Approximate sparse vector techniques for power network solutions

Approximate sparse vector techniques can be used to enhance solution speeds of sparsity-oriented power network algorithms. They are especially applicable to large problems in which rapid solutions are particularly important and where it may be advantageous to trade a certain amount of accuracy to gain speed. Speed is gained with approximate sparse vector techniques by skipping operations with relatively small effects in the forward/backward substitution when solving a sparse linear system of equations and when updating factors to reflect matrix changes. Four such techniques are described and discussed. Numerical examples showing the effectiveness of approximate sparse vector techniques for selected applications are also presented