Phase: |
Theme |
Theme: | Wind (T14) |
Status: | Active |
Start Date: | 2025-01-01 |
End Date: | 2026-06-30 |
Principal Investigator |
Mohamed, Yasser |
Highly Qualified Personnel
Project Overview
This project targets the development of advanced data-driven artificial intelligence (AI)-enabled impedance modeling and stability analysis tools for wind farms. The proposed data-driven AI-enabled approach can effectively capture the nonlinear dynamics of complex wind farms, even with limited knowledge of the control system parameters. Furthermore, it accounts for modern wind farms' inherent uncertainties and structural complexity. Hence, it facilitates accurate assessment and prediction of potential instabilities and control system oscillations across a broad range of typical operating conditions. The proposed approach can potentially establish the foundations for entirely new tools for dynamic analysis and control of complex renewable energy resources systems via advanced AI and machine learning methods.