves into and out of the wake deficit, the blade experiences cyclic loading, leading to even stronger fluctuations in the aerodynamic loads than the upstream rotor. These analysis provides a comprehensive understanding of the yaw control effects on the two tandem rotors from the perspectives of aerodynamic performance, wake profiles, and unsteady characteristics. In conclusion, the insights gained from the present study can aid the design of collective yaw control strategies of wind farms, and lay the foundation for assessing the fatigue damage associated with yaw misalignment.

17 WIND ENERGY↗
DOE OSTI2020

AMR-Wind [SWR-20-85]

AMR-Wind is a massively parallel, block-structured adaptive-mesh, incompressible flow solver for wind turbine and wind farm simulations. The solver is built on top of the AMReX library. AMReX is developed at LBNL , NREL , and ANL as part of the Block-Structured AMR Co-Design Center in DOE's Exascale Computing Project. AMReX library provides the mesh data structures, mesh adaptivity, as well as the linear solvers used for solving the governing equations. The primary applications for AMR-Wind are: performing large-eddy simulations (LES) of atmospheric boundary layer (ABL) flows, simulating wind farm turbine-wake interactions using actuator disk or actuator line models for turbines, and as a background solver when coupled with a near-body solver with overset methodology to perform blade-resolved simulations of multiple wind turbines within a wind farm.

Ananthan, Shreyas↗
DOE OSTI2021

Accomplishments and Year-End Performance Report; Wind Energy Program: Fiscal Year 2021

The National Wind Technology Center (NWTC), located at the U.S. Department of Energy's (DOE's) National Renewable Energy Laboratory (NREL) Flatirons Campus, has been a driving force in advancing wind energy technology research worldwide since its designation as a DOE national research center in 1992. Enabled by the Flatirons Campus's world-class facilities, scientists, engineers, analysts, and researchers are pushing the frontiers of science to pursue wind energy innovation. In Fiscal Year (FY) 2021, NREL continued to provide the technical expertise, research capabilities, and industry understanding to support DOE's ambitious climate action and research goals by advancing technology, addressing market and deployment barriers, and driving down costs with more efficient, reliable, and predictable wind energy systems. One of several highlights, NREL received an R&D 100 Special Recognition Award for its Thermoplastic Resin System for Wind Turbine Blades. This breakthrough in the wind turbine manufacturing process will enable the production of recyclable blades that are stronger, longer, and less expensive, while increasing energy capture, decreasing energy and transportation costs, and increasing blade reliability. In a year when the entire U.S. economy struggled to address workforce gaps, an NREL study compared wind industry needs, training programs, and hiring practices with perspectives from students and recent college graduates. Researchers hope that, by pinpointing areas of disconnect, the expectations of employers who have difficulty filling entry-level jobs can better align with the preparation of the potential applicants who find it hard to break into the field. The lab also made numerous new data and modeling resources available in FY 2021. Recent NREL releases include a modeling tool for predicting the power performance and structural loads of wind turbines within a wind farm (FAST.Farm), a computational framework for modeling golden eagle behavior near wind farms, and 20 years of offshore wind data. Updates were also made to the widely used Wind Plant Integrated Systems Design and Engineering Model (WISDEM), which couples engineering and cost models to examine system-level trade-offs. Now, bolstered by a renewed national commitment to tackle climate change and revitalize the U.S. economy through increased investment in clean energy - particularly in offshore wind energy - NREL stands poised to lead the way to a sustainable future that powers the United States with significant levels of reliable, low-cost, accessible wind energy. This report provides an overview of the achievements NREL made on behalf of DOE's Wind Energy Technologies Office (WETO) and other partners during FY 2021 (between Oct. 1, 2020, and Sept. 30, 2021).

