• DocumentCode
    3465955
  • Title

    Scalable distribution state estimation approach for Distribution Management Systems

  • Author

    De Alvaro Garcia, Leticia ; Grenard, Sébastien

  • Author_Institution
    EDF R&D, Clamart, France
  • fYear
    2011
  • fDate
    5-7 Dec. 2011
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    The flexibility and controllability of the distribution network is only possible if control centre tools and control engineers have a more accurate representation of the grid in real-time. Therefore, one of the main objectives of new Distribution Management Systems (DMS) is to enhance the observability of MV networks in order to run new automation functions such as Volt and Var control or network reconfiguration. To do so, Distribution State Estimation (DSE) functions can be used in order to assess voltage profiles near to real-time with a minimal number of sensors. However, applying classical DSE to distribution networks leads to ill conditioned problems and long computation times due to the size and the characteristics of these networks. Therefore, this article presents a method which helps overcome these issues. It is based on a scalable zonal approach which leads to accurate state estimation results while decreasing computation times.
  • Keywords
    distribution networks; power system management; state estimation; DMS; DSE; distribution management systems; distribution network; scalable distribution state estimation approach; Accuracy; Automation; Program processors; Real time systems; Sensors; State estimation; DMS; Distribution State Estimation; Scalability; parallel computing; sensors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Innovative Smart Grid Technologies (ISGT Europe), 2011 2nd IEEE PES International Conference and Exhibition on
  • Conference_Location
    Manchester
  • ISSN
    2165-4816
  • Print_ISBN
    978-1-4577-1422-1
  • Electronic_ISBN
    2165-4816
  • Type

    conf

  • DOI
    10.1109/ISGTEurope.2011.6162617
  • Filename
    6162617