Research on Fault Location Method of Distribution Network Based on Archimedes Optimization Algorithm

To address the challenges of high dimensionality, nonlinearity, and multiple constraints in distribution network fault location, where traditional intelligent optimization algorithms are prone to local optima and slow convergence, this paper proposes a fault location method based on the Archimedes Optimization Algorithm (AOA). By constructing a fault state encoding model for the distribution network, the fault location problem is transformed into a binary optimization problem. Leveraging the global search capability and convergence characteristics of the AOA, rapid and accurate location of faulty sections is achieved. Simulation experiments based on the IEEE 33-node system under various fault scenarios, including single-point and multi-point faults, demonstrate that the proposed method outperforms comparative algorithms in terms of convergence speed.