Flatirons Campus↗
DOE OSTI2020

Estimation of Large-Scale Wind Field Characteristics Using Supervisory Control and Data: Preprint

As the wind energy industry continues to pushfor increased power production and lower cost of energy, thefocus of research has expanded from individual turbines toentire wind farms. Among a host of interesting problems to besolved when considering the wind farm as a whole, we considerthe challenge of scalar field estimation, based on informationalready collected at the individual turbine level. We aim toestimate the large-scale, low-frequency characteristics of thewind field, such as the mean wind direction and the overalldecrease in wind speed across the farm, and employ a Kalmanfilter that models the wind field using a polynomial function.We compare the proposed method’s performance to both asimple averaging technique and filtering of individual turbinemeasurements. The method presented is not limited to windturbines and is applicable in other situations where multipleremote agents are used to estimate a scalar field.

large scale↗
DOE OSTI2023

AWAKEN

The American WAKE experimeNt (AWAKEN) is a landmark collaborative international wake observation and validation campaign. Wake interactions are among the least understood and most impactful physical interactions in wind plants today, leading to unexpected power losses and increased operations and maintenance costs. The AWAKEN campaign is designed to gather observational data to address the most pressing science questions about wind turbine wake interactions and aerodynamics and to further understand wake behavior and validate wind plant models. Simultaneously, the AWAKEN campaign will also focus on testing of wind farm control strategies that have been shown to increase wind plant power production. Leveraging the expertise and resources of a large body of National Laboratories, academic institutions, and industry partners will lead to improved wind farm layout with greater power production and improved reliability, ultimately leading to lower wind energy costs.

17 WIND ENERGY↗
DOE OSTI2021

Computational Math Problems for a Clean Energy Future

Cutting edge computational mathematics are ubiquitous in renewable energy research. Problems in resilient and reliable electric grid operations, infrastructure planning, wind farm yaw control, and more demand sophisticated and scalable computational tools that enable the transition of renewable energy technologies from proof of concept to deployment into our energy system. The mission of the Computational Science Center at NREL is to lead the lab's efforts to solve energy challenges using high-performance computing (HPC), computational science, applied mathematics, scientific data management, visualization, and informatics. In this poster, we provide a short overview of three areas of computational mathematics research at NREL: wind power scenario generation for stochastic grid operations and infrastructure planning, improved rational function approximations for electromagnetic transients codes, and wind farm yaw control using a combination of the Alternating Direction Method of Multipliers (ADMM) and reinforcement learning (RL). Increasing penetrations of renewable energy into power grids motivate the investigation of new approaches to characterizing uncertainty for five-minute economic dispatch problems. Similarly, as the penetration of distributed energy resources on power grids increases, it becomes important to revisit our methods of modelling transient phenomena, i.e. electromagnetic transients programs. Finally, the combination of ADMM and RL for wind farm yaw control presented here can potentially increase the efficiency of the deployed distributed controllers by orders of magnitude.

ADMM↗
DOE OSTI2024

A Tutorial on the Control of Floating Offshore Wind Turbines: Stability Challenges and Opportunities for Power Capture

Climate change is a serious threat facing humanity. The United States (U.S.) and many other countries are increasing the amount of electrical power generated from renewable energy sources in an effort to combat climate change and ensure energy independence. The U.S. has set goals to achieve a 100% decarbonized electric grid by 2035 and a net-zero emissions economy by no later than 2050. Renewable energy currently accounts for about 20% of the U.S. power grid. According to the U.S. Department of Energy and the National Renewable Energy Laboratory (NREL), in the U.S. in 2021, wind and solar photovoltaic generation supplied 9.1% and 4% of total electricity generation, respectively, and the latest publicly available data show that hydropower represented 6.6% of all electricity generated in the U.S. in 2019. As wind farms have been built in many of the best wind resource areas on land, the U.S. and many other countries are turning to offshore wind for further growth of wind power capacity. Further, the U.S. has committed to deploy 30 GW of offshore wind by 2030, a significant increase from the 0.04 GW of installed offshore wind in the country as of the end of 2023. Many other countries have also established ambitious goals or plans to increase the amount of installed offshore wind power.

