Abstract: To address the issue of high investment costs in building-side energy storage during urbanization, this paper proposes a bi-level optimal configuration method of intelligent buildings (IBs) based on shared energy storage services. First, a shared energy storage station (SESS) model considering the lifecycle is established. Then, a mathematical model for IBs is constructed, considering the thermal inertia of building structures and air conditioning systems. Next, the method comprehensively considers the differentiated interests and demands of both SESS and IBs, leading to the development of a bi-level optimal model based on SESS for IBs. The upper-level model aims to reduce the planning cost of the SESS. The lower-level model aims to minimize the annual operational cost of IBs and employs the KKT conditions to transform the original bi-level optimal problem into a single-level mixed-integer linear programming problem for solving. Finally, using four typical days from three IBs communities as examples, a comparative analysis is conducted to assess the impact of different optimal configurations on the operation of IBs and the configuration results of SESS. The case study demonstrates that the proposed optimal configuration method ensures the interests of different stakeholders, achieves a win-win situation for both SESS operators and IBs, and guarantees the temperature comfort of IBs' users.