A Differential Planning Strategy for Distribution Network Resilience Enhancement Considering Decision Dependence Uncertainty

To reduce the impact of extreme natural disasters on urban distribution networks and improve the interpretability of planning decisions, this paper proposes a distributionally robust planning strategy for distribution networks that considers decision-dependent uncertainty. First, a decision-dependent uncertainty model is established to represent the relationship between power line failure probability and reinforcement decisions, with uncertainty described using norm-bounded fuzzy sets. Then, a three-level distributionally robust multi-grade reinforcement model is developed, which retains typical fault scenarios to reduce computational complexity and improve efficiency. Next, a global sensitivity analysis method based on the Sobol’ approach is introduced to analyze the marginal effects of resilience investments and quantify the impact of specific reinforcement measures on total planning cost and overall power system resilience. Finally, simulations based on the IEEE 33-bus test system verify the effectiveness of the proposed planning strategy. The results show that the proposed method can effectively enhance grid resilience while improving the interpretability of planning strategies.