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Bad Data Analysis for Power System State Estimation

  • Conference paper
4th IFAC/IFIP International Conference on Digital Computer Applications to Process Control

Part of the book series: Lecture Notes in Economics and Mathematical Systems ((LNE,volume 94))

Summary

The state estimation problem in electric power systems consists of four basic operations: hypothesiae structure; estimate; detect, identify. This paper addresses the last two problems with respect to the bad data problem. The paper interrelates various detection and identification methods (sum of squared residuals, weighted and normalized residuals, nonquadratic criteria) and presents new results on bad data analysis (probability of detection, effect of bad data). The theoretical results are illustrated by means of a 25 bus network.

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References

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Author information

Authors and Affiliations

  1. Brown Boveri Research Center, Baden, Switzerland

    E. Handschin, J. Kohlas & A. Fiechter

  2. Electric Power Systems Engineering Laboratory, EE Dept, Mass. Institute of Technology, Boston, USA

    F. C. Schweppe

Authors
  1. E. Handschin
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  2. F. C. Schweppe
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  3. J. Kohlas
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  4. A. Fiechter
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Editor information

Editors and Affiliations

  1. Institute of Automatic Control and Industrial Electronics, Swiss Federal Institute of Technology, CH-Zürich, Physikstraße 3, Switzerland

    M. Mansour  & W. Schaufelberger  & 

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© 1974 Springer-Verlag Berlin · Heidelberg

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Handschin, E., Schweppe, F.C., Kohlas, J., Fiechter, A. (1974). Bad Data Analysis for Power System State Estimation. In: Mansour, M., Schaufelberger, W. (eds) 4th IFAC/IFIP International Conference on Digital Computer Applications to Process Control. Lecture Notes in Economics and Mathematical Systems, vol 94. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-65798-6_20

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  • DOI: https://doi.org/10.1007/978-3-642-65798-6_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-06621-7

  • Online ISBN: 978-3-642-65798-6

  • eBook Packages: Springer Book Archive

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