Identification of dynamic equivalents for distribution power networks using recurrent ANNs

This paper introduces a recurrent ANN-based dynamic equivalent for distribution networks in interconnected power systems and outlines the implementation of such equivalents in simulation packages. According to this approach, a recurrent ANN is trained in the offline mode using measurements only at boundary buses and hence it is independent of the network size and complexity. Then, a suitable dynamic model, which depends on the structure and parameters of the ANN, is developed and implemented within the simulation program. As the proposed ANN-based dynamic equivalent interacts with the retained subsystem in the online mode, it can be used for different stability analysis purposes. The proposed strategy is applied to define a dynamic equivalent for a distribution system containing a large number of active sources in a multimachine network. The dynamic performances of the original full network and that containing the equivalent model are simulated and their behaviours are compared under different disturbances in the retained network. The practical capability of the ANN in developing simple but accurate dynamic equivalents for distribution power networks is demonstrated through these comparisons.