Wind Energy Resource Assessment Technology for Multi-Type Complex Terrains Based on CNN

Against the backdrop of global low-carbon energy transition, high-precision wind resource assessment is crucial for achieving the “dual carbon” goals. To address the limitations of traditional methods in complex terrains and nonlinear wind field modeling, this paper proposes a CNN-based assessment approach. By analyzing the impact of roughness, terrain, and obstacles on wind speed, key input parameters are identified. A CNN model is then constructed to extract spatial features, enabling efficient and accurate wind resource evaluation. Case studies validate the model's prediction accuracy in complex terrains, offering a new solution for wind farm micro-siting and dynamic resource assessment.