Active Splitting Control of Power System with High Proportion of Renewable Energy under Extreme Events

To deal with the dangers of extreme accidents, this paper investigates the active splitting control of power system with high proportion of renewable energy under extreme events. To start with, probabilistic models of power systems are built with considering the effects of extreme events, such as typhoons, ice disasters and earthquakes. On the basis, an appropriate active splitting control strategy based on genetic algorithm and back-propagation neural network (GA-BP) is presented to implement zoning and optimal control of the power system under extreme events. The objective function is to minimize the active power imbalance within each node set, so as to achieve the most balanced active power within each island. Finally, IEEE39-node system is established in the Matlab/Simulink to verify the presented active splitting with GA-BP.