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Modeling and optimization of a network of energy hubs to improve economic and emission considerations

Author

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  • Maroufmashat, Azadeh
  • Elkamel, Ali
  • Fowler, Michael
  • Sattari, Sourena
  • Roshandel, Ramin
  • Hajimiragha, Amir
  • Walker, Sean
  • Entchev, Evgueniy

Abstract

Energy hubs that incorporate a variety of energy generation and energy transformation technologies can be used to provide the energy storage needed to enable the efficient operation of a ‘smart energy network’. When these hubs are combined as a network and allowed to exchange energy, they create efficiency advantages in both financial and environmental performance. Further, the interconnectedness of the energy network design provides an added layer of reliability. In this paper, a complex network of energy hubs is modeled and optimized under different scenarios to examine both the financial viability and potential reduction of greenhouse gas emissions. Two case studies consisting of two and three energy hubs within a network are considered. The modeling Scenarios vary according to the consideration of distributed energy systems and energy interaction between energy hubs. In the case of a network of two energy hubs, there is no significant economic or emissions benefit with only a 0.5% reduction in total cost and 3% reduction in CO2 emission. In the case of a network of three energy hubs, there is a significant economic benefit ranging from 11% to 29%, and 11% emission reduction benefit, as well as a 13% reduction in natural gas consumption.

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  • Maroufmashat, Azadeh & Elkamel, Ali & Fowler, Michael & Sattari, Sourena & Roshandel, Ramin & Hajimiragha, Amir & Walker, Sean & Entchev, Evgueniy, 2015. "Modeling and optimization of a network of energy hubs to improve economic and emission considerations," Energy, Elsevier, vol. 93(P2), pages 2546-2558.
    • Handle: RePEc:eee:energy:v:93:y:2015:i:p2:p:2546-2558
    DOI: 10.1016/j.energy.2015.10.079
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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. Koeppel, Gaudenz & Andersson, Göran, 2009. "Reliability modeling of multi-carrier energy systems," Energy, Elsevier, vol. 34(3), pages 235-244.
    3. Akorede, Mudathir Funsho & Hizam, Hashim & Pouresmaeil, Edris, 2010. "Distributed energy resources and benefits to the environment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(2), pages 724-734, February.
    4. Mancarella, Pierluigi, 2014. "MES (multi-energy systems): An overview of concepts and evaluation models," Energy, Elsevier, vol. 65(C), pages 1-17.
    5. Evins, Ralph & Orehounig, Kristina & Dorer, Viktor & Carmeliet, Jan, 2014. "New formulations of the ‘energy hub’ model to address operational constraints," Energy, Elsevier, vol. 73(C), pages 387-398.
    6. Fabrizio, Enrico & Corrado, Vincenzo & Filippi, Marco, 2010. "A model to design and optimize multi-energy systems in buildings at the design concept stage," Renewable Energy, Elsevier, vol. 35(3), pages 644-655.
    7. Baños, R. & Manzano-Agugliaro, F. & Montoya, F.G. & Gil, C. & Alcayde, A. & Gómez, J., 2011. "Optimization methods applied to renewable and sustainable energy: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(4), pages 1753-1766, May.
    8. Rieder, Andreas & Christidis, Andreas & Tsatsaronis, George, 2014. "Multi criteria dynamic design optimization of a small scale distributed energy system," Energy, Elsevier, vol. 74(C), pages 230-239.
    9. 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.
    10. 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.
    11. 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.
    12. Bracco, Stefano & Delfino, Federico & Pampararo, Fabio & Robba, Michela & Rossi, Mansueto, 2014. "A mathematical model for the optimal operation of the University of Genoa Smart Polygeneration Microgrid: Evaluation of technical, economic and environmental performance indicators," Energy, Elsevier, vol. 64(C), pages 912-922.
    13. Yang, Christopher, 2008. "Hydrogen and electricity: Parallels, interactions,and convergence," Institute of Transportation Studies, Working Paper Series qt0p14s1cg, Institute of Transportation Studies, UC Davis.
    14. Wakui, Tetsuya & Kinoshita, Takahiro & Yokoyama, Ryohei, 2014. "A mixed-integer linear programming approach for cogeneration-based residential energy supply networks with power and heat interchanges," Energy, Elsevier, vol. 68(C), pages 29-46.
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