Advances and Challenges in Analytical Wake Modelling for Offshore Wind Farm Layout Optimization

Wakes generated by upstream turbines in an offshore wind farm severely reduce the efficiency and power output of downstream turbines. Wind farm layout optimization offers a way to alleviate these negative impacts, where the main challenge lies in accurate and efficient evaluation across a vast number of potential configurations. Analytical wake models are crucial tools for this optimization, owing to their superb ability to efficiently predict wake distributions. This paper evaluates and discusses recent advances and persistent challenges in analytical wake modelling for layout optimization of wind farms. While the Jensen model remains efficient for discrete searches, the models capturing radial velocity gradients have become a preferred choice for high-fidelity optimization designs. Advanced models show the transition to full wakes to cover near-wake characteristics and complex inflow conditions. Motion corrections and physically based superposition methods improve the performance evaluation of floating offshore wind farms. Multi-objective optimization frameworks balance energy production and fatigue life by the integration of turbulence modelling. However, the increasing scale of modern wind turbines, the dynamic complexity of floating offshore wind farms, the clustering, and the model validation of large-scale wind farms present significant challenges to the applicability of these models. This paper highlights these emerging limitations in optimization problems, clarifying that addressing the gaps in these specific areas is essential for the development of high-fidelity optimizations and the design of future large-scale offshore wind turbine clusters.