The application provides a wind farm
layout and
yaw control multi-objective optimization method based on a nested collaborative optimization architecture. A three-layer nested collaborative optimization architecture is established. The outer layer iteratively searches for a wind
turbine position vector through a multi-objective optimization module to obtain a
Pareto optimal solution set between annual power generation and
land use efficiency. The middle layer annual power generation evaluation module quantitatively evaluates the power generation potential of each candidate wind
turbine layout scheme generated in the
iteration process. The inner layer
yaw optimization module is called to obtain the optimal output power of each candidate wind
turbine layout scheme under different wind conditions. The optimal output powers are weighted and summarized according to their occurrence probabilities, and the corresponding
collaborative design annual power generation is output to feedback to the outer layer multi-objective optimization module. The
yaw control optimization result is directly embedded in the wind farm layout design scheme, realizing the collaborative optimization of the wind turbine spatial layout and the
yaw control strategy, which is very beneficial to improve the power generation efficiency of the wind farm in the region with limited
land resources.