It is shown that faster and highly localized power flow solutions can be obtained by exploring the difference in convergence rate of individual nodes. Nodes whose mismatches are smaller than a certain tolerance are processed as if their mismatches were actually zero. Computational effort is saved by skipping small mismatch computations and using sparse vector techniques for the nonzero mismatches. Since the proposed approach does not rely on network reduction or equivalencing, the accuracy of the solution remains high in all cases. The ZM (zero mismatch) approach can improve the speed of any Newton-like power flow algorithm without degrading solution accuracy. The relative advantage of ZM for contingency cases increases directly with network size. Its main advantage over other localization methods is that it uses the unmodified global factors of the FDPF (fast decoupled power flow) algorithm and requires no equivalents. ZM exploits the physical characteristics of power flows, the numerical characteristics of iterative solutions, and the sparsity of the matrix factors.
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