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Distributed optimization is becoming popular to solve a large power system problem with the objective of reducing computational complexity. To this end, the convergence performance of distributed optimization plays an important role to solve an optimal power flow (OPF) problem. One of the critical factors that have a significant impact on the convergence performance is the reference bus location. Since selecting the reference bus location does not affect the result of centralized DC OPF, we can change the location of the reference bus to get more accurate results in distributed optimization. In this paper, our goal is to provide some insights into how to select reference bus location to have a better convergence performance. We modeled the power grid as a graph and based on some graph theory concepts, for each bus in the grid a score is assigned, and then we cluster buses to find out which buses are more suitable to be considered as the reference bus. We implement the analytical target cascading (ATC) on the IEEE 48-bus system to solve a DC OPF problem. The results show that by selecting a proper reference bus, we obtained more accurate results with an excellent convergence rate while improper selection may take much more iterations to converge.