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DESOD: a mathematical programming tool to optimally design a distributed energy system

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  • Bracco, Stefano
  • Dentici, Gabriele
  • Siri, Silvia

Abstract

One of the main challenges of the community is nowadays to satisfy end use energy demand in an eco-friendly and economic way. EU governmental policies encourage the spread of efficient and clean technologies in the energy sector, supporting distributed generation, cogeneration and trigeneration, as well as the exploitation of renewable sources. Furthermore, smart microgrid and energy storage systems have acquired more and more importance in the last years. Within this context, the DESOD (Distributed Energy System Optimal Design) tool, described in the present paper, has been developed at the University of Genoa. DESOD is based on a mixed-integer linear programming model to optimally design and operate a distributed energy system which provides heating, cooling and electricity to an urban neighborhood. In the paper, the model is described in detail and the results derived from its application to a real test case are discussed; a computational analysis of the model is reported as well.

Suggested Citation

  • Bracco, Stefano & Dentici, Gabriele & Siri, Silvia, 2016. "DESOD: a mathematical programming tool to optimally design a distributed energy system," Energy, Elsevier, vol. 100(C), pages 298-309.
  • Handle: RePEc:eee:energy:v:100:y:2016:i:c:p:298-309
    DOI: 10.1016/j.energy.2016.01.050
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    1. Chicco, Gianfranco & Mancarella, Pierluigi, 2009. "Distributed multi-generation: A comprehensive view," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(3), pages 535-551, April.
    2. Wang, Jiang-Jiang & Jing, You-Yin & Zhang, Chun-Fa, 2010. "Optimization of capacity and operation for CCHP system by genetic algorithm," Applied Energy, Elsevier, vol. 87(4), pages 1325-1335, April.
    3. Zhou, Zhe & Zhang, Jianyun & Liu, Pei & Li, Zheng & Georgiadis, Michael C. & Pistikopoulos, Efstratios N., 2013. "A two-stage stochastic programming model for the optimal design of distributed energy systems," Applied Energy, Elsevier, vol. 103(C), pages 135-144.
    4. Ren, Hongbo & Gao, Weijun, 2010. "A MILP model for integrated plan and evaluation of distributed energy systems," Applied Energy, Elsevier, vol. 87(3), pages 1001-1014, March.
    5. Cho, Heejin & Smith, Amanda D. & Mago, Pedro, 2014. "Combined cooling, heating and power: A review of performance improvement and optimization," Applied Energy, Elsevier, vol. 136(C), pages 168-185.
    6. Hawkes, A.D. & Leach, M.A., 2009. "Modelling high level system design and unit commitment for a microgrid," Applied Energy, Elsevier, vol. 86(7-8), pages 1253-1265, July.
    7. Casisi, M. & Pinamonti, P. & Reini, M., 2009. "Optimal lay-out and operation of combined heat & power (CHP) distributed generation systems," Energy, Elsevier, vol. 34(12), pages 2175-2183.
    8. Haeseldonckx, Dries & D'haeseleer, William, 2008. "The environmental impact of decentralised generation in an overall system context," Renewable and Sustainable Energy Reviews, Elsevier, vol. 12(2), pages 437-454, February.
    9. Franco, Alessandro & Salza, Pasquale, 2011. "Strategies for optimal penetration of intermittent renewables in complex energy systems based on techno-operational objectives," Renewable Energy, Elsevier, vol. 36(2), pages 743-753.
    10. Mehleri, E.D. & Sarimveis, H. & Markatos, N.C. & Papageorgiou, L.G., 2013. "Optimal design and operation of distributed energy systems: Application to Greek residential sector," Renewable Energy, Elsevier, vol. 51(C), pages 331-342.
    11. Bracco, Stefano & Dentici, Gabriele & Siri, Silvia, 2013. "Economic and environmental optimization model for the design and the operation of a combined heat and power distributed generation system in an urban area," Energy, Elsevier, vol. 55(C), pages 1014-1024.
    12. Weber, C. & Shah, N., 2011. "Optimisation based design of a district energy system for an eco-town in the United Kingdom," Energy, Elsevier, vol. 36(2), pages 1292-1308.
    13. Connolly, D. & Lund, H. & Mathiesen, B.V. & Leahy, M., 2010. "A review of computer tools for analysing the integration of renewable energy into various energy systems," Applied Energy, Elsevier, vol. 87(4), pages 1059-1082, April.
    14. 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.
    15. Pruitt, Kristopher A. & Braun, Robert J. & Newman, Alexandra M., 2013. "Evaluating shortfalls in mixed-integer programming approaches for the optimal design and dispatch of distributed generation systems," Applied Energy, Elsevier, vol. 102(C), pages 386-398.
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