Equivalent modeling and simulation of cascading dynamics via neural network algorithm for A Microgrid Network

Due to the complex structure of microgrids, there is currently a lack of an orderly modeling framework. This article proposes a dynamic equivalent modeling method for microgrids based on cascaded neural network models. Clustering the physical network of microgrids based on prior knowledge, and proposing a dynamic equivalent modeling method for each group using neural networks. The effectiveness of the method is verified through simulation using a 10-node microgrid clusters as the object.