The energy system of the future is expected to be composed of a large variety of technologies and applications. However, the diverse nature of these components, their interlinked topology, and the sheer size of the system lead to an unprecedented level of complexity. Industry is confronted with severe problems in designing interoperable grid components, analyzing system stability, and improving efficiency. This paper describes the main challenges of continuous time-based and discrete event-based models of such cyber-physical energy systems. Using a characteristic test model, the scalability of the two approaches is analyzed. The results show the strengths and weaknesses of these two fundamentally different modeling principles that need to be considered when working with large scale cyber-physical energy systems.

With the transition toward a smart grid, the power system has become strongly intertwined with the information and communication technology (ICT) infrastructure. The interdependency of both domains requires a combined analysis of physical and ICT processes, but simulating these together is a major challenge due to the fundamentally different modeling and simulation concepts. After outlining these challenges, such as time synchronization and event handling, this paper presents an overview of state-of-the-art solutions to interface power system and ICT simulators. Due to their prominence in recent research, a special focus is set on co-simulation approaches and their challenges and potentials. Further, two case studies analyzing the impact of ICT on applications in power system operation illustrate the necessity of a holistic approach and show the capabilities of state-of-the-art co-simulation platforms.

Energy systems experience a rise in complexity: new technologies, topologies and components, tighter links to other systems like markets and the increased usage of information technology. This leads to challenging questions that can not be answered via traditional methods. The goal of including renewable energy and clean technologies in the grid, however, requires solutions for the resulting complex problems. This paper investigates dynamic demand response for intelligent electric vehicle charging as a use-case for detailed hybrid models that cannot be properly handled by traditional tools alone. Universal modeling languages and specialized domain-specific modeling solutions are brought together via standardized co-simulation interfaces to achieve maximal flexibility and minimal implementation efforts. This combination of previously numerically incompatible modeling paradigms enables a detailed look into the dynamics of hybrid component models while keeping the comfort and the strength of established tools. This coupling of a Modelica-based physical simulation engine, a commercial power system simulation tool and an agent-based discrete event simulator for energy grids results in a novel co-simulation platform. This visionary concept provides the high level of detail, scope, flexibility, scalability and accuracy in simulations needed to analyze and optimize energy systems of the future.

Recently many commercial and non-commercial Simulation Packages (SPs) have agreed to use the Functional Mockup Interface (FMI) as the medium of interoperability. FMI presents numerous opportunities to utilize highly specialized SPs for modeling, and simulating multidisciplinary applications with several components of various types. However there is one thing missing in the FMI; the master algorithm. The paper proposes to use, the High Level Architecture (HLA) compliant Run Time Infrastructure (RTI), as a master for the FMI compatible simulation components. The ultimate goal is to provide a completely generic and standalone master for the FMI, making FMI-based simulation components usable as plug and play components, on variety of distributed environments including grids and clouds. Towards this promising goal an initial methodology is outlined.