A Stochastic Bi-level Optimal Allocation Approach of Intelligent Buildings Considering Energy Storage Sharing Services

To decrease the investment cost of energy storage for urbanization purposes, a stochastic bi-level optimal allocation approach of intelligent buildings (IBs) considering energy storage sharing (ESS) services is proposed. First, based on the thermal inertia (TI) of buildings and the lifecycle of energy storage devices, a detailed thermal dynamic model of IBs equipped with air conditioning (AC) systems and the ESS station model are established respectively. Then, a stochastic bi-level optimal allocation model of IBs considering ESS services is established to consider the uncertainties of electricity prices. Given the different interests of the ESS station and IBs, the upper-level model aims to reduce the planning costs of the ESS station, and the lower-level model aims to reduce the annual operating costs of IBs. Finally, the nonlinear bi-level model is converted into a single-level mixed-integer linear programming problem using the Karush–Kuhn–Tucher (KKT) condition. The results show that while meeting the temperature comfort demands of IBs users, the proposed stochastic bi-level optimal allocation approach can guarantee the interests of different agents under the uncertainties of electricity prices and achieve a win-win situation for the ESS station and IBs.