Algorithm Based fault tolerant state estimation of power systems

Electric power industry deregulation has transformed state estimation from an important application into a critical one. State estimations in power systems involve very tedious computations since large systems can consist of thousands of buses and lines. In this paper, we apply algorithm based fault tolerance techniques to the Gauss-Newton iterative algorithm that solves a weighted least-squares (WLS) state estimator of a power system. These techniques efficiently detect computational errors due to transient and permanent faults in the hardware. We show that the modified state estimation algorithm has low computational over-head and is free from false alarms