Influence of Turbulence Characteristics on Wind Turbine Performance

Wind energy serves as a pivotal component in global renewable energy transitions, yet its efficiency and reliability are critically challenged by turbulence—a complex phenomenon characterized by chaotic wind speed fluctuations arising from terrain roughness, thermal instability, and turbine wake interactions. This report investigates how turbulence intensity (TI) impacts both power output and mechanical wear in wind turbines, employing advanced computational models such as Computational Fluid Dynamics (CFD) and the FAST. Farm tool with Dynamic Wake Meandering (DWM) modules. Analyses reveal that turbulence reduces annual energy production (AEP) by ۵–۱۵% due to nonlinear wind-speed-to-power relationships P = ۱/۲ρA Cp U^۳ and increases fatigue loads on critical components (e.g., blades, towers) by up to ۳۰%, driven by unsteady aerodynamic forces and frequent load cycles. To mitigate these effects, optimization strategies are proposed, including turbine spacing adjustments (۱۰–۱۵ rotor diameters downstream) to minimize wake overlap, AI-driven layout optimization using genetic algorithms, and turbulence-aware fatigue load calculations. Case studies, such as the Horns Rev ۳ offshore wind farm, demonstrate that increasing downstream spacing to ۱۲D reduces wake turbulence exposure, yielding a ۷% AEP improvement and ۲۰% fatigue load reduction. Furthermore, incorporating turbulence intensity distributions into fatigue analysis reduces over-conservative design margins by ۱۰–۱۵%, enabling lighter, cost-effective components without compromising durability. This study emphasizes the urgency of integrating turbulence dynamics into wind farm design and control systems to enhance energy yield, extend operational lifetimes, and ensure economic viability in turbulent environments.

کلیدواژه ها:

Turbulence ، Wind energy ، CFD ، FAST