Monte Carlo method-based clustering analysis applied for robust state estimation and data debugging of power systems

Jeu M. Lin, Shyh-Jier Huang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents a robust method for power system state estimation along with a statistical technique of data debugging. In the estimation process, an exponential function is utilized to modify the variances of measurements in anticipation of enhancing the estimation performance and improving the convergence characteristics. Besides, with the aid of Monte Carlo method (MCM)-based clustering analysis, those bad data can be effectively identified from the set of raw measurements. To validate the effectiveness of the proposed approach, this method has been tested under different scenarios. Test results help confirm the feasibility of the method for the applications considered.

Original languageEnglish
Title of host publication2007 International Conference on Intelligent Systems Applications to Power Systems, ISAP
DOIs
Publication statusPublished - 2007 Dec 1

Publication series

Name2007 International Conference on Intelligent Systems Applications to Power Systems, ISAP

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Energy Engineering and Power Technology
  • Control and Systems Engineering

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