Exploring the Impact of Near-Term Innovations on the Technical Potential of Land-Based Wind Energy

O&M, wake steering, and climbing cranes. Our aim is to quantify the cost reductions and changes in performance from these innovations in relative terms while holding other modeling assumptions fixed (e.g., differences between regional energy markets and land costs). This approach enables us to examine the regional cost reductions and explore where and by how much these innovations reduce LCOE. Geographically, this study aims to evaluate the potential for wind energy across CONUS, with a specific focus on areas that have seen low levels of deployment (e.g., parts of the South, Southeast, and Intermountain West). This study finds that near-term innovations in land-based wind technology result in lower LCOE values relative to the baseline technology in nearly every location in CONUS, with larger LCOE reductions in areas with wind resource lower than the current fleetwide average (Wiser et al. 2021). This expansion provides an opportunity for land-based wind to contribute more to the renewable energy deployment and climate mitigation targets of the United States.

[1]  Pietro Bortolotti,et al.  Toward the Advanced Manufacturing of Land-Based Wind Turbine Blades , 2023, AIAA SCITECH 2023 Forum.

[2]  J. Lundquist,et al.  Grand Challenges: wind energy research needs for a global energy transition , 2022, Wind Energy Science.

[3]  Jonathan L. Ho,et al.  Examining Supply-Side Options to Achieve 100% Clean Electricity by 2035 , 2022 .

[4]  Annika Eberle,et al.  Scaling trends for balance-of-system costs at land-based wind power plants: Opportunities for innovations in foundation and erection , 2021, Wind Engineering.

[5]  Christopher J. Bay,et al.  Objective and Algorithm Considerations When Optimizing the Number and Placement of Turbines in a Wind Power Plant , 2021, Wind Energy Science.

[6]  M. Lerner Local power: Understanding the adoption and design of county wind energy regulation , 2021, Review of Policy Research.

[7]  N. Darghouth,et al.  Land-Based Wind Market Report: 2021 Edition , 2021 .

[8]  Paula Doubrawa,et al.  Demonstration of Wake Steering Through Yaw Control in a Wind Plant Field Experiment: Cooperative Research and Development Final Report, CRADA Number CRD-16-00629 , 2021 .

[9]  T. Mai,et al.  Land use and turbine technology influences on wind potential in the United States , 2021 .

[10]  T. Mai,et al.  Interactions of wind energy project siting, wind resource potential, and the evolution of the U.S. power system , 2021 .

[11]  P. Fleming,et al.  Evaluation of the potential for wake steering for U.S. land-based wind power plants , 2021, Journal of Renewable and Sustainable Energy.

[12]  H. Madsen,et al.  Competitiveness of a low specific power, low cut-out wind speed wind turbine in North and Central Europe towards 2050 , 2021, Applied Energy.

[13]  P. Beiter,et al.  2019 Cost of Wind Energy Review , 2020 .

[14]  B. Ó. Gallachóir,et al.  Wind turbine cost reduction: A detailed bottom-up analysis of innovation drivers , 2020 .

[15]  Taeseong Kim,et al.  Active tip deflection control for wind turbines , 2020 .

[16]  R. Wiser,et al.  Opportunities for and challenges to further reductions in the “specific power” rating of wind turbines installed in the United States , 2020, Wind Engineering.

[17]  K. Dykes,et al.  NREL's Balance-of-System Cost Model for Land-Based Wind , 2019 .

[18]  Fabian Wendt,et al.  Investigation of Innovative Rotor Concepts for the Big Adaptive Rotor Project , 2019 .

[19]  Travis M. Williams,et al.  The Renewable Energy Potential (reV) Model: A Geospatial Platform for Technical Potential and Supply Curve Modeling , 2019 .

[20]  R. Wiser,et al.  Assessing wind power operating costs in the United States: Results from a survey of wind industry experts , 2019, Renewable Energy Focus.

[21]  Jake D. Nunemaker,et al.  Increasing Wind Turbine Tower Heights: Opportunities and Challenges , 2019 .

[22]  T. Mai,et al.  2018 Standard Scenarios Report: A U.S. Electricity Sector Outlook , 2018 .

[23]  Nate Blair,et al.  System Advisor Model (SAM) General Description (Version 2017.9.5) , 2018 .

[24]  Rick Damiani,et al.  Analysis of Ideal Towers for Tall Wind Applications , 2018 .

[25]  G. Scott,et al.  2018 Cost of Wind Energy Review , 2017 .

[26]  M. Hand,et al.  Enabling the SMART Wind Power Plant of the Future Through Science-Based Innovation , 2017 .

[27]  Inês L. Azevedo,et al.  Should we build wind farms close to load or invest in transmission to access better wind resources in remote areas? A case study in the MISO region , 2016 .

[28]  Galen Maclaurin,et al.  Transportation of Large Wind Components: A Review of Existing Geospatial Data , 2016 .

[29]  B. Maples,et al.  2014 Cost of Wind Energy Review , 2015 .

[30]  Bri-Mathias Hodge,et al.  The Wind Integration National Dataset (WIND) Toolkit , 2015 .

[31]  Shreyas Ananthan,et al.  Enabling Wind Power Nationwide , 2015 .

[32]  Ryan Wiser,et al.  Understanding wind turbine price trends in the U.S. over the past decade , 2012 .

[33]  M. Hand,et al.  Wind Turbine Design Cost and Scaling Model , 2006 .

[34]  R. Poore,et al.  Development of an Operations and Maintenance Cost Model to Identify Cost of Energy Savings for Low Wind Speed Turbines: July 2, 2004 -- June 30, 2008 , 2008 .