Transactive Energy-Based Sequential Load Restoration of Distribution Systems With Networked Microgrids Under Uncertainty

Natural disasters such as hurricane would cause damages in distribution systems (DSs), resulting in large-scale blackouts. In order to reduce socioeconomic losses under blackouts, it is critical to enhance resilience of DSs through a series of restoration means. Microgrids (MGs) are considered as viable and critical sources to provide emergency power support, and can facilitate restoration of DSs when properly coordinated with the utility-owned control measures. Instead of direct coordination control, this paper proposes a transactive energy (TE) framework for load restoration of DSs, under which the distribution system operator (DSO) organizes a TE market with MGs to trade emergency energy through price signals. Moreover, in order to consider renewable generation uncertainties, a distributionally robust optimization (DRO)-based sequential load restoration model is formulated under the TE framework to maximize the expected restored load with respect to the worst-case probability distribution. Case studies were conducted on the modified IEEE 123 node system. Simulation results show that the proposed strategy can effectively coordinate MGs scheduling to assist in load restoration. Moreover, as compared to the conventional stochastic programming model, the proposed DRO model is less sensitive to the number of scenarios modeled and can produce a more robust solution against out-of-sample scenarios.