Automated superstructure-based synthesis and optimization of distributed energy supply systems

A framework is presented for the automated superstructure generation and optimization of distributed energy supply systems (DESS). Based on a basic problem description (specifying load cases, available technologies, and topographic constraints), the presented framework first employs the P-graph approach for the generation of an initial superstructure containing exactly one unit of each feasible technology. DESS, however, require to account for multiple redundant conversion units, and thus a successive approach is employed to automatically expand the initial P-graph superstructure. In addition, topographic constraints are incorporated. The expanded superstructure is automatically converted into a mathematical model using a generic component-based modeling approach. Here, a robust MILP formulation is used to rigorously optimize the structure, sizing and operation of DESS. The employed MILP formulation accounts for time-varying load profiles, continuous equipment sizing, and part-load dependent operating efficiencies. In the present implementation, a GAMS model is generated that can be readily optimized. The methodology is applied to a real-world case study. It is shown that the framework conveniently and efficiently enables automated grassroots and retrofit synthesis of DESS identifying unexpected and complex designs.