1.Shaanxi Key Laboratory of Smart Grid (Xi’an Jiaotong University), Xi’an 710049, China;2.School of Electrical Engineering, Xi’an Jiaotong University, Xi’an 710049, China;3.State Grid Sichuan Electric Power Company, Chengdu 610000, China
Low voltage ride-through (LVRT) requires wind power generation systems to remain continuous operation during the sudden grid voltage sag and provide reactive power support for power grid. To enhance the LVRT capability of wind power generation systems using doubly-fed induction generators (DFIGs), this paper proposes a disturbance attenuation control (DAC) method based on state-dependent Riccati equation (SDRE) technique. The DAC objectives are as follows: the rotor side converter should provide required reactive power support for power grid during the transient period; the grid side converter should keep the DC-link voltage constant. Based on the above control objectives, the corresponding DAC problems are constructed, and the feedback control laws are obtained by using SDRE technique. The influence of control objectives, control effect and control cost are fully considered in the design of weighing matrices. To ensure the rotor current and DC-link voltage are within the safe range in the LVRT process, a rotor current limiting mechanism is proposed and a protection circuit using series dynamic resistor is adopted. Compared with the simulation results of the conventional proportional-integral (PI) control, the PI control based on particle swarm optimization (PSO), the sliding-mode control, and the exact linearization control, the proposed control strategy has better transient performance and can effectively improve the LVRT capability of wind power generation systems using DFIGs.
This work is supported by National Natural Science Foundation of China (No. 51707147) and Shaanxi Provincial Key R&D Program of China (No. 2017ZDCXL-GY-02-03).
|||ZHANG Ruowei, QIN Boyu, LI Hengyi, et al. Low Voltage Ride-through Control Strategy for DFIG-based Wind Turbine Based on Disturbance Attenuation[J]. Automation of Electric Power Systems,2020,44(20):112-120. DOI:10.7500/AEPS20200229002|