Partitioned sparse A-1 methods [power systems]

The classic Ax=b problem in the partitioning of sparse vector matrices is solved by constructing factored components of the inverses of L and U, the triangular factors of matrix A. The number of additional fill-ins in the partitioned inverses of L and U can be made zero. The number of partitions is related to the path length of sparse vector methods. Allowing some fill-in in the partitioned inverses of L and U results in fewer partitions. Ordering algorithms most suitable for sparsity preservation in the inverses of L and U require addition fill-in in L and U themselves. Tests on practical power system matrices with from 118 to 1993 nodes indicate that the proposed approach is competitive in serial environments, and appears more suitable for parallel environments. Because sparse vectors are not required, the approach works not only for short-circuit calculations but also for power flow and stability computations