Improving the Flexibility of the Distribution Network Based on the Robust Chance Constraint Method

Abstract

Abstract While the large-scale access to distributed new energy brings economic and environmental benefits, its inherent uncertainty characteristics also trigger problems such as voltage overruns and fluctuations. In order to effectively solve the adverse effects of large-scale grid connection of distributed new energy, this paper proposes the optimization method of regional autonomy capacity based on the robust chance constraint model. First, the regional autonomy capacity measurement method based on distribution robust optimization is studied, and the regional autonomy robust chance constraint model containing distributed energy is constructed. Second, the active distribution network scheduling model is studied to achieve the optimization of regional self-energy capacity. Finally, simulation examples show that the proposed approach can fully utilize the flexible resources within the distribution network and effectively improve the autonomy of the distribution network park.