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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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Control of power converters in AC microgrids is well understood and established in the literature and in the industry, allowing the high penetration of distributed generation, electrical energy storage systems and controllable loads. These building blocks connected to the grid through power electronic converters open new opportunities to the expansion of microgrids in electrical power systems. A behavioral large-signal nonlinear polytopic model for grid-supporting converters operating as a current source is proposed in this paper. This model is able to represent the nonlinear behavior of the power converter and it is also very well suited for system-level modeling and simulation. The proposed modeling strategy can be easily extended to power converters in any other of the possible operating modes.

DC electric power distribution is becoming popular due to the proliferation of renewable sources and storage elements in applications such as electric vehicles, ships, aircrafts, microgrids, etc. These systems are characterized by a high integration of power electronic converters. From a system-level perspective, it would be desirable to design this kind of systems using commercial-off-the shelf converters. However, in general, the manufacturers do not provide a behavioral model of the devices in order to analyze the dynamic behavior of the interconnected system before the actual implementation. In the literature, several blackbox modeling techniques have been proposed to overcome this lack of information. This paper proposes the integration of dynamic weighting functions to the polytopic model in order to improve the accuracy of the behavioral models when the input variables change sharply. A boost converter is used as case study and the performance of the proposed model is compared with the most relevant techniques that can be found in the literature. INDEX TERMS Blackbox models, dc microgrids, dc-dc converters, dynamic interactions, electronic power distribution, modeling, system identification, nonlinear models. AIRÁN FRANCÉS (GS'16-M'18) received the M.Sc. and Ph.D. degrees in electrical engineering from the Universidad Politécnica de Madrid (UPM), Spain, in 2012 and 2018, respectively. He is currently an Assistant Professor with the Department of Electrical Engineering, UPM. He participated for two years in the European Project XFEL, where he collaborated in the design and development of dc-dc power supplies for superconducting magnets. His current research interests include modeling, control and stability assessment of electronic power distribution systems, and smart grids.

The huge progress of power electronics technology along last decades opens extraordinary new possibilities for the electric grid. Some examples of what can be achieved with the incorporation of electronic power converters in the system are the penetration of RS (renewable sources) and storage, boosting reliability and power quality, and integrating consumers as part of the system. However, there are still some challenges ahead before the massive deployment of Smart Grids.Lately, a lot of research has been carried out on converters topologies and control strategies in order to get the most out of the microgrids. Therefore, there is a need for methodologies that allow designers to foresee the behavior of these systems comprised of several different power converters governed by the proposed control strategies. In this context, this paper studies the performance of the polytopic models for the analysis of commercial power converters working in dc microgrids. This is a nonlinear modeling technique which integrates small-signal models obtained in different operation points by means of suitable weighting functions. Furthermore, the linear local models can be obtained in a blackbox fashion using suitable two-port models as can be the G-parameters models. This work particularly focuses on the analysis of different power converters using the well-known dc bus signaling control strategy. Thus the modeling of the diverse possible states in which this control technique can operate, and more important the transitions among them, are investigated. In addition, the feasibility of applying system level control techniques to the polytopic models of the converters, such as current sharing or voltage restoration, is considered.