This study explores the multiple functions of liquid air energy storage (LAES) in a hybrid renewable micro-grid, which hasn't been covered so far, to decarbonize the distributed energy systems that are increasingly popular. To cope with this, a decoupled off-design LAES model was developed, and integrated into a micro-grid mixed-integer linear programming (MILP) design framework. This methodology enables studying the optimal energy to power ratios of LAES, and the identification of specific value streams of the storage, as well as optimally sizing the micro-grid equipment and LAES units simultaneously, to achieve the balanced economics and environmental benefits. The simulation has led to three major results. Firstly, the optimal charge/discharge power and storage capacity of LAES vary with the services it provides. The optimal charge/discharge energy to power ratio are 8/3 h, 12/6 h and 12/6 h corresponding to the arbitrage, wind stabilization and operating reserve. Secondly, for a micro-grid with ∼50% of wind power, LAES presents the key value in supporting the system operation by providing multiple functions. It is split into six explicit revenue streams that can be stacked up for the first time, including the time shifting (13.2%), renewable firming (11.4%), peak shaving (28%), flexibility (21%) and reserve value (20.4%), as well as the waste heat recovery (6%). Thirdly, in comparison with the mildly reduced LAES capital cost and enlarged electricity price differences, a higher renewable percentage would be a major driving force to increase the attractiveness of LAES in micro-grids. The system design framework can determine the optimal sizes of the micro-grid components and the LAES units. Specifically, the optimal charge/discharge energy to power ratio (27/14 h) and the storage tank size (608 t) of LAES in a micro-grid with 75% wind power are obtained, leading to ∼60% of carbon emission reduction on the 2016 level. The importance of this work lies in it provides the preliminary business model of applying small-scale LAES in hybrid renewable micro-grids, and can promote the optimal deployment of LAES under different scenarios in micro-grids.