Review of Recent Development of Dynamic Wind Farm Equivalent Models Based on Big Data Mining

2018 Asia Conference on Energy and Environment Engineering

能源学;生态环境科学

Wang, Chenggen^1 ; Zhou, Qian^1 ; Han, Mingzhe^2 ; Lv, Zhan'Ao^2 ; Hou, Xiao^2 ; Zhao, Haoran^2 ; Bu, Jing^3

State Grid Jiangsu Electric Power Company Research Institute, Nanjing, China^1

Shandong University, Jinan, China^2

Nanjing University of Science and Technology, Nanjing, China^3

关键词: Collector systems;    Dynamic winds;    Equivalent model;    Equivalent parameters;    It focus;    Wind farm;    Wind speed prediction;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/133/1/012016/pdf
DOI  :  10.1088/1755-1315/133/1/012016

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

Recently, the big data mining method has been applied in dynamic wind farm equivalent modeling. In this paper, its recent development with present research both domestic and overseas is reviewed. Firstly, the studies of wind speed prediction, equivalence and its distribution in the wind farm are concluded. Secondly, two typical approaches used in the big data mining method is introduced, respectively. For single wind turbine equivalent modeling, it focuses on how to choose and identify equivalent parameters. For multiple wind turbine equivalent modeling, the following three aspects are concentrated, i.e. aggregation of different wind turbine clusters, the parameters in the same cluster, and equivalence of collector system. Thirdly, an outlook on the development of dynamic wind farm equivalent models in the future is discussed.