This paper studied a collaborative decision model to optimize electricity flow among commercial buildings, electric vehicle (EV) charging stations, and the grid under power demand uncertainty. We propose a two-stage stochastic programming model that realistically captures different operational constraints between multiple commercial buildings and EV charging stations. We developed a customized solution approach based on Sample Average Approximation method that can solve the proposed model efficiently and accurately. Finally, a real-life case study is constructed that draws managerial insights into how different key input parameters (e.g., grid power unavailability, power collaboration restriction) affect the overall energy network design and cost.