Abstract: In this paper, the impact of widespread deployment of distributed energy resources (DERs) on fault location in distribution networks is systematically investigated. Through theoretical analysis and simulation experiments, the study examines how the integration of distributed renewable energy sources affects fault location processes in distribution grids. To address this, a new switch function and a fitness function are constructed, tailored for systems with multi-state, diverse distributed sources. Additionally, to enhance the optimization performance of the fault location algorithm, a multi-strategy improved crested porcupine optimizer (ICPO) algorithm is proposed. This algorithm incorporates an optimal position guidance to enhance the global search capability of the crested porcupine optimizer (CPO) algorithm, along with a lens imaging inverse learning strategy to enhance the capability of escaping local optima, thereby improving the optimization performance. Furthermore, a dynamic random walk strategy is implemented to escape local optima and improve the search for the optimal solution. Simulation results indicate that the proposed ICPO algorithm significantly improves accuracy, convergence speed, fault tolerance, and computational efficiency in fault location, particularly in active distribution networks experiencing single or multiple section faults, or when fault alarm information is distorted.