Atmospheric stability, which has received widespread attention in recent years, has a significant impact on the performance of wind farms. However, majority of traditional wind farm layout optimization (WFLO) studies assume that atmospheric stability is always neutral. Hence, to consider the influence of atmospheric stability, we developed a novel WFLO framework based on an improved Gaussian wake model. In this framework, local atmospheric stability was used as an important input parameter, and the calculation method of wind power generation was modified accordingly. The proposed method was applied to three ideal wind farms and one real wind farm (Horns Rev 1 wind farm) for layout optimization. The results illustrated that atmospheric stability had a critical influence on WFLO results. As the atmosphere became more stable, the number of wind turbines with low power generation levels in the optimized layout increased gradually, resulting in a decline in the overall power generation. Moreover, the layout optimized under traditional neutral assumption was not suitable for the actual atmospheric environment. However, correct consideration of local atmospheric stability distribution in WFLO will result in a layout with a higher power output. In the real-world scenario, the developed WFLO framework can comprehensively consider local wind resource conditions to obtain a more efficient and reliable optimized layout scheme.

近年来，大气稳定性受到了广泛的关注，对风电场的性能产生了重大影响。但是，大多数传统的风电场布局优化（WFLO）研究都假定大气稳定性始终是中性的。因此，考虑到大气稳定性的影响，我们基于改进的高斯尾流模型开发了一种新颖的WFLO框架。在此框架下，当地的大气稳定性被用作重要的输入参数，并相应地修改了风力发电的计算方法。所提出的方法被应用于三个理想的风场和一个真实的风场（Horns Rev 1风场）以进行布局优化。结果表明，大气稳定性对WFLO结果具有关键影响。随着气氛变得更加稳定，优化布局中的低发电量风力涡轮机数量逐渐增加，导致总发电量下降。而且，在传统的中性假设下优化的布局不适合实际的大气环境。但是，正确考虑WFLO中的局部大气稳定性分布将导致布局具有更高的功率输出。在现实世界中，开发的WFLO框架可以综合考虑当地的风资源条件，以获得更有效，更可靠的优化布局方案。在传统的中性假设下优化的布局不适合实际的大气环境。但是，正确考虑WFLO中的局部大气稳定性分布将导致布局具有更高的功率输出。在现实世界中，开发的WFLO框架可以综合考虑当地的风能条件，以获得更有效，更可靠的优化布局方案。在传统的中性假设下优化的布局不适合实际的大气环境。但是，正确考虑WFLO中的局部大气稳定性分布将导致布局具有更高的功率输出。在现实世界中，开发的WFLO框架可以综合考虑当地的风能条件，以获得更有效，更可靠的优化布局方案。