Resilience enhancement of distribution networks based on demand response under extreme scenarios

Abstract

In the context of rare but high-impact extreme scenarios, such as natural disasters, it is crucial to utilize all available resources, including microgrids and distributed power sources, to restore critical loads in the distribution network as much as possible. This paper proposes a two-stage resilience enhancement strategy for distribution networks considering post-disaster topology reconstruction and demand response, aiming to facilitate the recovery of critical loads after disasters. In the first stage, a heuristic algorithm is introduced to determine the post-disaster topology of the distribution network. In the second stage, by employing a step-wise elastic load curve, user demand response is incorporated to maximize the socio-economic value of the restoration, and resilience metrics are computed. Finally, the effectiveness of the proposed resilience restoration strategy is validated through simulations on Case33 and Case69 systems.