• DocumentCode
    3665180
  • Title

    Ambient signal based load model parameter identification using optimization method

  • Author

    Xinran Zhang; Chao Lu;Yingduo Han; Songtai Yu; Jifeng Wang;He Huang; Yinsheng Su

  • Author_Institution
    State Key Laboratory of Control and Simulation of Power System and Generation Equipments, Tsinghua University, Beijing, China
  • fYear
    2015
  • fDate
    7/1/2015 12:00:00 AM
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Load modelling is a crucial part in modelling a power system. The complex, nonlinear and stochastic characteristics of power load increase the difficulty of modelling. In this paper, a new approach of ambient signal based load model parameter identification method is proposed to solve this problem. With the proposed method, load model parameter can be identified in any time regardless of the existence of fault. First, Z+M model is simplified to reduce the number of parameters to be identified. Then, parameters of Z+M model are identified with an optimization method, the objective function of which is calculated from WAMS measured power and voltage data. An iterative process is proposed to solve the problem of initial value sensitivity in optimization problems. Finally, the effectiveness of this identification method is validated through the simulation results on WSCC three machines nine nodes system under different operation situation including both small disturbance and large disturbance.
  • Keywords
    "Load modeling","Optimization","Integrated circuit modeling","Parameter estimation","Data models","Reactive power","Power measurement"
  • Publisher
    ieee
  • Conference_Titel
    Power & Energy Society General Meeting, 2015 IEEE
  • ISSN
    1932-5517
  • Type

    conf

  • DOI
    10.1109/PESGM.2015.7285620
  • Filename
    7285620