Considering the uncertainty of renewable energy station output, a two?stage optimization model for AC/DC parallel transmission channel power distribution of a power system with a high proportion of renewable energy is established based on the distributionally robust optimization (DRO) method. The objective function of the first stage is to minimize the sum of active power loss costs of all transmission lines in the forecast scenario. The objective function of the second stage is to minimize the expected adjustment cost of directly dispatching generators and DC transmission lines power under the worst?case probability distribution (PD). When constructing the ambiguity set of PDs, Hellinger distance is used to measure the distance between real PD and reference PD, and the Markov chain is used to describe the time correlation of renewable energy station output. The column and constraint generation algorithm is used to solve the two?stage DRO model to obtain the day?ahead power transmission schedules of AC/DC parallel transmission channels. Finally, with the case study on an actual Hybrid AC/DC power grid and the computational results demonstrate the correctness and effectiveness of the proposed model and algorithm.