Power System Dynamic State Estimation With Synchronized Phasor Measurements

The dynamic state estimation (DSE) applied to power systems with synchrophasor measurements would estimate the system's true state based on measurements and predictions. In this application, as phasor measurement units (PMUs) are not deployed at all power system buses, state predictions would enhance the redundancy of DSE input data. The significance of predicted and measured data in DSE is affected by their confidence levels, which are inversely proportional to the corresponding variances. In practice, power system states may undergo drastic changes during hourly load fluctuations, component outages, or network switchings. In such conditions, the inclusion of predicted values could degrade the power system state estimation. This paper presents a mixed-integer programming formulation of DSE that is capable of simultaneously discarding predicted values whenever sudden changes in the system state are detected. This feature enhances the DSE computation and will not require iterative executions. The proposed model accommodates system-wide synchronized measurements of PMUs, which could be of interest to smart grid applications in energy management systems. The voltage phasors at buses without PMUs are calculated via voltage and current measurements of adjacent buses, which are referred to as indirect measurements. The guide to the expression of uncertainty in measurement is used for computing the confidence level of indirect measurements based on uncertainties associated with PMU measurements as well as with transmission line parameters. Simulation studies are conducted on an illustrative three-bus example and the IEEE 57-bus power system, and the performance of the proposed model is thoroughly discussed.