Distributionally robust planning method for cyber-physical distribution system based on the coordinated recovery of multi-type resilience resources

Ice-covering disasters with increased frequency and intensity pose a serious threat to the reliable operation of cyber-physical distribution systems (CPDS). In order to fully exploit the complementary advantages of resilience resources and accelerate the load recovery process, this paper proposes the distributionally robust planning method for CPDS based on the coordinated recovery of multi-type resilience resources. Firstly, based on the meteorological elements of disasters, the cumulative thickness of ice accumulation at the source-grid level is quantified. By analyzing the abnormal effect mechanism of ice accumulation on wind power generation loss and line failure rate, the source-side wind power output model and the grid-side line failure model considering disaster accumulation are constructed. Secondly, considering the dynamic coordination between line fault repair status and network topology changes, the coordinated recovery model for fault repair and network reconfiguration based on spatiotemporal mobility is constructed. Thirdly, taking into account the coupled control relationship between the distribution network and the communication network, the bi-layer resilience planning model for CPDS based on distributionally robust chance constraint is constructed. Among them, the upper model configures distributed units with the minimum investment cost in the pre-disaster stage, and the lower model determines the optimal scheduling decision that meets resilience indicator thresholds with the minimum load recovery cost in the post-disaster stage. Finally, the objective function is reconstructed by combining strong duality theory, and the conditional value-at-risk theory is used to perform convex optimization on the chance constraint. And the effectiveness of the proposed planning method in ensuring the reliability of power supply is verified through case studies.