Wind farm layout optimization based on dynamic Levy sparrow search algorithm: A multi-parameter analysis with active yaw control

Wind farm layout optimization is essential for improving power generation efficiency and reducing operational costs in wind farms. This study develops a multi-turbine wake superposition model incorporating turbine yaw effects, based on a three-dimensional polynomial wake model. Dynamic weight and Levy flight strategies are employed to enhance the sparrow search algorithm (SSA) for layout optimization. The proposed wake model is validated with experimental data, and the superiority of DLSSA is confirmed through comparisons with traditional algorithms. Parameter analysis of active yaw strategy is conducted using two tandem wind turbines. Integrating DLSSA with the wake model, layout optimization considering height variation and active yawing strategies is investigated using dimensionless annual energy production (DAEP) as the objective function. Simulation data suggests that optimal total power output is attained when two wind turbines are positioned in a tandem configuration, with the upstream turbine set at a yaw angle of 15°. Incorporating height variation and active yaw control significantly enhances the total power output of wind farms. Implementing these strategies in layout optimization can increase total power output by 1.32 %–10.86 % compared to alternative layouts. Notably, joint optimization surpasses sequential optimization, resulting in a 1.70 % higher total power output.