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


  • Voll, Philip
  • Klaffke, Carsten
  • Hennen, Maike
  • Bardow, André


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.

Suggested Citation

  • Voll, Philip & Klaffke, Carsten & Hennen, Maike & Bardow, André, 2013. "Automated superstructure-based synthesis and optimization of distributed energy supply systems," Energy, Elsevier, vol. 50(C), pages 374-388.
  • Handle: RePEc:eee:energy:v:50:y:2013:i:c:p:374-388
    DOI: 10.1016/

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    References listed on IDEAS

    1. Fazlollahi, Samira & Mandel, Pierre & Becker, Gwenaelle & Maréchal, Francois, 2012. "Methods for multi-objective investment and operating optimization of complex energy systems," Energy, Elsevier, vol. 45(1), pages 12-22.
    2. Fred Glover, 1975. "Improved Linear Integer Programming Formulations of Nonlinear Integer Problems," Management Science, INFORMS, vol. 22(4), pages 455-460, December.
    3. Mehleri, Eugenia D. & Sarimveis, Haralambos & Markatos, Nikolaos C. & Papageorgiou, Lazaros G., 2012. "A mathematical programming approach for optimal design of distributed energy systems at the neighbourhood level," Energy, Elsevier, vol. 44(1), pages 96-104.
    4. Voll, Philip & Lampe, Matthias & Wrobel, Gregor & Bardow, André, 2012. "Superstructure-free synthesis and optimization of distributed industrial energy supply systems," Energy, Elsevier, vol. 45(1), pages 424-435.
    5. Rong, Aiying & Lahdelma, Risto & Luh, Peter B., 2008. "Lagrangian relaxation based algorithm for trigeneration planning with storages," European Journal of Operational Research, Elsevier, vol. 188(1), pages 240-257, July.
    6. Dimopoulos, George G. & Frangopoulos, Christos A., 2008. "Optimization of energy systems based on Evolutionary and Social metaphors," Energy, Elsevier, vol. 33(2), pages 171-179.
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