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The convergent performance of the auxiliary problem principle based distributed and parallel optimization algorithm (APPBDPOA) is dependent on its parameters and power network partition. Because of the complexity of the optimal power flow, it is difficult to obtain the sufficient and necessary conditions of convergence for APPBDPOA in theory. In this paper the convergent performance of APPBDPOA is studied through large numbers of tests. The relations between parameters and convergent performance and the influence of the power network partition on convergent speed are discussed. The conclusions can guide the parameter evaluation, which is significant for optimizing the power network partition and further speeding up APPBDPOA.