AbstractThe strong interconnection between human activities, energy use and pollution reduction strategies in contemporary society has determined the necessity of collecting scientific knowledge from different fields to provide useful methods and models to foster the transition towards more sustainable energy systems. This is a challenging task in particular for contemporary communities where an increasing demand for services is combined with rapidly changing lifestyles and habits. The Smart Grid concept is the result of a confluence of issues and a convergence of objectives, which include national energy security, climate change, pollution reduction, grid reliability, etc. While thinking about a paradigm shift in energy systems, drivers, characteristics, market segments, applications and other interconnected aspects must be taken into account simultaneously. In this context, the use of multi-commodity network flow models for dynamic energy management aims at finding a compromise between model usefulness, accuracy, flexibility, solvability and scalability in Smart Grid applications.