Hierarchical fuzzy neural networks toward a unified load dynamics modeling framework

Modeling of both static and dynamic load characteristics has been studied in the context of voltage stability analysis incorporating load models. With the consideration that load models, or more precisely, load prediction models, can be used to predict the load shapes for the future from a few hours up to several days, and motivated by the fact that the various load models for different application purposes can be accommodated in a general mathematical form, this paper is intended for providing a unified framework to accommodate various applications that make use of load models whether they are represented in a mathematical form suitable for load dynamics modeling used in regular power system stability analysis, or used in voltage stability analysis, or used for forecasting purposes. The study is conducted in conjunction with the application of hierarchical fuzzy neural networks. It is shown that modeling of load dynamics can be formulated in such a way that hierarchical fuzzy neural networks become naturally and logically applicable. A few theoretical results on hierarchical fuzzy neural networks for load modeling are presented. Furthermore, a study case is presented to illustrate how hierarchical fuzzy neural networks can be applied and how they perform, which demonstrates the effectiveness of the proposed unified framework for modeling of load dynamics