Distribution Network Reconstruction Based on Artificial Immune Algorithm

In this paper, an improved artificial immune algorithm is proposed, which significantly improves the convergence speed of the algorithm and effectively avoids the immature convergence problem by introducing mechanisms such as vaccination, high-frequency mutation and immune renewal. This algorithm has been successfully applied in distribution network reconfiguration, and can quickly generate high-quality reconfiguration schemes, thus reducing network loss and improving system stability, and achieving good optimization results. In addition, this paper innovatively adopts the switching state (0 or 1) of the branch as the control parameter, abandoning the traditional cumbersome coding method, greatly shortening the coding length and simplifying the calculation process. This concise coding method not only reduces the search space, but also significantly improves the computational efficiency of the algorithm, providing an efficient and practical solution for power system optimization.