Design of a Pitch Controller for a Wind Turbine Using Hybrid Mean-Variance Mapping Optimization
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Abstract
A variable-speed wind energy conversion system (WECS) has the advantage of extracting more power from the time-varying wind. To achieve this, the pitch angle is controlled to maintain the speed of the turbine and hence the generated power at a constant level, while reducing mechanical stress on the turbines. In this work, a proportional-integral (PI) controller is used for pitch angle control. The optimal PI control gains and
are tuned by the hybrid mean-variance mapping optimization (MVMO-SH) technique, particle swarm optimization (PSO), and a genetic algorithm (GA). Different fitness evaluation criteria and optimization techniques are compared, and the performances of optimal controllers presented in the time domain. The results reveal that MVMO-SH achieves the minimum error criteria within a shorter time. The optimal controller design gives an error of less than
in the region for which it is tuned. The performance of the optimal PI controller designed for one operating condition is tested in different cases of wind gust, random variation of wind, and disturbance from the grid side to mitigate line to ground fault. The performance of the controller is shown to be satisfactory in all the cases studied.
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