An Adaptive Fuzzy Logic Control Strategy for Performance Enhancement of a Grid-Connected PMSG-Based Wind Turbine

Wind power installations are rapidly increasing worldwide, leading to a huge level of permeation into electricity supply networks. Enormous efforts are spent to improve the performance of the wind turbine generator systems. This paper proposes a novel adaptive fuzzy logic control strategy for performance improvement of a grid-tied wind generator system. The variable-speed wind turbine driven permanent-magnet synchronous generator is tied to the electricity network by a full-capacity power converter. A cascaded adaptive fuzzy logic control strategy is proposed as the control methodology for the generator- and the grid-side converter/inverter. The adaptive technique depends on a continuous mixed p-norm algorithm, which on-line updates the scaling factors of the fuzzy logic controllers (FLCs) at a high convergence speed. For the sake of preciseness, real wind speed data measured in the Za-afarana wind farm, Egypt, are considered in the analyses. The effectiveness of the proposed adaptive FLC is compared to that achieved using particle swarm optimization algorithm based an optimal proportional-integral controller, considering severe grid disturbances. Extensive simulation analyses, which are done using MATLAB/Simulink software, are presented to validate the efficiency of the adaptive fuzzy logic control strategy.