DESIGN AND OPTIMIZATION OF A TIDAL TURBINE AND FARM

被引:0
|
作者
Mayeed, Mohammed S. [1 ]
机构
[1] Kennesaw State Univ, Dept Mech Engn, Marietta, GA 30060 USA
关键词
D O I
暂无
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Tidal ocean power is a dependable and dense form of renewable energy which is a relatively underdeveloped field. This study optimizes a tidal turbine with respect to performance and economics, and then optimizes a farm to be economically feasible. It was determined that the southeastern portion of the Gulf Stream, Florida current, would be used for the tidal turbine system as it has some of the world's fastest velocities and is relatively close to shore. The vertical axis designs were ruled out from extended research on turbine design for their lower efficiency in general. Only horizontal axis designs were tested in simulated environments. Using SolidWorks Flow Simulation and SolidWorks Simulation, turbine models were optimized and selected as having the potential for the greatest energy extraction. Static and fatigue analyses were conducted on the optimized models in order to prevent premature failure. Cost analysis was also performed on the turbine models and the model that had the lowest initial cost as well as the highest power generation was chosen for farm development. The optimized design produced reasonable amount of power considering varying velocities throughout the day having a diameter of about 30 m. Through fatigue analysis the optimized design also showed long enough lifetime so that a good return on investment can be acquired. The single optimized turbine was then placed in a farm, and the farm's shape and arrangement were tested and optimized so that the best arrangement and distances between units could be found. It was found that a farm 1.25 kilometers by 20 kilometers consisting of 800 turbines would be optimal. The farm would produce an average of 249.33 megawatts for a profit of $294.88 million dollars annually. The farm would pay for itself in 7.12 years and have an expected life span of 26.1 years which was obtained through fatigue analysis.
引用
收藏
页数:9
相关论文
共 50 条
  • [1] The Design and Optimization for The Dome of Tidal Turbine
    Lu, Hong-bo
    Li, Yong-lin
    Ma, Liang-liang
    Pao, Xiu-ling
    2012 INTERNATIONAL CONFERENCE ON FUTURE ELECTRICAL POWER AND ENERGY SYSTEM, PT B, 2012, 17 : 1710 - 1716
  • [2] Design and Optimization of Tidal Turbine Airfoil
    Grasso, F.
    JOURNAL OF AIRCRAFT, 2012, 49 (02): : 636 - 643
  • [3] Blade design and optimization of a horizontal axis tidal turbine
    Zhu, Fu-wei
    Ding, Lan
    Huang, Bin
    Bao, Ming
    Liu, Jin-Tao
    OCEAN ENGINEERING, 2020, 195
  • [4] Design and optimization for strength and integrity of tidal turbine rotor blades
    Liu, Pengfei
    Veitch, Brian
    ENERGY, 2012, 46 (01) : 393 - 404
  • [5] Tidal turbine hydrofoil design and optimization based on deep learning
    Li, Changming
    Liu, Bin
    Wang, Shujie
    Yuan, Peng
    Lang, Xianpeng
    Tan, Junzhe
    Si, Xiancai
    RENEWABLE ENERGY, 2024, 226
  • [6] Modeling tidal turbine farm with vertical axis tidal current turbines
    Li, Ye
    Lence, Barbara J.
    Calisal, Sander M.
    2007 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS, VOLS 1-8, 2007, : 1195 - +
  • [7] Impact of tidal turbine support structures on realizable turbine farm power
    Muchala, Subhash
    Willden, Richard H. J.
    RENEWABLE ENERGY, 2017, 114 : 588 - 599
  • [8] Design Optimization of a Tidal Current Turbine for Energy Harvesting Smart Buoy
    Honda, Ichiro
    Wang, Wantong
    Nagayama, Tokimune
    Yamada, Reiko
    Yokoi, Yuichi
    Kyozuka, Yusaku
    Sakaguchi, Daisaku
    OCEANS 2021: SAN DIEGO - PORTO, 2021,
  • [9] Gradient Based Optimization of Permanent Magnet Generator Design for a Tidal Turbine
    Rokke, Astrid
    2014 INTERNATIONAL CONFERENCE ON ELECTRICAL MACHINES (ICEM), 2014, : 1199 - 1205
  • [10] Tidal turbine hydrofoil optimization design based on NURBS and genetic algorithm
    Li Z.
    Sun Z.
    Zhang Q.
    Feng L.
    2018, University of Petroleum, China (42): : 141 - 147