Self-healing distribution expansion planning considering distributed energy resources, electric vehicles parking lots and energy storage systems

This paper addresses an iterative optimization model for self-healing distribution expansion planning considering distributed energy resources, electric vehicles' parking lots, and energy storage systems. The main contribution of this model is that the smart devices of smart homes are modeled and the impacts of their commitments are explored in the expansion planning exercise. The proposed algorithm is another contribution of this paper that consists of tri-stage optimization processes. In the first stage, the optimal commitment of smart devices of smart homes is solved considering the worst-case external shock impacts on the consumers' comfort levels. Then, the optimal expansion planning of the distribution system is determined in the second stage problem. Finally, in the third stage, the optimal topology and dispatch of distributed energy resources are determined for the external shock conditions. The effectiveness of the proposed algorithm was assessed for the modified 123-bus system. Based on the simulation results, the aggregated costs of the 123-bus system were reduced by about 42.62 % using the proposed framework. Further, the expected energy not supplied costs of the system were reduced from 113 million monetary units to 0.284 million monetary units based on the fact that the model endeavored to minimize the interruption of critical loads.