Title :
Identification of multiple interacting bad data via power system decomposition
Author :
Cheniae, M.G. ; Mili, L. ; Rousseeuw, J.
Author_Institution :
Bradley Dept. of Electr. Eng., Virginia Polytech. Inst. & State Univ., Blacksburg, VA, USA
fDate :
8/1/1996 12:00:00 AM
Abstract :
This paper presents a new, highly robust bad data identification algorithm for electric power system state estimation. A system decomposition scheme is coupled with the least median of squares estimator to allow identification of multiple interacting bad data even in cases of conforming errors. The algorithm is inherently resistant to bad measurements in positions of leverage, makes no a priori measurement error probability distribution assumptions, and is applicable in a real-time environment
Keywords :
least mean squares methods; numerical stability; power system analysis computing; power system state estimation; real-time systems; IEEE 14-bus test system; computer simulation; conforming errors; least median of squares estimator; multiple interacting bad data; power system state estimation; real-time environment; robust bad data identification algorithm; system decomposition scheme; Fluid flow measurement; Laplace equations; Least squares approximation; Measurement errors; Position measurement; Power system measurements; Power system reliability; Power systems; Robustness; State estimation;
Journal_Title :
Power Systems, IEEE Transactions on
