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According to the requirement of energy sustainable development strategy in Jilin province, this paper evaluates the performance of wind power coupling compressed air energy storage projects for a wind farm in Jilin from the perspective of sustainability. Firstly, a sustainable criteria system is established from economic, social and ecological dimensions, and 10 secondary criteria are given. Secondly, to fully express the hesitancy and fuzziness of experts, linguistic fuzzy hesitant sets (LFHSs) are used to describe the subjective evaluation information. And then, the cloud model is developed to deal with the randomness and fuzziness of LFHS. Thirdly, a multi criteria decision-making model based on improved Choquet fuzzy integral and deviation degree is proposed for a multi criteria evaluation problem with initial data in the form of crisp values, interval numbers and linguistic fuzzy hesitant sets. The deviation degree can deal with multi-source heterogeneous data and Choquet fuzzy integral improved with Mobius transformation can eliminate the overlap information between criteria. Finally, the case study in Jilin is given to illustrate the effective of the proposed evaluation criteria and technique. From the results, the project 4: wind power coupling compressed air energy storage system with meshing switch is the most suitable alternative for the wand farm, followed by the project of wind power coupling compressed air energy storage system with variable configuration. Moreover, the sensitivity analysis reveals that the project 4 always occupies its top ranking when its weight is floating within a certain range. At last, some policy implications to promote wind power industry are given for the government. • The sustainability evaluation criteria system for wind power project is presented. • A MCDM method based on Choquet fuzzy integral and Mobius transformation is proposed. • Linguistic fuzzy hesitant sets are used to present subjective evaluation information. • The proposed model can deal with multi-source heterogeneous data. [ABSTRACT FROM AUTHOR]