State estimation of flexible AC transmission systems considering synchronized phasor measurements

•A formulation to estimate the state of a power system containing FACTS devices through measurements provided by a SCADA system and PMUs is proposed.•Equations relating PMU measurements and FACTS controllers’ state variables are derived from first principles.•The values of the state variables of FACTS devices and electric network are simultaneously upgraded for a unified estimation of the system state.•The effect of the different numbers and locations of PMUs on the accuracy of the state estimation is illustrated by numerical examples.

This paper proposes a practical approach to incorporate synchronized phasor measurements into a weighted least squares state estimation algorithm suitable for electric networks containing flexible AC transmission systems (FACTS) controllers. Equations relating the branch current phasors to FACTS controllers’ state variables are derived from first principles in order to directly append synchronized phasor measurements of currents and voltages to the set of measurement data collected from the supervisory control and data acquisition system to estimate the equilibrium point of the electric power system. The phase angle measured by a perfect phasor measurement unit at one of the buses is selected as the global reference for the estimation, such that the voltage phasor measurements provided as data to the estimator correspond to the angle differences between all remaining voltage phasor measurements and the reference angle. Furthermore, the synchronized current phasor measurements are transformed to rectangular coordinates to enhance the convergence properties of the proposed state estimation approach. In both cases, the variance of the new set of synchronized measurements is calculated based on the uncertainty propagation theory. The proposed approach simultaneously upgrades the estimated values of the state variables of FACTS devices and the electric network for a unified estimation of the system state. Lastly, numerical simulations with two real-life electric power networks are reported to demonstrate the prowess of the proposed approach.