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Title: Development of FAST.Farm: A New Multiphysics Engineering Tool for Wind Farm Design and Analysis: Preprint

Abstract

This paper presents the development of FAST.Farm, a new multiphysics tool applicable to engineering problems in research and industry involving wind farm performance and cost optimization that is needed to address the current underperformance, failures, and expenses plaguing the wind industry. Achieving wind cost-of-energy targets - which requires improvements in wind farm performance and reliability, together with reduced uncertainty and expenditures - has been eluded by the complicated nature of the wind farm design problem, especially the sophisticated interaction between atmospheric phenomena and wake dynamics and array effects. FAST.Farm aims to balance the need for accurate modeling of the relevant physics for predicting power performance and loads while maintaining low computational cost to support a highly iterative and probabilistic design process and system-wide optimization. FAST.Farm makes use of FAST to model the aero-hydro-servo-elastics of distinct turbines in the wind farm, and it is based on some of the principles of the Dynamic Wake Meandering (DWM) model, but avoids many of the limitations of existing DWM implementations.

Authors:
; ; ; ;
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), NREL Laboratory Directed Research and Development (LDRD)
OSTI Identifier:
1339350
Report Number(s):
NREL/CP-5000-67528
DOE Contract Number:
AC36-08GO28308
Resource Type:
Conference
Resource Relation:
Conference: To be presented at AIAA SciTech 2017, 9-13 January 2017, Grapevine, Texas
Country of Publication:
United States
Language:
English
Subject:
17 WIND ENERGY; FAST.Farm; FAST; wind farm design and analysis; wake and array effects; dynamic wake meandering model; DWM

Citation Formats

Jonkman, Jason, Annoni, Jennifer, Hayman, Greg, Jonkman, Bonnie, and Purkayastha, Avi. Development of FAST.Farm: A New Multiphysics Engineering Tool for Wind Farm Design and Analysis: Preprint. United States: N. p., 2017. Web.
Jonkman, Jason, Annoni, Jennifer, Hayman, Greg, Jonkman, Bonnie, & Purkayastha, Avi. Development of FAST.Farm: A New Multiphysics Engineering Tool for Wind Farm Design and Analysis: Preprint. United States.
Jonkman, Jason, Annoni, Jennifer, Hayman, Greg, Jonkman, Bonnie, and Purkayastha, Avi. Sun . "Development of FAST.Farm: A New Multiphysics Engineering Tool for Wind Farm Design and Analysis: Preprint". United States. doi:. https://www.osti.gov/servlets/purl/1339350.
@article{osti_1339350,
title = {Development of FAST.Farm: A New Multiphysics Engineering Tool for Wind Farm Design and Analysis: Preprint},
author = {Jonkman, Jason and Annoni, Jennifer and Hayman, Greg and Jonkman, Bonnie and Purkayastha, Avi},
abstractNote = {This paper presents the development of FAST.Farm, a new multiphysics tool applicable to engineering problems in research and industry involving wind farm performance and cost optimization that is needed to address the current underperformance, failures, and expenses plaguing the wind industry. Achieving wind cost-of-energy targets - which requires improvements in wind farm performance and reliability, together with reduced uncertainty and expenditures - has been eluded by the complicated nature of the wind farm design problem, especially the sophisticated interaction between atmospheric phenomena and wake dynamics and array effects. FAST.Farm aims to balance the need for accurate modeling of the relevant physics for predicting power performance and loads while maintaining low computational cost to support a highly iterative and probabilistic design process and system-wide optimization. FAST.Farm makes use of FAST to model the aero-hydro-servo-elastics of distinct turbines in the wind farm, and it is based on some of the principles of the Dynamic Wake Meandering (DWM) model, but avoids many of the limitations of existing DWM implementations.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Sun Jan 01 00:00:00 EST 2017},
month = {Sun Jan 01 00:00:00 EST 2017}
}

Conference:
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