Response surface methodology Nondominated sorting genetic algorithm II Maximum power point tracki... more Response surface methodology Nondominated sorting genetic algorithm II Maximum power point tracking (MPPT) a b s t r a c t This paper presents a novel design procedure for the coordinated tuning of rotor side converter (RSC) and grid side converter (GSC) controllers of doubly fed induction generator (DFIG) wind turbine system. The RSC and GSC controller parameters are determined by simultaneously optimizing the controller performance indices. The performance indices considered are maximum peak overshoot (MPOS x), settling time (Tss x) of the generator speed and the maximum peak overshoot (MPOS Vdc), maximum peak undershoot (MPUS Vdc) and settling time (Tss Vdc) of DC link voltage. The coordinated controller design is carried out in two steps. First step is to arrive at the analytical expression that relates the performance indices and the controller parameters. This is achieved using response surface methodology (RSM) thereby saving significant computational time. In the second step the determination of controller parameters is posed as a constrained multiobjective optimization problem. The constrained multiobjective optimization problem is solved using NSGAII (nondominated sorting genetic algorithm II). The proposed methodology is tested on a sample system with DFIG based WECS. Simulation results demonstrate the effectiveness of the proposed methodology.
Response surface methodology Nondominated sorting genetic algorithm II Maximum power point tracki... more Response surface methodology Nondominated sorting genetic algorithm II Maximum power point tracking (MPPT) a b s t r a c t This paper presents a novel design procedure for the coordinated tuning of rotor side converter (RSC) and grid side converter (GSC) controllers of doubly fed induction generator (DFIG) wind turbine system. The RSC and GSC controller parameters are determined by simultaneously optimizing the controller performance indices. The performance indices considered are maximum peak overshoot (MPOS x), settling time (Tss x) of the generator speed and the maximum peak overshoot (MPOS Vdc), maximum peak undershoot (MPUS Vdc) and settling time (Tss Vdc) of DC link voltage. The coordinated controller design is carried out in two steps. First step is to arrive at the analytical expression that relates the performance indices and the controller parameters. This is achieved using response surface methodology (RSM) thereby saving significant computational time. In the second step the determination of controller parameters is posed as a constrained multiobjective optimization problem. The constrained multiobjective optimization problem is solved using NSGAII (nondominated sorting genetic algorithm II). The proposed methodology is tested on a sample system with DFIG based WECS. Simulation results demonstrate the effectiveness of the proposed methodology.
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Papers by Annas Qureshi