Design and multilevel reconstruction method of intelligent power industry control system based on digital twins

Abstract

In order to improve the security and reliability of power industry control systems, research proposes the design of intelligent industrial control systems based on digital twins. This design combines the digital twin multilevel reconstruction method to construct an intelligent power control system structure, and proposes a system safety verification range design and evaluation indicators. The experimental data illustrates that the production time of the deep learning digital twin system reconstruction algorithm is 19.1% less than that of the reconstruction algorithm based on differential evolution; and when the number of nodes and the type and number of twins change, the algorithm proposed in the study takes less time and is more in line with the actual needs of the situation. The intelligent power industry control system based on digital twins has a score of no less than 9.5 in four aspects, indicating that the overall effectiveness of the system is good. The results indicate that this method can improve the safety and reliability of the system, ensure the stable operation of the power system, and provide technical support for the widespread application of intelligent power industry control systems.