Improve operational flexibility of distribution systems using transportable resources

With the continuous progress of carbon neutrality, the accelerating integration of distributed renewable energy sources (RES) poses tremendous pressure on distribution systems' safe and stable operation. The distribution systems that cannot be upgraded in time, e.g., those in border areas, are hard to adapt to the large-scale integration of RES and the growing energy demand, facing a severe lack of operational flexibility. In light of this, the integrated mobile energy station (IMES), which consists of a battery system and photovoltaic cells, is used to improve operational flexibility and alleviate the need for upgrades. An adaptive robust allocation and dispatch model is introduced to coordinate the operation of the distribution system and IMES under multiple uncertainties. The first stage of the proposed model optimizes the locations of IMES using the forecast information of RES and loads, while the second stage optimizes the dispatch plan that is adaptive to the realization of uncertainties. Since the uncertain photovoltaic power in the IMES depends on its deployment location, the proposed model is an adaptive robust optimization with decision-dependent uncertainty, bringing great challenges to the solution. To solve it efficiently, a warmstart-enhanced column-and-constraint generation algorithm is introduced, in which the bi-level subproblem is solved by the dual method and outer approximation algorithm. Finally, case studies demonstrate the effectiveness of the proposed method. The participation of six IMESs can save 5.23 % on the system's total cost and avoid the load shedding caused by transmission congestion, indicating IMES's potential for economical and flexible operation of the system.