4.6 Article

D-decomposition-based multi-objective robust resilient control for blade pitch of wind energy conversion system

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.ijepes.2022.108781

Keywords

Wind energy conversion systems; Blade pitch control; D-decomposition; PID; Robustness and resiliency

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This paper proposes a new resilient control approach for blade pitch of wind energy conversion systems (WECS) to tackle the uncertainties caused by load variations and wind speed fluctuations. The approach uses a graphical D-decomposition strategy to identify the optimal region on the stability profile of the WECS and considers the robustness and resiliency objectives for the controller gains.
The uncertainties due to the load variations and wind speed fluctuations represent the biggest challenges to the stabilization of the wind energy conversion systems (WECS). In this regard, this paper develops a new resilient control approach for blade pitch of WECS as well as a low computational burden to tackle the uncertainty issue instead of the metaheuristics techniques. The proposed approach is formulated via a graphical D-decomposition strategy to identify the optimal region on the stability profile of the WECS that achieves the desired damping performance as well as minimum oscillation, settling time, and overshoot. Furthermore, the proposed approach takes into account a set of segment plants to achieve the robust performance and resiliency objectives simultaneously for the controller gains. The proposed approach is designed mathematically without hypothesis or probability as well as simple structure compared with metaheuristics techniques. Various performance indices are taken into account to assert the proposed approach accomplishment. Besides, the performance of the WECS based on the designed controller via D-decomposition is compared with different techniques in the literature. The results confirm that the proposed approach demonstrates better damping performance including less overshoot around 2.2329% and settling time around 9.2626 s than metaheuristics techniques. Furthermore, the robustness and resiliency of the designed controller are emphasized in the case of different test aspects including load variations and wind speed fluctuations compared with other techniques.

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