Robust Approach for Identification of Bad Data in State Estimation Using SLP Technique

Thukaram Dhadbanjan 1 , H. P. Khincha 2  and M. S.S. Phaniram 3
  • 1 Indian Institute of Science, Bangalore
  • 2 Indian Institute of Science, Bangalore
  • 3 Indian Institute of Science, Bangalore

This paper proposes a new approach for solving the state estimation problem. The approach is aimed at producing a robust estimator that rejects bad data, even if they are associated with leverage-point measurements. This is achieved by solving a sequence of Linear Programming (LP) problems. Optimization is carried via a new algorithm which is a combination of ``upper bound optimization technique" and ``an improved algorithm for discrete linear approximation". In this formulation of the LP problem, in addition to the constraints corresponding to the measurement set, constraints corresponding to bounds of state variables are also involved, which enables the LP problem more efficient in rejecting bad data, even if they are associated with leverage-point measurements. Results of the proposed estimator on IEEE 39-bus system and a 24-bus EHV equivalent system of the southern Indian grid are presented for illustrative purpose.

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IJEEPS publishes significant research and scholarship related to latest and up-and-coming developments in power systems. The mandate of the journal is to assemble high quality papers from the recent research and development efforts in new technologies and techniques for generation, transmission, distribution and utilization of electric power.

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