Wind-farm power prediction using a turbulence-optimized Gaussian wake model

• Published in: Wind Energy and Engineering Research 2024-12, Vol.2, p.100007, Article 100007
• Main Authors: Zehtabiyan-Rezaie, Navid, Justsen, Josephine Perto, Abkar, Mahdi
• Format: Article
• Language: English
• Subjects: Farm-to-farm interactions; Gaussian wake model; Power prediction; Wake-added turbulence; Wind-farm wakes
• ISSN: 2950-3604; 2950-3604
• DOI: 10.1016/j.weer.2024.100007

In this study, we present an improved formulation for the wake-added turbulence to enhance the accuracy of intra-farm and farm-to-farm wake modeling through analytical frameworks. Our goal is to address the tendency of a commonly used formulation to overestimate turbulence intensity within wind farms and to overcome its limitations in predicting the streamwise evolution of turbulence intensity beyond them. To this end, we utilize high-fidelity data and adopt an optimization technique to derive a refined functional form of the wake-added turbulence. We then integrate the achieved formulation with a widely used Gaussian wake model to study various intra-farm and farm-to-farm scenarios. The outcomes reveal that the new methodology effectively addresses the overestimation of power in both standalone wind farms and those impacted by upstream counterparts. Our new approach meets the need for accurate and lightweight models, ensuring the effective coexistence of wind farms within clusters as the wind-energy capacity rapidly expands. •An improved formulation for the wake-added turbulence is presented.•The new formulation is integrated into a widely-used Gaussian wake model.•Diverse intra-farm and farm-to-farm scenarios are analyzed.•Enhanced power prediction for both isolated and downstream-influenced wind farms is achieved.