The continuously increasing complexity of modern and sustainable power and energy systems leads to a wide range of solutions developed by industry and academia. To manage such complex system-of-systems, proper engineering and validation approaches, methods, concepts, and corresponding tools are necessary. The Smart Grid Architecture Model (SGAM), an approach that has been developed during the last couple of years, provides a very good and structured basis for the design, development, and validation of new solutions and technologies. This review therefore provides a comprehensive overview of the state-of-the-art and related work for the theory, distribution, and use of the aforementioned architectural concept. The article itself provides an overview of the overall method and introduces the theoretical fundamentals behind this approach. Its usage is demonstrated in several European and national research and development projects. Finally, an outlook about future trends, potential adaptations, and extensions is provided as well.

The 5G radio access network (RAN) features a partially centralized architecture, in which a subset of the network functions are deployed in a centralized unit. Centralizing these functions reduces operating costs and enables coordination techniques. However, the more functions are centralized, the more capacity is needed on the fronthaul network connecting centralized and distributed units. In addition, the required fronthaul capacity also depends on the instantaneous user traffic, which varies over time. Therefore, in order to optimize its performance, the 5G RAN should be able to dynamically adapt its centralization level to the user traffic. In this paper, we present the design of an adaptive RAN that can switch between two different centralization options at runtime. We provide design objectives and challenges, as well as measurement results from a working implementation.

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Although, a variety of established tools for analysis of power systems already exists, it is in the medium term very unlikely that one of these tools alone will provide all functionalities and models that are required to simulate future Smart Grids in all its facets. This is mainly due to the high number of Smart Grid use cases, actors, and technologies to be integrated that is not known from other industries so far. Accordingly, a mixture of various different and established tools will be required. These, again, have to be composed in use cases specific to complex and system-wide scenarios. Therefore, tools such as simulation platforms and -suites are required that are additionally capable of integrating software-and hardware models and components. Therefore, the proposed approach is an integrated concept allowing for analyzing large-scale scenarios taking into consideration both, stationary and dynamic simulations in real-time.