The large-scale integration of new energy resource with strong uncertainty brings great challenges to the planning and operation of power systems. In this paper, a distributionally robust planning method of generation and transmission considering the multi-energy complementarity and DC transmission optimization is proposed. Firstly, considering wind-pumped storage complementarity and DC transmission power adjustment, a joint planning
model of generation and transmission is established with the objective of minimizing the annual comprehensive planning cost. On this basis, considering the strong uncertainty of wind power output, a two-stage distributionally robust planning model of generation and transmission based on probability scenario ambiguity sets is constructedand and solved by a parallel computable column-and-constraint generation algorithm. A modified generative adversarial network is adopted to generate typical planning scenarios. Finally, simulation with Graver-6 node system verifies that the proposed planning method can form a planning scheme that balances economic improvement and conservative control.