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.
Highlights
The major factors that demand for a rapid progression towards distributed energy systems (DES) are the depletion of fossil fuels, climate change and the increase in power consumption
DC nanogrid-based DES are composed of several commercial power electronics converters (PEC)
The integration of a huge number of PEC in DES can at times negatively influence its dynamic behavior
Summary
The major factors that demand for a rapid progression towards distributed energy systems (DES) are the depletion of fossil fuels, climate change and the increase in power consumption. At the same time, due to the limited data availability about the internal design of converters, identification techniques are required to be employed to construct a model, which is able to capture their dynamic behavior. Modeling these types of systems is not straightforward because the dc nanogrid-based DES are characterized by the large variation in their operating conditions. For any PEC, the number of transfer functions required to construct its behavioral model is equal to the number of input variables times the number of output variables. The behavioral modeling technique has been applied to a complex dc nanogrid-based DEGSo,dw=hovvsiode block diGagoqra=m io =viq =0 ivso viq siho =owvidn=0inZFo ig=urvieoo vid =viq =0
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