Layout Method of Met Mast Based on Macro Zoning and Micro Quantitative Siting in a Wind Farm

被引:2
|
作者
Chen, Wenjin [1 ]
Qian, Gang [2 ]
Qi, Weiwen [2 ]
Luo, Gang [2 ]
Zhao, Lin [3 ]
Yuan, Xiaoling [3 ]
机构
[1] State Grid Zhejiang Elect Power Co Ltd, Hangzhou 310007, Peoples R China
[2] State Grid Shaoxing Power Supply Co, Shaoxing 312000, Peoples R China
[3] Hohai Univ, Coll Energy & Elect Engn, Nanjing 211100, Peoples R China
关键词
met mast layout; REOF; DPSO macro zoning; micro quantitative siting; POWER;
D O I
10.3390/pr10091708
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
In order to promote the wind monitoring accuracy and provide a quantitative planning method for met mast layout in practical projects, this paper proposes a two-stage layout method for met mast based on discrete particle swarm optimization (DPSO) zoning and micro quantitative siting. Firstly, according to the wind turbines layout, rotational empirical orthogonal function and hierarchical clustering methods are used to preliminarily determine zoning number. Considering the geographical proximity of wind turbines and the correlation of wind speed, an optimal macro zoning model of wind farm based on improved DPSO is established. Then, combined with the grid screening method and optimal layout evaluation index, a micro quantitative siting method of met mast is proposed. Finally, the rationality and efficiency of macro zoning method based on improved DPSO, as well as the objectivity and standardization of micro quantitative siting, are verified by an actual wind farm.
引用
收藏
页数:18
相关论文
共 50 条
  • [31] Developing offshore wind farm siting criteria by using an international Delphi method
    Ho, Lip-Wah
    Lie, Tek-Tjing
    Leong, Paul Tm
    Clear, Tony
    ENERGY POLICY, 2018, 113 : 53 - 67
  • [32] A SPATIAL PLANNING SUPPORT SYSTEM FOR WIND FARM CONSTRUCTION WITH MACRO AND MICRO PERSPECTIVES
    Kamkar, K.
    Motieyan, H.
    ISPRS GEOSPATIAL CONFERENCE 2022, JOINT 6TH SENSORS AND MODELS IN PHOTOGRAMMETRY AND REMOTE SENSING, SMPR/4TH GEOSPATIAL INFORMATION RESEARCH, GIRESEARCH CONFERENCES, VOL. 10-4, 2023, : 355 - 362
  • [33] HYBRID GA-PSO ALGORITHM FOR WIND FARM MICRO-SITING IN COMPLEX TERRAIN
    Hu W.
    Yang Q.
    Nie B.
    Chen H.
    Yan B.
    Xu Z.
    Taiyangneng Xuebao/Acta Energiae Solaris Sinica, 2024, 45 (05): : 118 - 125
  • [34] Wind farm micro-siting by Gaussian particle swarm optimization with local search strategy
    Wan, Chunqiu
    Wang, Jun
    Yang, Geng
    Gu, Huajie
    Zhang, Xing
    RENEWABLE ENERGY, 2012, 48 : 276 - 286
  • [35] Multi-objective genetic algorithm based innovative wind farm layout optimization method
    Chen, Ying
    Li, Hua
    He, Bang
    Wang, Pengcheng
    Jin, Kai
    ENERGY CONVERSION AND MANAGEMENT, 2015, 105 : 1318 - 1327
  • [36] Coupled On-Site Measurement/CFD Based Approach for Wind Resource Assessment and Wind Farm Micro-Siting Over Complex Terrain
    Hu, Weicheng
    Yang, Qingshan
    Zhang, Jian
    Hu, Jianxiao
    6TH INTERNATIONAL CONFERENCE ON ENVIRONMENTAL SCIENCE AND CIVIL ENGINEERING, 2020, 455
  • [37] A Novel Energy Yields Calculation Method for Irregular Wind Farm Layout
    Hou, Peng
    Hu, Weihao
    Soltani, Mohsen
    Chen, Zhe
    IECON 2015 - 41ST ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY, 2015, : 380 - 385
  • [38] A versatile multi-method ensemble for wind farm layout optimization
    Pérez-Aracil, J.
    Casillas-Pérez, D.
    Jiménez-Fernández, S.
    Prieto-Godino, L.
    Salcedo-Sanz, S.
    Journal of Wind Engineering and Industrial Aerodynamics, 2022, 225
  • [39] Optimization of wind turbines siting in a wind farm using genetic algorithm based local search
    Abdelsalam, Ali M.
    El-Shorbagy, M. A.
    RENEWABLE ENERGY, 2018, 123 : 748 - 755
  • [40] Optimal Micro-Siting of Wind Turbines in an Offshore Wind Farm Using Frandsen-Gaussian Wake Model
    Tao, Siyu
    Kuenzel, Stefanie
    Xu, Qingshan
    Chen, Zhe
    IEEE TRANSACTIONS ON POWER SYSTEMS, 2019, 34 (06) : 4944 - 4954