Abstract:

With the continuous expansion of the scale of bulk power grid, the operating characteristics of new power system has become more and more complex. Accurately identifying the weak links in the power grid is of great practical significance for improving the monitoring ability of the system and ensuring its reliable operation. Therefore, an identification strategy of weak links for power grid is proposed based on random matrix theory. The strategy uses the measured data in power grid operation to construct a random matrix and uses the weak links judgment index based on the random matrix theory to design the judgment method of weak nodes and weak branches. This method is analyzed from the perspective of data correlation, without considering the complex network structure and operation mechanism of the actual power grid, so there is no complex modeling process. To verify the feasibility of the method, an example simulation is established through the IEEE 39 node system and compared with the traditional methods. The results show that the proposed identification strategy has a good effect on identifying weak nodes and branches, and the accuracy is improved compared with the traditional methods.

Key words: bulk power grid, new power system, measured data, weak link identification, weak nodes, weak branch, data-driven, random matrix theory