• DocumentCode
    3683304
  • Title

    Probabilistic tools for DMS

  • Author

    O. Vlachokyriakou;K. Mavrogenou;D. Trakas;D. Koukoula;G. Sideratos;A. Dimieas;N. Hatziargyroui;M. Kouveletsou;E. Leonidaki;K. Andreadis

  • Author_Institution
    National Teclinical University, NTUA, Athens, Greece
  • fYear
    2015
  • Firstpage
    189
  • Lastpage
    194
  • Abstract
    The paper presents a set of probabilistic functions based on stochastic RES (PV and Wind) forecasting and probabilistic load flow, which use the AMR (Automatic Meter Reading) infrastructure for data acquisition at MY Networks and the SCADA measurements at the MA" bus. More specifically, probabilistic functions are implemented, in order to provide improved monitoring of the system state, identification in advance and management of operational limits notations (e.g. over voltages), etc. Moreover, probabilistic tools are used for RES Hosting Capacity Evaluation and the Assessment of the impact of Y/Q control strategies of Distributed Energy Resources (DER). Results from the application and evaluation of the probabilistic functions in actual, rural MY feeders with high PY penetration are presented and evaluated.
  • Keywords
    "Voltage measurement","Probabilistic logic","Load flow","Voltage control","Load modeling","Predictive models","Forecasting"
  • Publisher
    ieee
  • Conference_Titel
    Smart Electric Distribution Systems and Technologies (EDST), 2015 International Symposium on
  • Type

    conf

  • DOI
    10.1109/SEDST.2015.7315205
  • Filename
    7315205