Affine power flow calculation is an effective method for uncertainty analysis in power systems. With the increasing integration of distributed generation (DG), the existing Gaussian iterative affine power flow algorithm faces challenges in dealing with distribution networks that incorporate DG controlled by different strategies. To address these problems, a Gaussian iterative power flow algorithm for a distribution network that integrates an affine model for DG is proposed. Firstly, an uncertainty power flow model is established based on affine arithmetic, and a Gaussian iterative model for the affine power flow model is constructed. Secondly, the affine models for DG under different control strategies are established. By using common noise processing, reactive power correction, and voltage boundary correction, a Gauss iterative power flow algorithm for DG is proposed. Finally, through simulations on the IEEE 33-bus system, the effectiveness and reliability of the proposed algorithm are validated. The results indicate that the proposed method is capable of calculating the affine power flow in distribution networks with different DG control strategies, offering low conservatism and high computational efficiency.