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In this paper, the author proposes a methodology to create a family of zonal Power Transfer Distribution Factor (PTDF) matrices that can be dynamically chosen to more estimate power flows more accurately for the zonal market model. Data mining methods are introduced to select typical hours based on area balance. PTDF matrices of these typical hours are calculated to form a family. The rule for assigning a PTDF matrix from such a family to a random hour is defined later. The method is tested on the New England system. The results show that using a family of PTDF matrices for estimating cross-border power flows in a zonal market model can significantly reduce the error compared with using only one PTDF matrix.