17 WIND ENERGY↗
DOE OSTI2024

Software-Defined Virtual Synchronous Condenser

Synchronous condensers (SCs) play important roles in integrating wind energy into relatively weak power grids. However, the design of SCs usually depends on specific application requirements and may not be adaptive enough to the frequently-changing grid conditions caused by the transition from conventional to renewable power generation. This paper devises a software-defined virtual synchronous condenser (SDViSC) method to address the challenges. Our contributions are fourfold: 1) design of a virtual synchronous condenser (ViSC) to enable full converter wind turbines to provide built-in SC functionalities; 2) engineering SDViSCs to transfer hardware-based ViSC controllers into software services, where a Tustin transformation-based software-defined control algorithm guarantees accurate tracking of fast dynamics under limited communication bandwidth; 3) a software-defined networking-enhanced SDViSC communication scheme to allow enhanced communication reliability and reduced communication bandwidth occupation; and 4) Prototype of SDViSC on our real-time, cyber-in-the-loop digital twin of large-wind-farm in an RTDS environment. Furthermore, extensive test results validate the excellent performance of SDViSC to support reliable and resilient operations of wind farms under various physical and cyber conditions.

17 WIND ENERGY↗
DOE OSTI2024

The IEA Wind Task 49 Reference Floating Wind Array Design Basis

International Energy Agency Wind Technology Collaboration Programme (IEA Wind) Task 49 on Integrated Design of Floating Wind Arrays is an international collaboration aiming to advance the development of large-scale floating wind farms by providing open-access resources to the research and development and planning communities. The work of Task 49 focuses on array-level challenges related to the colocation of many floating wind turbines; their layouts, mooring systems, and cabling systems; failure risks; logistical considerations; marine spatial planning needs; and future research needs and innovation directions. This report provides a general design basis for the development of reference floating wind farm designs. These reference array designs will extend the scope of existing reference floating wind turbine designs to facilitate research on array-level floating wind technology challenges and innovations. The design basis promotes coordination and consistency in developing the reference array designs.

17 WIND ENERGY↗
NASA NTRS1980

MOD-2 wind turbine farm stability study

The dynamics of single and multiple 2.5 ME, Boeing MOD-2 wind turbine generators (WTGs) connected to utility power systems were investigated. The analysis was based on digital simulation. Both time response and frequency response methods were used. The dynamics of this type of WTG are characterized by two torsional modes, a low frequency 'shaft' mode below 1 Hz and an 'electrical' mode at 3-5 Hz. High turbine inertia and low torsional stiffness between turbine and generator are inherent features. Turbine control is based on electrical power, not turbine speed as in conventional utility turbine generators. Multi-machine dynamics differ very little from single machine dynamics.

Hinrichsen, E. N.↗
DOE OSTI2021

Control-Oriented Model for Secondary Effects of Wake Steering

This paper presents a model to incorporate the secondary effects of wake steering in large arrays of turbines. Previous models have focused on the aerodynamic interaction of wake steering between two turbines. The model proposed in this paper builds on these models to include yaw-induced wake recovery and secondary steering seen in large arrays of turbines when wake steering is performed. Turbines operating in yaw-misaligned conditions generate counter-rotating vortices that entrain momentum and contribute to the deformation and deflection of the wake at downstream turbines. Rows of turbines can compound the effects of wake steering that benefit turbines far downstream. This model quantifies these effects and demonstrates that wake steering has greater potential to increase the performance of a wind farm due to these counter-rotating vortices especially for large rows of turbines. This is validated using numerous large-eddy simulations for three-turbine, five-turbine, and wind farm scenarios.

17 WIND ENERGY↗
NASA NTRS1982

Potential errors in using one anemometer to characterize the wind power over an entire rotor disk

Wind data collected at four levels on a 90-m tower in a prospective wind farm area are used to evaluate how well the 10-m wind speed data with and without intermittent vertical profile measurements compare with the 90-m tower data. If a standard, or even predictable, wind speed profile existed, there would be no need for a large, expensive tower. This cost differential becomes even more significant if several towers are needed to study a prospective wind farm.

