WAMS/SCADA Hybrid System State Estimation Algorithm with Double Constraints

The precision of traditional power system state estimation (SE) based on supervisory control and data acquisition system (SCADA) is low. This paper aims to construct a SE objective function combined with the constraints of zero-injection nodes and wide area measurement system (WAMS) in order to improve the precision of SE, in the WAMS/SCADA hybrid system. The optimal estimation can be derived from the SE objective function with double constraints by the optimization theory of Lagrange multipliers method. A standard test system has been used to prove the efficiency and the real-time performance of the proposed method, the precision is improved and the real-time performance is similar in the certain scope comparing with the traditional SE method.