Fault Location of Active Distribution Network Based on Improved Gray Wolf Algorithm

As the scale of the power grid continues to expand and a large number of distributed power sources are connected, the difficulty of locating faults is increasing. The gray wolf optimization algorithm is simple in principle, easy to implement and has good global performance, so it is widely used, but the algorithm also has the defects of low optimization accuracy and easy to fall into the local optimal solution. Based on the gray wolf algorithm based on dynamic update weights, this paper proposes an improved gray wolf optimization algorithm. The algorithm first improved the C strategy to balance the global exploration and local development capabilities of the algorithm; then the sine and cosine global optimization strategy was used to guide and update the position again to reduce the premature probability and improve the algorithm optimization accuracy; finally, the adaptive local optimization strategy was used to select the optimal solution through neighborhood comparison to avoid the algorithm falling into the local optimal solution. The gray wolf optimization algorithm before and after the improvement is used to simulate and analyze the fault section location, which further verifies the correctness and superiority of the algorithm.