A Novel Adaptive Control Method for Performance Enhancement of Grid-Connected Variable-Speed Wind Generators

Abstract

Huge penetration of grid-tied wind generators into the existing electricity networks increased various challenges in modern power grids. Tremendous attempts are accomplished to properly enhance the behavior of the wind generation systems. This article exhibits a new self-tuned control approach for enhancing the performance of a permanent-magnet synchronous generator-based wind turbine, which is interlinked to the electricity network. The self-tuned technique relies on an improved multiband-structured subband adaptive filter (IMSAF) algorithm, which achieves less computational intricacy over the least-mean-square approach. The IMSAF algorithm-based self-tuned proportional-integral (PI) controller is employed to adjust the interface voltage source converters through a cascaded control structure. The IMSAF algorithm updates the multiple PI controllers' gains on-line without the necessity to optimize or fine-tune. To achieve realistic responses, practical wind speed data measured in Zaafarana wind farm, Egypt, are implemented in this study. The efficacy of self-tuned control approach is compared with that realized using an optimized PI control approach by the water cycle and the genetic algorithms, considering symmetrical and unsymmetrical faults, as the network disturbances. The validity of self-tuned control approach is widely confirmed by performing simulation analyses using MATLAB/Simulink software, and satisfactory responses are achieved. Notably, the IMSAF-based self-tuned control approach is realized to be an accurate means for improving the characteristic of grid-tied wind generators.