Szczegóły publikacji
Opis bibliograficzny
Advanced direct power control strategies for grid-connected DFIG-based wind energy conversion systems: a comprehensive state-of-the-art review / Naima Salym, Btissam Majout, Badre Bossoufi, Mohammed El Ghzaoui, Rachid El Alami, Paweł SKRUCH, Saleh Mobayen // Computers and Electrical Engineering ; ISSN 0045-7906 . — 2026 — vol. 135 art. no. 111178, s. 1–24. — Bibliogr. s. 21–24, Abstr. — Publikacja dostępna online od: 2026-04-20
Autorzy (7)
- Salym Naima
- Majout Btissam
- Bossoufi Badre
- El Ghzaoui Mohammed
- El Alami Rachid
- AGHSkruch Paweł
- Mobayen Saleh
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 167516 |
|---|---|
| Data dodania do BaDAP | 2026-05-25 |
| Tekst źródłowy | URL |
| DOI | 10.1016/j.compeleceng.2026.111178 |
| Rok publikacji | 2026 |
| Typ publikacji | przegląd |
| Otwarty dostęp |  |
| Czasopismo/seria | Computers & Electrical Engineering |
Abstract
Given the increasing emphasis on the integration of advanced control platforms to enhance the performance of wind energy conversion systems, Direct Power Control (DPC) has emerged as one of the most widely adopted strategies. In particular, DPC has demonstrated remarkable effectiveness for grid-connected wind energy conversion systems based on Doubly-Fed Induction Generators (DFIGs), offering significant advantages in terms of dynamic response, implementation simplicity, and reduced reliance on system parameters. This technique does not require synchronous coordinate transformations, has no current control loops, depends less on system parameters, and is relatively easy to implement. However, classical DPC presents some drawbacks, such as ripples in currents, active and reactive power, and the inability to maintain a constant switching frequency, which may directly affect system performance and compromise stability. Various control strategies have been proposed to improve DPC techniques and overcome these limitations. This review provides a detailed description of the DPC algorithm and the proposed advancements, including DPC with Space Vector Modulation (DPC-SVM), Fuzzy Logic-based DPC (DPC-FL), Sliding Mode Control (DPC-SMC), and Predictive DPC (MPC-DPC). It also highlights the integration of Artificial Intelligence, showcasing DPC advancements based on Neural Networks (DPC-ANN), Genetic Algorithms (DPC-GA), Ant Colony Optimization (DPC-ACO), and Rooted Tree Optimization (DPC-RTO). A comparative analysis of these applications is also presented in this paper, identifying the strengths and weaknesses of these techniques and guiding the selection of the most suitable method for WECS-DFIG applications. Furthermore, the review examines the various experimental boards and platforms used to implement these control strategies, offering valuable insights into their practical applications.