The random nature of a power system is accentuated by large-scale wind generation. Probabilistic load flow is an important tool for steady-state operation evaluation analysis that takes into account the random nature of the system. Considering the random nature and correlation of output power of several wind farms, a probability model based on Gaussian mixture model improved by genetic algorithm is proposed, which can exactly characterize the random nature and correlation of renewable generation. On this basis, the joint probability density function and joint cumulative distribution function of transmission lines are derived by a load flow equation, which obtains the results of probabilistic load flow. Simulation results demonstrate that the proposed method gives high accuracy and high speed. The method can assess the risk of multiple lines being overloaded simultaneously. This work is supported by National Natural Science Foundation of China (No. 51637005), Fundamental Research Funds for the Central Universities (No. 2018MS006), and Science and Technology Project of State Grid Corporation of China (Research and Design of System Level Control Protection Technology Framework for Extra Large Power Grid) (No. SGBJDK00KJJS1900088).