Simon, R. L.↗
DOE OSTI2020

Overview of FLORIS updates

In this paper, we review updates made to the FLORIS (FLOw Redirection and Induction in Steady State) open-source framework for wind farm control modeling, design and analysis. The updates are focused on improvements for large arrays of turbines - including heterogenous inflows and incorporating second-order wake steering effects - design, and analysis tools for practical application of wind farm control, and improvements to the software architecture for best practices in modularization and cooperative development.

17 WIND ENERGY↗
DOE OSTI2021

Dynamic P-Q Capability and Abnormal Operation Analysis of a Wind Turbine with Doubly-Fed Induction Generator

After several accidents occurred in wind farms in the United States and around the world, the subsynchronous oscillation (SSO) issues in grid-connected wind farms have gained serious attention. Particularly, these issues have caused significant challenges to wind turbines with a doubly fed induction generator (DFIG) because it is connected to the grid via both its stator and rotor paths. Traditionally, a P-Q capability chart is utilized to assure the safe operation boundary for a synchronous generator. But the energy conversion characteristics of a DFIG wind turbine are completely different. A critical factor to affect the reliable operation of a DFIG wind turbine is the rated current and pulse-width modulation (PWM) saturation constraints of its power converters. These constraint conditions can be affected by the wind turbine rotating speed and grid conditions. However, a detailed study of DFIG P-Q capability from these perspectives has not been conducted, which has hindered adequate understanding of many abnormal wind turbine operations reported in the literature and the development of advanced control technologies to overcome the challenges. The proposed study in this paper considers vector control implementation to DFIG power electronic converters in the dq reference frame, and the models and algorithms developed for the P-Q capability study have addressed specific DFIG power converter constraints that are different from those of a traditional synchronous generator. The paper especially focuses on exploring the dynamic natures of DFIG P-Q capability under uncertain and variable conditions to explore the root causes of many abnormal operations of DFIG wind turbines reported in the literature. The proposed study is validated through an electromagnetic transient simulation model of a grid-connected DFIG wind turbine. The proposed study has the potential to lead to the development of new DFIG control technologies that can help overcome the challenges for many abnormal operations of DFIG wind turbines.

17 WIND ENERGY↗
DOE OSTI2026

Benchmarking of three DWM-based wake models at below-rated wind speeds

Wind turbine wake models are essential tools for predicting power losses and structural loads in wind farms. Among these, the dynamic wake meandering (DWM) model, included as a recommended approach in the International Electrotechnical Commission design standard, is a widely used engineering-fidelity method that balances accuracy and computational cost. This study compares the performance of three DWM-based wake model implementations (from the Technical University of Denmark, the National Renewable Energy Laboratory, and the Institute for Energy Technology) under below-rated wind speed conditions. Model predictions of wake flow, power output, and structural loads for a four-turbine row are evaluated across different ambient turbulence levels and wind-direction misalignments and compared against high-fidelity large-eddy simulation results. All three models captured the overall wake evolution and mean turbine performance with reasonable accuracy; their predicted time-averaged thrust and power were typically within 5 %–10 % of the large-eddy simulation benchmark. However, notable differences emerged in wake structure and unsteady load predictions, with discrepancies increasing for turbines further downstream. These differences highlight the importance of modelling choices such as wake summation and turbulence treatment, which strongly influence power-deficit and fatigue-load predictions. Comparison with large-eddy simulations reveals each approach's strengths and weaknesses, indicating where improvements are needed. Overall, the findings point to specific refinements for DWM models to improve their fidelity, ultimately enabling more robust wake predictions for wind farm design and operation.

