Climate change impacts and adaptations are ongoing issues that are attracting the attention of many researchers. Insight into the wind power potential in an area and its probable variation due to climate change impacts can provide useful information for energy policymakers and strategists for sustainable development and management of the energy. In this study, spatial variation of wind power density at the turbine hub-height and its variability under future climatic scenarios are taken into consideration. An adaptive neuro-fuzzy inference system (ANFIS)-based post-processing technique was used to match the power outputs of the regional climate model (RCM) with those obtained from reference data. The near-surface wind data obtained from an RCM were used to investigate climate change impacts on the wind power resources in the Caspian Sea. After converting near-surface wind speed to turbine hub-height speed and computation of wind power density, the results were investigated to reveal mean annual power, seasonal and monthly variability for 20 year historical (1981–2000) and future (2081–2100) periods. The results revealed that climate change does not notably affect the wind climate over the study area. However, a small decrease was projected in the future simulation, revealing a slight decrease in mean annual wind power in the future compared to historical simulations. Moreover, the results demonstrated strong variation in wind power in terms of temporal and spatial distribution, with winter and summer having the highest values. The results indicate that the middle and northern parts of the Caspian Sea have the highest values of wind power. However, the results of the post-processing technique using the ANFIS model showed that the real potential of wind power in the area is lower than that projected in the RCM.

气候变化的影响和适应是持续存在的问题，吸引了许多研究人员的注意。对某个地区的风电潜力及其因气候变化影响而可能产生的变化的深入了解，可以为能源政策制定者和战略家提供有用的信息，以促进能源的可持续发展和管理。在这项研究中，考虑到了未来气候情景下轮毂高度处风能密度的空间变化及其变化性。基于自适应神经模糊推理系统（ANFIS）的后处理技术用于将区域气候模型（RCM）的功率输出与从参考数据中获得的功率输出进行匹配。从RCM获得的近地表风数据用于调查气候变化对里海风能资源的影响。在将近地表风速转换为涡轮轮毂高速并计算风能密度之后，对结果进行了调查，以揭示历史20年（1981-2000年）和未来（2081-2100年）的年均功率，季节和月度变化。期。结果表明，气候变化对研究区域的风气候没有明显影响。但是，未来的模拟预计会有小幅下降，与历史模拟相比，未来的年平均风能将略有下降。此外，结果表明风能在时间和空间分布方面存在很大的变化，其中冬季和夏季为最高值。结果表明，里海中部和北部地区的风能值最高。然而，