Dynamic State Estimation Based Control Strategy for DFIG Wind Turbine Connected to Complex Power Systems

This paper proposes a viable solution to the long-lasting issue of using flux-involved control scheme to regulate the behavior of doubly fed induction generator (DFIG) during faults. Instead of trying to design a complicated method to measure flux, which cannot be directly measured with contemporary technology, the solution utilizes unscented Kalman filter-based dynamic state estimation of DFIG connected to a complex power system to estimate the wanted variables. The decentralized estimation scheme takes into consideration the overall power system network and uses only local noisy PMU measurement data. DFIG control schemes are also investigated to a fair extent where three control methods are discussed with comparison results presented. The improved control scheme displays a better fault recovery response and system compatibility. A number of considerations are taken into account in the design of DFIG control schemes, including reactive power supports and dc-link current compensation.