Active Distribution Grid Risk Prevention and Control Method Based on Biological Immune Mechanism

Aiming at the insufficient optimization ability of traditional active distribution network (ADN) fault recovery, a combination of immune mechanism and immune genetic algorithm is proposed for risk prevention and control. First, a risk assessment model is constructed from the perspective of reliability of equipment operation and consequences of faults; second, for the first N scenarios with higher risk, a fault pre-recovery scheme is established with the objectives of restoring the most power supply, minimizing the number of switching times, and minimizing the network loss, and the immune genetic algorithm is used to solve the problem. The N scenarios are recorded in the set of expected incidents to expand the immune memory cell library; finally, the simulation is carried out using the IEEE 33-node distribution network model as an example, and the simulation results show the feasibility of the proposed risk prevention and control strategies and the algorithms used, which lays a foundation for the subsequent fast and accurate recovery of power supply.