Grid interlocking fault prevention and control method considering safety and network loss

The paper proposes a chain fault prevention and control method that takes into account safety and network loss to address chain fault accidents and the economic operation of the grid. The method is based on the Elman neural network to identify the key nodes that can reduce network loss and improve the safety margin. Secondly, a two-layer optimization model is established, in which the inner model is used to solve the safety level of the grid for interlocking faults characterized by the distance between nodes injecting power, and the outer model integrates the maximum safety distance and the minimum network loss of the grid for interlocking faults. Finally, the basic particle swarm algorithm is used to solve the two-layer optimization model based on the IEEE-39 node system. The results of the arithmetic example show that the method can improve the security level of the grid in a targeted way so that the security margin is increased from 0.004 to 20.0992 and, at the same time reduce the network loss, so that the network loss is reduced from 0.5166 to 0.4865, which effectively compresses the scope of control and reduces the difficulty of preventive control.