Model Structure Selection and Validation for Dynamic Equivalencing of Distribution Networks

Modeling of distribution networks has received a renewed interest due to the appearance of dynamic phenomena arising from the increasing penetration levels of distributed generation. The conflicting implications of a model’s parsimony and flexibility, required model accuracy, available a priori information, and the purpose of a model, are inherent in system modeling. To tackle these issues, different models and identification methods have been proposed with the aim of representing the response of distributed generation to system events. The number of proposed models points to the fact that no single model can represent all possible dynamic behaviors of distribution networks. To facilitate, and even automate, model structure selection, this paper proposes a method that sequentially processes system events and classifies them as informative or noninformative for parameter identification. The method then uses informative events for parameter identification while the noninformative ones are used for optimal model structure selection and validation. Such selected and validated models can then be used in operation for dynamic security assessment of a transmission system. The performance of the proposed method is demonstrated in the case of equivalencing of a distribution network with photovoltaic and wind generation.