Multi-objective turbine allocation on a wind farm site

被引:5
|
作者
Dincer, A. E. [1 ]
Demir, A. [2 ]
Yilmaz, K. [3 ]
机构
[1] Abdullah Gul Univ, Hydraul Lab, Dep Civil Eng, TR-38080 Kayseri, Turkiye
[2] Abdullah Gul Univ, Struct Lab, Dep Civil Eng, TR-38080 Kayseri, Turkiye
[3] Yasar Univ, Hydraul Lab, Dep Civil Eng, Izmir, Turkiye
关键词
Multi -objective turbine allocation; Wind farm layout optimization; Site selection; Geographic information system (GIS); Analytical hierarchy process (AHP); Renewable energy; LAYOUT OPTIMIZATION; GENETIC ALGORITHM; SUITABILITY ASSESSMENT; OPTIMAL PLACEMENT; POWER PRODUCTION; ENERGY; SELECTION; DESIGN; MODEL; WAKES;
D O I
10.1016/j.apenergy.2023.122346
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
The Multi-Objective Turbine Allocation (MOTA) method is introduced as a novel approach for wind farm layout optimization and site selection. By incorporating Geographic Information System (GIS) tools and the Analytical Hierarchy Process (AHP), the MOTA method offers a comprehensive solution to balance energy production, cost factors, and environmental impacts. In this study, the MOTA method is applied to Go center dot kceada, Turkiye, for wind farm development. Results show that the MOTA method effectively proposes the optimum wind farm layout by selecting the best site for each turbine. The sequential turbine allocation approach, integration of multiple objectives, and use of GIS tools and AHP are the key capabilities and novelties of the MOTA method. The method allows for flexible investment decisions, considering technical and economic aspects. The outcomes from the Go center dot kceada case study highlight the effectiveness of the MOTA method in maximizing energy production while considering cost factors and environmental impacts. The results indicate that for the selected objective functions, the optimal net profit is attained with the installation of 155 turbines on Go center dot kceada. The MOTA method presents a practical and efficient solution for wind farm development, contributing to sustainable and efficient renewable energy generation.
引用
收藏
页数:18
相关论文
共 50 条
  • [1] Wind turbine selection for wind farm layout using multi-objective evolutionary algorithms
    Montoya, Francisco G.
    Manzano-Agugliaro, Francisco
    Lopez-Marquez, Sergio
    Hernandez-Escobedo, Quetzalcoatl
    Gil, Consolacion
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2014, 41 (15) : 6585 - 6595
  • [2] Multi-site and multi-objective optimization for wind turbines based on the design of virtual representative wind farm
    Song, Dongran
    Xu, Shanmin
    Huang, Lingxiang
    Xia, E.
    Huang, Chaoneng
    Yang, Jian
    Hu, Yang
    Fang, Fang
    [J]. ENERGY, 2022, 252
  • [3] Multi-Objective Structural Optimization of a Wind Turbine Tower
    Zheng Y.
    Zhang L.
    Pan Y.
    He Z.
    [J]. Zheng, Yuqiao (zhengyuqiaolut@163.com), 1600, Shanghai Jiaotong University (25): : 538 - 544
  • [4] Multi-Objective Optimisation of the Benchmark Wind Farm Layout Problem
    Manikowski, Pawel L.
    Walker, David J.
    Craven, Matthew J.
    [J]. JOURNAL OF MARINE SCIENCE AND ENGINEERING, 2021, 9 (12)
  • [5] Multi-objective Optimization of Ply Parameters for Wind Turbine Blade
    Dong, Xinhong
    Sun, Pengwen
    Zhang, Lanting
    Wang, Zongtao
    [J]. Jixie Gongcheng Xuebao/Journal of Mechanical Engineering, 2022, 58 (04): : 165 - 173
  • [6] The Multi-objective Optimization Of The Planet Carrier In Wind Turbine Gearbox
    Yi, Pengxing
    Dong, Lijian
    Chen, Yuanxin
    [J]. FRONTIERS OF MECHANICAL ENGINEERING AND MATERIALS ENGINEERING, PTS 1 AND 2, 2012, 184-185 : 565 - 569
  • [7] Fast and Effective Multi-Objective Optimisation of Wind Turbine Placement
    Tran, Raymond
    Wu, Junhua
    Denison, Christopher
    Ackling, Thomas
    Wagner, Markus
    Neumann, Frank
    [J]. GECCO'13: PROCEEDINGS OF THE 2013 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE, 2013, : 1381 - 1388
  • [8] Multi-objective optimization design of small wind turbine blade
    Xie Yongzhi
    Zhang Huan
    Qin Jianhua
    [J]. 2019 4TH INTERNATIONAL CONFERENCE ON INTELLIGENT INFORMATION PROCESSING (ICIIP 2019), 2019, : 288 - 291
  • [9] Wake redirection control for offshore wind farm power and fatigue multi-objective optimisation based on a wind turbine load indicator
    Sun, Jili
    Yang, Jingqing
    Jiang, Zezhong
    Xu, JinFeng
    Meng, Xiaofei
    Feng, Xiaoguang
    Si, Yulin
    Zhang, Dahai
    [J]. Energy, 2024, 313
  • [10] A Multi-Objective Optimization Approach to Active Power Control of Wind Farm
    Zou, Jianxiao
    Yao, Junping
    Zou, Qingze
    Xu, Hongbing
    Zhang, Zhenzhen
    [J]. JOURNAL OF SOLAR ENERGY ENGINEERING-TRANSACTIONS OF THE ASME, 2014, 136 (02):