A method for determining pseudo-measurement state values for topology observability of state estimation in power systems

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This paper proposes a new technique for determining state values in power systems. Recently, it has been useful for carrying out state estimation with PMU (Phasor Measurement Unit) data. The authors have developed a method for determining state values with an artificial neural network (ANN) considering topology observability in power systems. The ANN has the advantage of approximating nonlinear functions with high precision. The method evaluates pseudo-measurement state values of data which are lost in power systems. The method has been successfully applied to the IEEE 14-bus system.

Original languageEnglish
Pages (from-to)27-34
Number of pages8
JournalElectrical Engineering in Japan (English translation of Denki Gakkai Ronbunshi)
Issue number2
Publication statusPublished - 30 Apr 2012



  • PMU (phasor measurement unit)
  • artificial neural network (ANN)
  • minimum spanning tree
  • pseudo-measurement state values
  • state estimation
  • topology observability

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