Impact of Uncertainty from Renewables on Dynamic State Estimation of Power Networks

The widespread installation of renewable energy resources in electrical power systems poses a new set of challenges primarily because of their variability. Their uncertain nature can highly affect electrical grid parameters which are essential for dynamic state estimation (DSE). In the current literature of power systems DSE usually a linearized or nonlinear ordinary differential equation model of power systems is used which cannot capture the uncertainties associated with the loads and renewable energy resources. These uncertainties can often only be taken into account via the nonlinear differential-algebraic (NL-DAE) model of power systems. This model explicitly captures renewables and the topological changes in the power system model. In this paper, we present an estimator for the complete NL-DAE representation of the power system which can provide robust state estimation in the presence of uncertainties from renewables, and investigate the impact of renewables on state estimation performance.