Research on self-healing function of smart distribution network based on adaptive genetic algorithm

Based on the impact of the uncertainty of distributed power supply output and load on the distribution network tide, a distribution network post-fault self-healing model is established considering factors such as supply capacity, load priority, network loss and operation loss. An improved adaptive genetic algorithm is proposed, which adopts the initial population generation based on loop unbundling. The algorithm performs coding and genetic operations for distribution network structure characteristics to avoid generating infeasible solutions, and finally obtains the target optimal distribution network self-healing scheme. The IEEE33 node distribution network architecture is used as an example for simulation, and the proposed algorithm is verified to be higher efficient and stable in finding the optimal solution. At the same time, the network structure is changed through self-healing, which can effectively reduce the reduction of network loss.