Hedayat Saboori

Previous research has proved that Mobile Battery Energy Storage (MBES) can play a pivotal role in achieving resiliency goals in distribution networks besides sustainability purposes. The missing links in the practical deployment of this new flexibility resource are the discontinuity between normal and emergency operating states in addition to the high computational burden. Accordingly, a new rolling-horizon operation model for a fleet of truck-mounted mobile batteries (TMMBs) employed in a joint transportation-distribution network is proposed. The model can effectively handle and switch between normal and emergency states by integrating a new schedule memory concept into the upcoming horizons. The spatial and temporal dynamics of the TMMBs, along with the transportation time and cost constraints, are modeled by a novel linear and computationally affordable formulation. The model runtime is further targeted by proposing a two-stage optimization model to detach transportation network calculations from the distribution grid. Additionally, a lexicographic multi-objective paradigm is used to ensure a maximum resiliency plan at the minimum expenses during emergencies. The model considers outage and congestion change of the road traffic beyond the forecasted values besides network uncertainties. Implementing the model on a test case proves its functionality in dealing with diverse network situations.