• DocumentCode
    648253
  • Title

    State estimation for smart distribution substations

  • Author

    Gomez-Quiles, Catalina ; Gomez-Exposito, Antonio ; de la Villa Jaen, Antonio

  • fYear
    2013
  • fDate
    21-25 July 2013
  • Firstpage
    1
  • Lastpage
    1
  • Abstract
    Summary form only given. In the upcoming smart grid environment many more measurements will be available, which can be locally processed by the so-called substation state estimator (SSE). Distribution substations serve energy to a large set of feeders, each one delivering power to a certain number of secondary transformers. In this context, the SSE may have to deal with a huge network model, comprising several hundred or even thousand buses. Taking advantage of the weak electrical coupling existing among the set of feeders connected to the same or adjacent substations, a two-stage procedure is proposed in this paper to efficiently solve the SSE. In the first stage the overall SE is decomposed into f + s WLS subproblems (f and s being the total number of feeders and substations, respectively), which are then solved in a decoupled manner. The second stage, involving a linear WLS problem, consists of coordinating the solution provided by each subsystem (feeder or substation). The proposed solution scheme has a number of advantages, as shown by the case studies.
  • Keywords
    power distribution; power system simulation; smart power grids; transformer substations; SSE; adjacent substations; electrical coupling; feeder set; feeder-substation WLS subproblem; linear WLS problem; network model; secondary transformers; smart distribution substations; smart grid environment; state estimation; substation state estimator; Context; Context modeling; Couplings; Smart grids; State estimation; Substations;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power and Energy Society General Meeting (PES), 2013 IEEE
  • Conference_Location
    Vancouver, BC
  • ISSN
    1944-9925
  • Type

    conf

  • DOI
    10.1109/PESMG.2013.6672825
  • Filename
    6672825