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Optimization of Alternative Wind Turbine Towers in Low Wind Resource Regions

Title: Optimization of Alternative Wind Turbine Towers in Low Wind Resource Regions.
Name(s): Al-Kaimakchi, Anwer, author
Jung, Sungmoon, professor directing thesis
Rambo-Roddenberry, Michelle Deanna, committee member
Spainhour, Lisa, committee member
Florida State University, degree granting institution
FAMU-FSU College of Engineering, degree granting college
Department of Civil and Environmental Engineering, degree granting department
Type of Resource: text
Genre: Text
Master Thesis
Issuance: monographic
Date Issued: 2017
Publisher: Florida State University
Place of Publication: Tallahassee, Florida
Physical Form: computer
online resource
Extent: 1 online resource (84 pages)
Language(s): English
Abstract/Description: Taller wind turbines with big wheel area have been proposed for low wind speed sites, where conventional 80m tower cannot produce enough electricity. Hub height of 140m gives the potential to all 50 states to produce power from wind. However, it is not clear which tower (steel, concrete or hybrid) is economically attractive beyond 80m, or which design parameter is most critical in enabling tall yet economic tower. The aim of this paper is to come up with optimum designs for steel, concrete and hybrid towers while minimizing wind turbine cost and maximizing power production and then study the influence of changing one design variable on optimum designs. Also, it was of interest to study the effect of defining rotor dimeter of turbine as an independent design variable or as function of height. Multiple optimal solutions were obtained, which are called Pareto-optimal solutions. The design variables were chosen to be diameter, thickness, height of tower and blade radius. Design constraints were buckling, yielding, shear stresses for steel tower and ultimate and service limit states for the concrete tower. Those constraints have been used to control the stability of the tower. Different linear constraints have been applied for each tower, e.g. radius of the rotor should be less than the height of the tower. The design problem is conceptual design so detailed design is beyond scope of this research, such as the flange for the steel tower, connection between the concrete parts, and connection between the steel and concrete for the hybrid tower. Nonetheless, the cost of these parts was added to the design problem. Due to the highly constrained, non-convex and non-linear nature of the design problem, Genetic algorithm has been chosen as a solver for the problem. The towers were analyzed for operational and nonoperational aerodynamic conditions according to IEC 61400-1. A comparison of steel, concrete and hybrid towers was analyzed for heights ranging (80m-150m). Results showed that up to 95m, the cost difference was negligible between all towers options. Beyond 95m hybrid towers were dominating the solutions. For 150m hub height, concrete tower saved 12% when it is compared to its steel counterpart. Concrete base diameter decreases to less than 10m, industry preferred, when average concrete wall thickness was equal or greater than 0.4m or compressive strength of concrete increases. Increasing compressive strength of concrete by 10% also resulted in cost reduction of 2.18% for 150m hub height. Results showed that defining rotor diameter as a design variable was better than defining it as a function of height because the optimization problem had fewer constraints.
Identifier: FSU_SUMMER2017_ALKAIMAKCHI_fsu_0071N_13989 (IID)
Submitted Note: A Thesis submitted to the Department of Civil and Environmental Engineering in partial fulfillment of the Master of Science.
Degree Awarded: Summer Semester 2017.
Date of Defense: June 19, 2017.
Keywords: Genetic algorithm, Optimization, power, wind turbine tower
Bibliography Note: Includes bibliographical references.
Advisory Committee: Sungmoon Jung, Professor Directing Thesis; Michelle Rambo-Roddenberry, Committee Member; Lisa Spainhour, Committee Member.
Subject(s): Civil engineering
Persistent Link to This Record:
Owner Institution: FSU

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Al-Kaimakchi, A. (2017). Optimization of Alternative Wind Turbine Towers in Low Wind Resource Regions. Retrieved from