Fractional-Order Control of a Wind Turbine Using Manta Ray Foraging Optimization

In this research paper, an improved strategy to enhance the performance of the DC-link voltage loop regulation in a Doubly Fed Induction Generator (DFIG) based wind energy system has been proposed. The proposed strategy used the robust Fractional-Order (FO) Proportional-Integral (PI) control technique. The FOPI control contains a non-integer order which is preferred over the integer-order control owing to its benefits. It offers extra flexibility in design and demonstrates superior outcomes such as high robustness and effectiveness. The optimal gains of the FOPI controller have been determined using a recent Manta Ray Foraging Optimization (MRFO) algorithm. During the optimization process, the FOPI controller's parameters are assigned to be the decision variables whereas the objective function is the error racking that to be minimized. To prove the superiority of the MRFO algorithm, an empirical comparison study with the homologous particle swarm optimization and genetic algorithm is achieved. The obtained results proved the superiority of the introduced strategy in tracking and control performances against various conditions such as voltage dips and wind speed variation.

Automated summary

The research introduced an improved strategy using Fractional-Order Proportional-Integral control technique for enhancing the performance of a Doubly Fed Induction Generator wind energy system. The optimal gains of the FOPI controller were determined using a Manta Ray Foraging Optimization algorithm, showcasing superior tracking and control performances under various conditions.