• DocumentCode
    30344
  • Title

    Optimization of State-Estimator-Based Operation Framework Including Measurement Placement for Medium Voltage Distribution Grid

  • Author

    Yu Xiang ; Ribeiro, P.F. ; Cobben, J.F.G.

  • Author_Institution
    Electr. Energy Syst. Group, Eindhoven Univ. of Technol., Eindhoven, Netherlands
  • Volume
    5
  • Issue
    6
  • fYear
    2014
  • fDate
    Nov. 2014
  • Firstpage
    2929
  • Lastpage
    2937
  • Abstract
    To provide a guideline for grid operators to manage medium voltage distribution grids, this paper presents a probabilistic approach for measurement placement optimization and a state-estimator-based operation framework. The Monte Carlo method is used to optimize the measurement placement with minimum measured points, which support the observability of state estimator and satisfy the requirements for operation activities. The proposed framework covers several important factors from practical situations, including cost allocation of measurement systems, unavailability of measurement data, and small voltage deviation across medium voltage (MV) grids. Finally, a case study on a typical European distribution grid demonstrates the feasibility of the framework.
  • Keywords
    Monte Carlo methods; distributed power generation; optimisation; power distribution economics; power grids; power system management; power system measurement; power system state estimation; European distribution grid; Monte Carlo method; cost allocation; measurement placement optimization; medium voltage distribution grid management; observability; probabilistic approach; state estimator-based operation framework optimization; Current measurement; Measurement units; Monte Carlo methods; Optimization; Reactive power; State estimation; Voltage measurement; Central limit theorem; Monte Carlo methods; distribution management system (DMS); load estimation; measurement placement; state estimation; state estimation.;
  • fLanguage
    English
  • Journal_Title
    Smart Grid, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1949-3053
  • Type

    jour

  • DOI
    10.1109/TSG.2014.2343672
  • Filename
    6879284