Identifying backbone grid has great significance to the differential planning of power grid, which can improve the ability to withstand natural disasters effectively. This paper presents an approach to construct backbone grid by taking the uncertainty of wind power into account. The approach can balance the survivability and cost, which represented by the sum of lines and busses. The biogeography-based optimization algorithm (BBO) is applied to search for backbone grid. In order to improve the convergence rate and precision, modified migration model, random perturbation operator, clear duplicate operator and repairing strategy which based on the theory of min-imum spanning tree are employed in the algorithm. Compared to traditional BBO, genetic algorithm (GA) and binary particle swarm optimization (BPSO), the improved algorithm can figure out backbone grid more effectively, which has optimal indices of survivability and cost. Also, the optimal case satisfies constraint conditions of power grid safe operation and connectivity. The backbone can weaken the influence of wind power uncertainty to a certain extent.