考虑联络线端点分布的分布鲁棒优化调度

As power systems scale up and uncertainties deep-en,traditional centralized optimization approaches impose sig-nificant computation burdens on large-scale optimization prob-lems,introducing new challenges for power system scheduling.To address these challenges,this study formulates a distribution-ally robust optimization(DRO)scheduling model that considers source-load uncertainty and is solved using a novel distributed approach that considers the distribution of tie-line endpoints.The proposed model includes a constraint related to the trans-mission interface,which consists of several tie-lines between two subsystems and is specifically designed to ensure technical operation security.In addition,we find that tie-line endpoints enhance the speed of distributed computation,leading to the de-velopment of a power system partitioning approach that consid-ers the distribution of these endpoints.Further,this study pro-poses a distributed approach that employs an integrated algo-rithm of column-and-constraint generation(C&CG)and sub-gradient descent(IACS)to address the proposed model across multiple subsystems.A case study of two IEEE test systems and a practical provincial power system demonstrates that the pro-posed model effectively ensures system security.Finally,the scal-ability and effectiveness of the distributed approach in acceler-ating problem-solving are confirmed.