Resilience improvement model of distribution network based on two-stage robust optimization

Abstract

Frequent natural disasters have a serious impact on the power system. It is urgent to ensure the normal operation of the distribution network under disaster events. This paper divides the stages of improving the resilience of the distribution network into two aspects: long-term investment planning and short-term response. We combine the decision-making process with the chronological order of natural disasters, and a N-k uncertainty set is applied to describe the uncertainty of distribution network damage. We propose a line hardening and distributed generations configuration strategy for the purpose of enhancing the resilience of distribution networks and countering extreme natural disasters. The problem is expressed as a tri-level robust optimization formulation in order to minimize the load shedding under the worst line damaged scheme. The first level corresponds to the long-term investment planning and preparation of pre-disaster stage. The second level represents the stage of line damage, and the third level matches the optimal scheduling during the post-disaster period. On the basis, this mixed integer linear programming problem is transformed into a solvable form, which is calculated by a modified Column and Constraint Generation (C&CG) algorithm. Case studies show that our proposed model can reduce load shedding to 70% of the original level, and the running time of the algorithm is less than 60 s, which verifies the model can effectively enhance the resilience of the distribution network and enhance its ability to respond to natural disasters.