This paper presents a novel probabilistic power flow calculation method for power systems with integrated wind farms, based on importance sampling and Hammersley sequence with eigen-decomposition. The method proposed in this paper adopts importance sampling to build probability density functions in a desired range to compress the sampling space and hence reduce the calculation burden. The Hammersley sequence, a kind of low discrepancy sequence, is used to obtain uniform samples for improving the sampling efficiency. In addition, since the traditional Cholesky method is unable to decompose the non-positive definite correlation matrix, this paper applies the eigen-decomposition to solve this problem for multiple correlated wind sources. Case studies are conducted on modified IEEE test systems, where the advantages of the proposed method are verified. According to the simulation results, the proposed method shows greater accuracy and efficiency, compared to the traditional methods.