Low Voltage Risk Assessment in Power System Using Neural Network Ensemble

  • Wei-Hua Chen
  • Quan-Yuan Jiang
  • Yi-Jia Cao
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3972)


Static voltage security is one of the important items of power system security. This paper provides an approach to calculate risk of low voltage in power system using neural network ensemble. Risk is defined as a condition under which there is a possibility of an adverse deviation from a desired outcome that is expected or hoped for. Risk index is used as an indicator of the low voltage security. It is calculated as the product of the probability of contingency and the impact of low voltage. Neural network ensemble (NNE) is used for the low voltage risk assessment to get the desired speed, accuracy and efficiency. The New England 39-bus test system is used as an example to demonstrate the efficiency of the proposed algorithm.


Power System Risk Index Line Outage Voltage Magnitude Neural Network Ensemble 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Wei-Hua Chen
    • 1
  • Quan-Yuan Jiang
    • 1
  • Yi-Jia Cao
    • 1
  1. 1.College of Electrical EngineeringZhejiang UniversityHangzhouChina

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