17 WIND ENERGY↗
DOE OSTI2023

U.S. Offshore Wind Energy Noise Reduction Associated with Installation of Fixed-Bottom Foundations: Workshop Report

As offshore wind energy development grows in the United States, solutions are needed to reduce the underwater noise and substrate vibration generated during fixed-bottom turbine installation to help protect marine life. Monopiles are currently the main turbine foundation type installed globally and impact pile driving, the primary installation method, can be a major source of noise and vibration generation during wind farm construction. Opportunities exist to reduce the amount of noise and vibration produced during future offshore wind farm development. The use of alternative foundation types and installation methods, as well as innovative noise abatement technologies, would help reduce the potential detrimental effects on sensitive marine species. To explore these opportunities, the Department of Energy’s Wind Energy Technologies Office, in collaboration with the Bureau of Ocean Energy Management and the National Oceanic and Atmospheric Administration, funded the National Renewable Energy Laboratory and the Pacific Northwest National Laboratory to organize, host, and facilitate a virtual workshop in December 2022. The goal of the workshop was to gather input from the offshore wind energy community on noise reduction strategies for the installation of fixed-bottom offshore wind turbines in U.S. waters across multiple regions, including the U.S. Atlantic Coast, Gulf of Mexico, and Great Lakes to inform recommendations on future research. The joint lab team convened industry representatives, subject matter experts, and regulators to discuss potential pathways to reduce noise and vibration associated with fixed-bottom turbine installation, including the practicality of using alternative foundations and installation methods, the effectiveness of noise abatement technologies, as well as research and monitoring needs. In preparation for the workshop, the team invited experts to be part of a steering committee and worked with its members to help focus activities to meet the workshop goals. Additional pre-workshop activities included developing the invitee list and workshop agenda, reviewing existing Construction and Operations Plans (COP) for proposed offshore wind projects, distributing a brief questionnaire to industry representatives, and drafting the workshop discussion questions and Mural boards. In total, 128 workshop participants provided over 600 comments in response to the 17 group discussion questions used over two workshop sessions. Overarching recommendations highlighted across themes included future investments to provide data sharing, consistency, transparency, and opportunities for sharing best available science, knowledge, and expertise. The joint lab team synthesized the comments and identified four key research and development themes that could help advance the successful implementation of noise and vibration reduction strategies (see report). This report provides an overview of the workshop goals and scope, reviews the pre-workshop activities, presents brief summaries of participant feedback, and concludes with detailed research themes and recommendations for future investments. Appendix A includes the group discussion questions, Appendix B includes the results of the COP review, and Appendix C includes the results of the industry questionnaire. Overall, there was a high level of interest and engagement in the workshop. The sessions provided an opportunity for significant exchange of information between workshop participants from across sectors. Participants identified a variety of opportunities for next steps towards the noise reduction of offshore wind turbine installation in U.S. waters, including recommendations for future investments to provide certainty in the use of new technologies associated with alternative foundation types, noise abatement systems, and efficacy monitoring.

17 WIND ENERGY↗
DOE OSTI2022

Lifetime fatigue response due to wake steering on a pair of utility-scale wind turbines

Quantifying the impacts on turbine loads during wind farm control is an important consideration in assessing power production benefits. Wake steering controls aim to improve total wind farm performance by coordinating the control actions of individual turbines, wherein an upstream turbine is intentionally yawed at an offset angle from the measured wind direction. Consequently, this redirects its wake for improved power production and potentially reduces fatigue loads of the downstream turbines. This paper studies the lifetime fatigue loads associated with wake steering by using utility-scale wind turbine experimental data to conduct an analysis on a pair of wind turbines. This study was part of a large field experiment in which a group of five GE 1.5-MW SLE CWE turbines were selected as targets for conducting wake steering research. A standard loads instrumentation package and data acquisition system were installed on two turbines within the cluster to measure turbine fundamental loads. The time-series databases were used to calculate loads statistics as well as short-term and lifetime damage equivalent loads. Fatigue calculations followed the guidance in Annex H of the International Electrotechnical Commission standard 61400-1, Edition 4. Lifetime fatigue calculation results are presented in this analysis; three methods of assessing lifetime fatigue were used to determine percent difference for blade root moments, main shaft moments, main shaft torque, and tower top torque. For all three fatigue treatments, some components’ lifetime fatigue increases for the controlled turbine; however, the downwind turbine experienced a reduction in lifetime fatigue and combined effect for the turbine pair results in a reduction of fatigue when wake steering controls are applied.

17 WIND ENERGY↗