Convergence improvement and bad data detection for fast-decoupled state estimator using optimal multiplier

From power system on-line operation and security control view point, state estimation, a methodology used to obtain reliable estimate of power system state, has become one of the important issues. Among some state estimation methods, the fast-decoupled state estimator is commonly used as a prevailed method and has been implemented by many utilities. However, it has been recognized that its convergence characteristics may become deteriorated when it encounters bad system conditions. Therefore, in this paper, first of all, we present the fast-decoupled state estimator which is used in present power systems. Next, we propose a method to improve the convergence characteristics of fast-decoupled state estimator using the optimal multiplier mu, followed by a reliable technique to detect, identify and eliminate bad data. The proposed method has been tested on two types of load flow test systems and successful results have been obtained