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Turkish Journal of Electrical Engineering and Computer Sciences

Author ORCID Identifier

ANIS FEDDAOUI: 0009-0005-7679-6855

LOTFI FARAH: 0000-0002-5101-9698

ABDELOUAHAB BENRETEM: 0009-0001-3155-7923

MOHAMMED ABDELDJALIL DJEHAF: 0000-0002-4482-6918

Abstract

This study proposes a novel power management strategy for wind farms using a grey wolf optimization (GWO)-based PI controller. The method aims to enhance active and reactive power control in systems employing dou bly fed induction generators. Three control strategies are evaluated—namely, a classical frequency-domain PI controller, an Artificial Neural Network (ANN)-based controller, and the proposed GWO-based PI controller—the last of which represents the main contribution. The classical PI and ANN controllers are included strictly for comparative bench marking. MATLAB simulations demonstrate that the GWO-beased PI controller offers superior dynamic performance, particularly in settling time and overshoot reduction. A power management algorithm is also developed to coordinate turbine outputs under varying wind conditions to meet a global production target. Results confirm the effectiveness of the proposed approach in enhancing wind farm stability, responsiveness, and energy efficiency.

DOI

10.55730/1300-0632.4156

Keywords

Wind farm, doubly fed induction generator, power management, power control, GWO, ANN

First Page

758

Last Page

782

Publisher

The Scientific and Technological Research Council of Türkiye (TÜBİTAK)

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

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