A two-stage solution approach based on complementary constraints and The Transformer Model with A Dummy Node is proposed to efficiently solve the large-scale nonlinear dynamic reactive power optimization (DRPO) problem with multi-period period coupled absolute value constraints and integer variables. The model for DRPO problem is represented by adding the voltage of the dummy nodes in the on-load tap changer transformer model to express the power and voltage relations firstly. Then the multi-period coupled absolute value constraints in the model are relaxed by linearization method, and the original model is respectively converted into a continuous mathematical programming model with complementary constraints based on complementary conditions and equivalent conversion of discrete variables. The solution steps are decomposed into two stages which are solved by the interior point method sequentially. In the first stage, the approximate optimization solution for discrete variables is quickly obtained without considering complementary constraints. And in the second stage, the complete model with complementary constraints is solved to obtain accurate optimization solutions for both discrete and continuous variables. Furthermore, a sparse storage and fast calculation method is proposed to reduce the computational complexity of the integrated Hessian matrix during the iteration of the interior point method. The simulation results of standard test systems such as IEEE 118-bus demonstrate the effectiveness and efficiency of the proposed approach.