Behavioral Modeling Paradigm for DC Nanogrid Based Distributed Energy Systems

Abstract

The remarkable progress of power electronic converters (PEC) technology has led to their increased penetration in distributed energy systems (DES). Particularly, the direct current (dc) nanogrid-based DES embody a variety of sources and loads, connected through a central dc bus. Therefore, PECs are required to be employed as an interface. It would facilitate incorporation of the renewable energy sources and battery storage system into dc nanogrids. However, it is more challenging as the integration of multiple modules may cause instabilities in the overall system dynamics. Future dc nanogrids are envisioned to deploy ready-to-use commercial PEC, for which designers have no insight into their dynamic behavior. Furthermore, the high variability of the operating conditions constitute a new paradigm in dc nanogrids. It exacerbates the dynamic analysis using traditional techniques. Therefore, the current work proposes behavioral modeling to perform system level analysis of a dc nanogrid-based DES. It relies only on the data acquired via measurements performed at the input–output terminals only. To verify the accuracy of the model, large signal disturbances are applied. The matching of results for the switch model and its behavioral model verifies the effectiveness of the proposed model.

Keywords

• behavioral modeling
• direct current (dc) nanogrid
• distributed energy systems
• power electronic converters
• renewable energy sources
• system identification