Load aggregators should fully consider the impact of fixed and inverter air conditioning groups' characteristics and the interaction willingness of users in different scenarios on the adjustable potential，when integrating and managing air-conditioning load resources. Firstly，two air conditioner monomer models and aggregation models are constructed for engineering applications，based on the detailed analysis of the differentiated working state of fixed and inverter air conditioners. Secondly，quantitative analysis is carried out to analyze the interaction willingness of users in different scenarios，days types，and time-of-use electricity prices. An air conditioning adjustable potential calculation model is proposed considering interaction willingness. Then，the multi-scenario adjustable temperature interval is obtained based on the interaction willingness of the users and used as a constraint to construct an optimization model for control strategies. The osprey-Cauchy-sparrow search algorithm （OCSSA） is applied to solve and obtain multi-scenario control instructions for fixed and inverter air conditioners. Finally，the high precision temperature control command is accurately calculated through the proposed control method，and the requirements of preset load reduction command is successfully met in the final control results. By considering different user interaction willingness，the ability to adaptively and accurately control fixed and inverter air conditioning loads is demonstrated in various scenarios.