In order to solve the problems of the inability to comprehensively consider the impact of equipment aging and operation environment on the performance of wind turbine system and their components, the severe imbalance in comprehensive weighting, and the lack of effective method to identify the operational states of wind turbine and its components, a wind turbine comprehensive operation state evaluation and sensitivity analysis based on optimal weighting and improved cloud model was proposed. Firstly, comprehensive state evaluation indicator system for wind turbine with multi-level and multi-performance index was created. Secondly, based on the maximization of deviation and the maximum entropy criterion, a multi-objective and multi-attribute optimal weighting model for wind turbine was established. Next, a comprehensive operation state evaluation model for wind turbine was established based on the optimal weighting model and the improved cloud model. And wind turbine and its components operation states of the wind turbine was identified and determined based on the improved ideal curve method. Finally, the effectiveness of the proposed model was verified by taking a wind turbine in wind farm as the research object, and sensitivity analysis was conducted on the wind turbine and its components. The results show that this method not only effectively solves the problem of the severe imbalance in comprehensive weighting and identifies the operational states of wind turbine and its components, but also reveals the impact of changes in operation states indicators on wind turbine system and its components. And it provides theoretical support for the high reliability and stable operation of wind turbine.