Aiming at the problem that residual current detection in low-voltage distribution areas containing photovoltaic power supply is easily affected by multiple factors and difficult to achieve accurate detection of leakage faults, a leakage fault detection method for low-voltage distribution areas containing photovoltaic power supply is proposed based on the random forest algorithm, taking into account the residual current disturbance factors. By mining and analyzing residual current disturbance factors from multiple perspectives, the residual current deviation method is used to quantitatively analyze the impact of residual current disturbance factors on residual current. The frequency domain characteristics of leakage faults considering residual current disturbance factors are analyzed, and multidimensional fault feature vectors and feature datasets are constructed. A leakage fault detection model based on random forest algorithm is established. Through simulation analysis and verification using a simulation model, the results show that the proposed method can detect leakage faults with high accuracy. Compared with commonly used methods, the fault detection accuracy and stability of the proposed method are higher, and the anti-interference ability is stronger.