In order to fully tap the adjustment ability of electric vehicles and improve the accuracy of user control, a user adjustability evaluation method for electric vehicles with multiple control needs was proposed. Firstly, considering the multiple regulation and control needs of the power grid and the characteristics of user behavior, the user adjustability evaluation index system of electric vehicles was constructed from the perspectives of guidance difficulty and guidance effect. Secondly, a two-stage evaluation model of adjustability was established, the improved inter-layer correlation weighting method was used to determine the objective weight of the index, and the improved fuzzy C-means algorithm was used to guide the difficulty clustering of users, so as to realize the initial selection of potential users. Then, in view of the problem of market demand difference, the fuzzy analytic hierarchy process was used to calculate the subjective weight of the index, the optimal combination weight was obtained based on the Nash equilibrium, and the improved advantage and disadvantage solution distance method is used to quantitatively rank the user guidance effect, so as to realize the comprehensive evaluation of user adjustability. Finally, a case study was conducted using data related to electric vehicle users on the state grid smart connected vehicle platform. The results showe that the proposed method is applicable and reliable, which can help achieve precise guidance of electric vehicle loads and provide reference for multi type market regulation.