Abstract
To optimally design integrated energy systems a widely used approach is the Energy Hub. The conversion, storage and transfer of different energy vectors is represented by a coupling matrix. Yet, the coupling matrix restricts the configuration of the Energy Hub and the constraints, that can be included. This paper proposes a MILP based optimization framework, which allows a high variability and adaptability and is based on energy flows. The functionality of the developed framework is tested on four use cases depicting different system sizes and Energy Hub configurations. It is shown that the framework is able to simplify the design process of an Energy Hub.