Synchrophasor-based real-time state estimation and situational awareness system for power system operation

State estimation is a critical functionality of energy management system (EMS) to provide power system states in real-time operations. However, problems such as failure to converge, prone to failure during contingencies, and biased estimates while system is under stressed condition occur so that state estimation results may not be reliable. The unreliable results further impact downstream network and market applications, such as contingency analysis, voltage stability analysis, transient stability analysis, system alarming, and unit commitment. Thus, operators may lose the awareness of system condition in EMS. This paper proposes a fully independent and one-of-a-kind system by integrating linear state estimator into situational awareness applications based on real-time synchrophasor data. With guaranteed and accurate state estimation solution and advanced real-time data analytic and monitoring functionalities, the system is capable of assisting operators to assess and diagnose current system conditions for proactive and necessary corrective actions. The architecture, building components, and implementation of the proposed system are explored in detail. Two case studies with simulated data from the subsystems of Electric Reliability Council of Texas (ERCOT) and Los Angeles Department of Water and Power (LADWP) are presented. The test results show the effectiveness and reliability of the system, and its value for realtime power system operations.