In a multi-infeed HVDC receiving system with wind power, the power support provided by the HVDC system and wind power can accelerate load recovery, but the inevitable uncertainty of wind power and load will bring challenges to recovery security. Therefore, a restoration decision-making method that can make full use of existing data to reduce the risk of uncertainty is proposed. First, this method considers the power control characteristics of an HVDC system and establishes a power control constraint model of multiple HVDC links. Secondly, the ambiguity sets of wind power output and load based on Wasserstein distance are constructed to describe the source-load uncertainty. Then a restoration risk index is defined to describe the risk of security violations caused by uncertainty. A two-stage distributionally robust optimization model is established to minimize the recovery risk under the worst-case probability distribution of ambiguity sets. Finally, by using dual theory and the big-M method, the model is transformed into a deterministic mixed integer linear programming problem. The method can make full use of the existing data, provide a robust and flexible and adjustable optimal load recovery scheme, and balance the economy and safety in the recovery process. The results show that the proposed method can effectively guarantee the coordinated optimization of HVDC transmission power and the safe and orderly access of load, and eliminate the operational risk caused by uncertainty. This work is supported by the National Key Research and Development Program of China (No. 2016YFB0900100).