Particle swarm optimization of a wind farm layout with active control of turbine yaws

被引:16
|
作者
Song, Jeonghwan [1 ]
Kim, Taewan [1 ]
You, Donghyun [1 ]
机构
[1] Pohang Univ Sci & Technol, Dept Mech Engn, 77 Cheongam Ro, Pohang 37673, Gyeongbuk, South Korea
基金
新加坡国家研究基金会;
关键词
Wind farm layout optimization; Active yaw control; Particle swarm optimization; Annual energy production; GENETIC ALGORITHM; DESIGN; WAKES; MODEL; EFFICIENCY; SPEED; PLANT; FLOW;
D O I
10.1016/j.renene.2023.02.058
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Higher annual energy production can be obtained by joint optimization which considers active yaw control in the layout design stage. Although accurate representation of a non-centrosymmetric three-dimensional yawed wake is necessary for the joint optimization of a realistic wind farm, it has not been considered. Furthermore, non-convexity in the joint optimization becomes severe because the layout and yaw angles have to be optimized for all wind directions considering non-centrosymmetric three-dimensional yawed wakes, leading to a not globally but locally optimal layout. To tackle the difficulty, a particle-swarm-optimization-based method which is capable of large-scale non-convex joint optimization is developed. In the present method, a farm layout is globally optimized with simultaneous consideration of yaw angles for various wind speeds and directions. The use of random initial particles which consist of the layout and yaw angles of wind turbines prevent from obtaining a locally optimal layout caused by non-convexity of the problem. The improvement in the annual energy production by the present simultaneously optimized layout is demonstrated.
引用
收藏
页码:738 / 747
页数:10
相关论文
共 50 条
  • [1] Offshore wind farm layout optimization using particle swarm optimization
    Pillai A.C.
    Chick J.
    Johanning L.
    Khorasanchi M.
    [J]. Journal of Ocean Engineering and Marine Energy, 2018, 4 (1) : 73 - 88
  • [2] Wind farm layout optimization through optimal wind turbine placement using a hybrid particle swarm optimization and genetic algorithm
    Qureshi, Tarique Anwar
    Warudkar, Vilas
    [J]. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2023, 30 (31) : 77436 - 77452
  • [3] Wind farm layout optimization through optimal wind turbine placement using a hybrid particle swarm optimization and genetic algorithm
    Tarique Anwar Qureshi
    Vilas Warudkar
    [J]. Environmental Science and Pollution Research, 2023, 30 : 77436 - 77452
  • [4] Wind Farm Layout Optimization with Different Hub Heights in Manjil Wind Farm Using Particle Swarm Optimization
    Yeghikian, Menova
    Ahmadi, Abolfazl
    Dashti, Reza
    Esmaeilion, Farbod
    Mahmoudan, Alireza
    Hoseinzadeh, Siamak
    Garcia, Davide Astiaso
    [J]. APPLIED SCIENCES-BASEL, 2021, 11 (20):
  • [5] Optimal Placement of Wind Turbines in Wind Farm Layout Using Particle Swarm Optimization
    Asaah, Philip
    Hao, Lili
    Ji, Jing
    [J]. JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY, 2021, 9 (02) : 367 - 375
  • [6] Optimal Placement of Wind Turbines in Wind Farm Layout Using Particle Swarm Optimization
    Philip Asaah
    Lili Hao
    Jing Ji
    [J]. Journal of Modern Power Systems and Clean Energy, 2021, 9 (02) : 367 - 375
  • [7] Wind Farm Layout Design using Modified Particle Swarm Optimization Algorithm
    Rehman, Shafiqur
    Ali, S. S. A.
    [J]. 2015 6TH INTERNATIONAL RENEWABLE ENERGY CONGRESS (IREC), 2015,
  • [8] Proposed particle swarm optimization technique for the wind turbine control system
    Iqbal, Atif
    Ying, Deng
    Saleem, Adeel
    Hayat, Muhammad Aftab
    Mateen, Muhammad
    [J]. MEASUREMENT & CONTROL, 2020, 53 (5-6): : 1022 - 1030
  • [9] COMPARISON OF OFFSHORE WIND FARM LAYOUT OPTIMIZATION USING A GENETIC ALGORITHM AND A PARTICLE SWARM OPTIMIZER
    Pillai, Ajit C.
    Chick, John
    Johanning, Lars
    Khorasanchi, Mahdi
    Barbouchi, Sami
    [J]. PROCEEDINGS OF THE ASME 35TH INTERNATIONAL CONFERENCE ON OCEAN, OFFSHORE AND ARCTIC ENGINEERING , 2016, VOL 6, 2016,
  • [10] The Effect of Acceleration Coefficients in Particle Swarm Optimization Algorithm with Application to Wind Farm Layout Design
    Rehman, Shafiqur
    Khan, Salman A.
    Alhems, Luai M.
    [J]. FME TRANSACTIONS, 2020, 48 (04): : 922 - 930