Array Effects in Large Wind Farms: Cooperative Research and Development Final Report, CRADA Number CRD-09-343

Array Effects in Large Wind Farms: Cooperative Research and Development Final Report, CRADA Number CRD-09-343
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Total Pages: 0
Release: 2016
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The effects of wind turbine wakes within operating wind farms have a substantial impact on the overall energy production from the farm. The current generation of models drastically underpredicts the impact of these wakes leading to non-conservative estimates of energy capture and financial losses to wind farm operators and developers. To improve these models, detailed research of operating wind farms is necessary. Rebecca Barthelmie of Indiana University is a world leader of wind farm wakes effects and would like to partner with NREL to help improve wind farm modeling by gathering additional wind farm data, develop better models and increase collaboration with European researchers working in the same area. This is currently an active area of research at NREL and the capabilities of both parties should mesh nicely.

Array Effects in Large Wind Farms: Cooperative Research and Development Final Report, CRADA Number CRD-15-590

Array Effects in Large Wind Farms: Cooperative Research and Development Final Report, CRADA Number CRD-15-590
Author:
Publisher:
Total Pages: 0
Release: 2019
Genre:
ISBN:

The effects of wind turbine wakes within operating wind farms has a substantial impact on the overall energy production from the farm. The current generation of models drastically underpredicts the impact of these wakes offshore leading to non-conservative estimates of energy capture and financial losses to wind farm operators and developers. To improve these models, detailed research of operating wind farms is necessary. Cornell University is a world leader of wind farm wakes effects and would like to partner with NREL to help improve wind farm modeling (by gathering additional wind farm data), develop better models and increase collaboration with European researchers working in the same area.

University of Colorado - Center for Research and Education in Wind (CREW): Cooperative Research and Development Final Report, CRADA Number CRD-11-446

University of Colorado - Center for Research and Education in Wind (CREW): Cooperative Research and Development Final Report, CRADA Number CRD-11-446
Author:
Publisher:
Total Pages: 0
Release: 2016
Genre:
ISBN:

Enabled by petascale supercomputing, the next generation of computer models for wind energy will simulate a vast range of scales and physics, spanning from turbine structural dynamics and blade-scale turbulence to mesoscale atmospheric flow. A single model covering all scales and physics is not feasible. Thus, these simulations will require the coupling of different models/codes, each for different physics, interacting at their domain boundaries.

Develop Wake Mitigation Strategy: Cooperative Research and Development Final Report, CRADA Number CRD-17-00693

Develop Wake Mitigation Strategy: Cooperative Research and Development Final Report, CRADA Number CRD-17-00693
Author:
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Total Pages: 0
Release: 2021
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Wind turbines in a wind farm typically operate individually to maximize their own performance and do not take into account information from nearby turbines. In an autonomous wind farm, enabling cooperation to achieve farm-level objectives, turbines will need to use information from nearby turbines to optimize performance, ensure resiliency when other sensors fail, and adapt to changing local conditions. A key element of achieving an autonomous wind farm is to develop algorithms that provide necessary information to ensure reliable, robust, and efficient operation of wind turbines in a wind plant using local sensor information that is already being collected, such as supervisory control and data acquisition (SCADA) data, local meteorological stations, and nearby radars/sodars/lidars. In this work consensus control is applied in a hybrid analysis to data from an existing wind farm to demonstrate the benefit of consensus control.

DNV GL Joint Industry Project on Validation of Turbulence Models: Cooperative Research and Development Final Report, CRADA Number CRD-17-673

DNV GL Joint Industry Project on Validation of Turbulence Models: Cooperative Research and Development Final Report, CRADA Number CRD-17-673
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Total Pages: 0
Release: 2019
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This shared resource CRADA defines research collaborations between the National Renewable Energy Laboratory (NREL) and Det Norske Veritas (Norway) and Germanischer Lloyd (Germany), known as DNV GL, an international certification body. Under the terms and conditions described in this CRADA agreement, NREL will participate in a wind turbine Joint Industry Project (JIP) led by DNV GL, and including nine other Joint Industry Project sponsors and partners to examine the wind inflow models needed to define the design conditions for wind turbines, with specific focus on atmospheric turbulence. The international design standards are implemented by certification companies, such as DNV GL, the organizing agent of the JIPs. Through this collaboration, the JIP participants have the ability to improve wind turbine design, internationally, as well as in the United States, and can make this improvement by leveraging the significant aggregation of industry funds that has been organized by DNV GL.

Status of Wake and Array Loss Research

Status of Wake and Array Loss Research
Author:
Publisher:
Total Pages: 17
Release: 1991
Genre:
ISBN:

In recent years, many projects have evaluated wind turbine wake effects and resultant array losses in both Europe and the United States. This paper examines the status of current knowledge about wake effects and array losses and suggests future research. Single-turbine wake characteristics have been studied extensively and are generally described well by existing theoretical models. Field measurements of wake effects in wind turbine arrays are largely limited to small arrays, with 2 to 4 rows of turbines. Few data have been published on wake effects within large arrays. Measurements of wake deficits downwind of large arrays that deficits are substantially larger and extend farther downwind than expected. Although array design models have been developed, these models have been tested and verified using only limited data from a few rows of wind turbines in complex terrain, whereas some of the largest arrays have more than 40 rows of wind turbines. Planned cooperative efforts with the wind industry will obtain existing data relevant to analyzing energy deficits within large arrays and identifying data sets for potential use in array model verification efforts. Future research being considered include a cooperative research experiment to obtain more definitive data on wake deficits and turbulence within and downwind of large arrays. 16 refs., 9 figs., 1 tab.

Disciplinary Convergence in Systems Engineering Research

Disciplinary Convergence in Systems Engineering Research
Author: Azad M. Madni
Publisher: Springer
Total Pages: 1169
Release: 2017-11-24
Genre: Technology & Engineering
ISBN: 331962217X

The theme of this volume on systems engineering research is disciplinary convergence: bringing together concepts, thinking, approaches, and technologies from diverse disciplines to solve complex problems. Papers presented at the Conference on Systems Engineering Research (CSER), March 23-25, 2017 at Redondo Beach, CA, are included in this volume. This collection provides researchers in academia, industry, and government forward-looking research from across the globe, written by renowned academic, industry and government researchers.