• DocumentCode
    3665303
  • Title

    Online clustering modeling of large-scale photovoltaic power plants

  • Author

    Zhimin Ma;Jinghong Zheng;Shouzhen Zhu;Xinwei Shen; Ling Wei;Xiaoyu Wang; Kun Men

  • Author_Institution
    Dept. of Electrical Engineering, Tsinghua University, Beijing, China
  • fYear
    2015
  • fDate
    7/1/2015 12:00:00 AM
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    This paper presents an online clustering modeling method for large-scale photovoltaic (PV) power plants. The proposed method utilizes the defined feature distance of inverter control parameters as the clustering index to derive the equivalent PV plant model. Based on the offline parameter database and the online matching method, the feature distance weighted by online parameter sensitivity is obtained to cluster PV generation units by using the K-means clustering algorithm. The method to acquire equivalent parameters of each clustered PV model is also presented. Simulation results show that the proposed online modeling method is effective and can track the dynamic characteristics of PV power plants accurately.
  • Keywords
    "Inverters","Sensitivity","Power system dynamics","Photovoltaic systems","Indexes"
  • Publisher
    ieee
  • Conference_Titel
    Power & Energy Society General Meeting, 2015 IEEE
  • ISSN
    1932-5517
  • Type

    conf

  • DOI
    10.1109/PESGM.2015.7285745
  • Filename
    7285745