Abstract: Advanced compressed air energy storage (A-CAES) has emerged as one of the most promising new energy storage technologies due to its distinctive advantages such as large capacity, non-supplementary firing, long lifespan, and low specific investment. To fully exploit the potential of A-CAES and enhance the rationality of its optimal planning, a multi-stage optimization planning strategy for large-scale A-CAES considering its multi-application values in peak shaving, reserve, ramping, and inertia support is proposed. Firstly, the growth trends of new energy and load demand are taken into consideration, then a framework and process for multi-stage optimization planning of large-scale A-CAES are established. Secondly, the application values and operational characteristics of A-CAES in peak shaving, emergency reserve, flexible ramping, and inertia support are investigated. Finally, guided by the multi-stage economic and multi-scale effectiveness values, these operational characteristics are mapped into planning boundaries to construct a multi-stage optimization planning model for large-scale A-CAES. Case studies based on the modified IEEE-118-bus system demonstrate that the proposed strategy can fully consider the multi-application values of large-scale A-CAES for allocation, thereby avoiding energy storage resource redundancy caused by over-investment and rough estimation.