Gradient-Based Optimization of Wind Farms with Different Turbine Heights [electronic resource] : Preprint
- Published:
- Washington, D.C. : United States. Dept. of Energy. Office of Energy Efficiency and Renewable Energy, 2017.
Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy - Physical Description:
- 1.6 MB : digital, PDF file
- Additional Creators:
- National Renewable Energy Laboratory (U.S.), United States. Department of Energy. Office of Energy Efficiency and Renewable Energy, and United States. Department of Energy. Office of Scientific and Technical Information
Access Online
- Restrictions on Access:
- Free-to-read Unrestricted online access
- Summary:
- Turbine wakes reduce power production in a wind farm. Current wind farms are generally built with turbines that are all the same height, but if wind farms included turbines with different tower heights, the cost of energy (COE) may be reduced. We used gradient-based optimization to demonstrate a method to optimize wind farms with varied hub heights. Our study includes a modified version of the FLORIS wake model that accommodates three-dimensional wakes integrated with a tower structural model. Our purpose was to design a process to minimize the COE of a wind farm through layout optimization and varying turbine hub heights. Results indicate that when a farm is optimized for layout and height with two separate height groups, COE can be lowered by as much as 5%-9%, compared to a similar layout and height optimization where all the towers are the same. The COE has the best improvement in farms with high turbine density and a low wind shear exponent.
- Report Numbers:
- E 1.99:nrel/cp-5000-67661
nrel/cp-5000-67661 - Subject(s):
- Other Subject(s):
- Note:
- Published through SciTech Connect.
05/08/2017.
"nrel/cp-5000-67661"
Presented at the American Institute of Aeronautics and Astronautics SciTech 2017, 16-20 January 2017, Dallas, Texas.
Stanley, Andrew P. J.; Thomas, Jared; Ning, Andrew; Annoni, Jennifer; Dykes, Katherine; Fleming, Paul. - Funding Information:
- AC36-08GO28308
View MARC record | catkey: 23767916