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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.