A comparative study on wide-area damping controllers using multiple DFIG-based wind farms under intermittent observations

In this paper specific attention is focused on wide-area oscillation damping control of a power grid with substantial penetration of large-scale inverter-interfaced wind energy resources using remote feedback signals. These signals sent through communication channels encounter data dropout, which is represented by the Gilbert-Elliott model. Performance of three different control techniques are compared: Conventional Feedback Control (CFC), an Observer-driven Reduced Copy (ORC) approach, and Modified Kalman Filtering (MKF). ORC uses the knowledge of the nominal system dynamics during data dropouts to improve the damping performance whereas MKF adapts the updation step according to data drop. An expression for the expectation of the bound on the error norm between the actual and the estimated states relating uncertainties in the cyber system due to data dropout and physical system due to change in operating conditions is also derived for ORC. Nonlinear time-domain simulations are carried out to compare the performance of CFC, MKF, and ORC under higher data drop scenarios.