Self-filtering based on the fault ride-through technique using a robust model predictive control for wind turbine rotor current

• Published in: Scientific reports 2024-01, Vol.14 (1), p.1905-46, Article 1905
• Main Authors: Achar, Abdelkader, Djeriri, Youcef, Benbouhenni, Habib, Colak, Ilhami, Oproescu, Mihai, Bizon, Nicu
• Format: Article
• Language: English
• Subjects: 639/166; 639/4077; Algorithms; Alternative energy sources; Electricity; Energy resources; Environmental impact; Humanities and Social Sciences; multidisciplinary; R&D; Research & development; Science; Science (multidisciplinary); Turbines; Wind farms; Wind power
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-023-51110-3

This paper studies the possibility of connecting Wind Farms (WF) to the electric grid with the use of finite space model predictive command (FS-MPC) to manage wind farms to improve the quality of the current output from the doubly-fed induction generator (DFIG) with considering fault ride-through technique. This proposed system can generate active power and enhance the power factor. Furthermore, the reduction of harmonics resulting from the connection of non-linear loads to the electrical grid is achieved through the self-active filtering mechanism in DFIGs-WF, facilitated by the now algorithm proposed. FS-MPC technique has the ability to improve system characteristics and greatly reduce active power ripples. Therefore, MATLAB software is used to implement and verify the safety, performance, and effectiveness of this designed technique compared to the conventional strategy. The results obtained demonstrated the effectiveness of the proposed algorithm in handling the four operational modes (Maximum power point tracking, Delta, Fault, and Filtering). Additionally, the suggested technique exhibited flexibility, robustness, high accuracy, and fast dynamic response when compared to conventional strategies and some recently published scientific works. On the other hand, the THD value of the current was significantly reduced, obtaining at one test time the values 56.87% and 0.32% before and after filtering, respectively 27.50% and 0.26% at another time of testing, resulting in an estimated THD reduction percentage of 99.43% and 99.05%, respectively. These high percentages prove that the quality of the stream is excellent after applying the proposed strategy.