EPCs (Electronic Power Converters) are the key elements of the smart dc microgrid architectures. In order to enhance the controllability of the system, most of the elements are envisioned to be connected to the different buses through EPCs. Therefore, power flow, stability, and dynamic response in the microgrid are function of the behavior of the EPCs and their control loops.Besides, dc microgrids constitute a new paradigm in power distribution systems due to the high variability of their operating conditions, owing to the intermittent behavior of the renewable sources and customer energy consumption. Furthermore, in order to deal with this variability, the power converters can modify their operation mode, adding complexity to the dynamic and stability analysis of the system. This paper gives an overview of the various analytical and blackbox modeling strategies applied to smart dc micro/nanogrids. Different linear and nonlinear modeling techniques are reviewed describing their capabilities, but also their limitations. Finally, differences among blackbox models will be highlighted by means of illustrative examples.
The smart grid concept is increasingly becoming popular within the academia and industry. The integration of electronic power converters as an enabler for the massive deployment of distributed renewable energy sources, along with the inclusion of control, monitoring and automation systems in the grid, has drawn the attention of many researchers. Furthermore, a transition towards dc distribution is currently under investigation due to its more suitable interface with most of the modern loads and sources, which offers benefits in terms of size, cost and reliability of the whole system.This paper proposes a black-box polytopic modeling approach as a tool for the system-level design of dc based nanogrids. This strategy allows both small and large-signal analysis of power distribution systems even when commercial off-the-shelf converters have to be integrated. In addition, the main characteristics of the dc bus signaling control, i.e. droop control, changes in power converter control mode and disconnection of loads, have been incorporated in the modeling structure.
Modern electric power distribution systems are progressively integrating electronic power converters. However, the design of electronic-power-converter-based systems is not a straightforward task, as the interactions among the different converters can lead to dynamic degradation or instabilities. In addition, electric power distribution systems are expected to consist of commercial-off-the-shelf converters, which implies limited information about the dynamic behavior of the devices. Large-signal blackbox modeling approaches have been proposed in order to obtain accurate dynamic models of commercial converters that can be used for system-level analyses. However, most of the works are focused on DC-DC converters. In this work, a large-signal blackbox model is proposed to model grid-connected three-phase DC-AC converters. An experimental setup has been used to demonstrate the limitations of small-signal models and the capability of the proposed modeling approach to capture the dynamic behavior of the converter when large perturbations are applied. Finally, the automation of the model identification process is discussed.
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