Optimization Control of LVRT for FESRWT Based on Improved NSGA-II

Aiming at the low voltage ride through (LVRT) problem of front-end speed regulation wind turbine (FESRWT), an optimal control strategy based on improved NSGA-II is put forward to change pitch angle, guide vane opening and excitation current. In this strategy, the reverse learning mechanism is used to the initialization process, crossover and mutation probabilities are dynamically adjusted based on exponential distribution. The objective function is established with the minimum active power fluctuation and the constant generator terminal voltage as the control objectives. The improved algorithm proposed in this paper is used to optimize the three control parameters of the FESRWT: pitch angle, vane opening and exciting current. The control strategy verification analysis of a 2MW FESRWT was conducted. The simulation results show that the proposed optimal control strategy can make the FESRWT provide large reactive current during the fault period, support grid voltage and meet the technical requirements of wind power access to power system.