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Equipment arrangement planning of a fuel cell energy network optimized for cost minimization

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  • Obara, Shin’ya

Abstract

The systems configuration and operation plan of a fuel cell energy network using the micro-grid of the power using a solid polymer membrane-type fuel cell and the hot-water piping network to which exhaust heat is conveyed are considered. In this study, a computer program that optimizes the equipment arrangement of each building linked to a fuel cell network and the path of the hot-water piping network for supplying the exhaust heat of fuel cells and reformers to each house under the cost minimization objective was developed. As a result of analyzing the fuel cell network constructed in four to nine houses using the energy demand pattern of the average house of Sapporo, which is a cold, snow-covered city, compared with the system that is not optimized, it clearly showed lower equipment and installation costs. As a result of using and analyzing the energy demand pattern of the house in Sapporo, and outside temperature data in February, there will be 18%–25% cost reduction by optimization. Having optimized and planned the path of hot-water piping and arrangement of equipment so that the heat release of a hot-water piping network decreases is a reason for the cost reduction result. Furthermore, by this study, the capacity of a heat storage tank, and the arrangement planning of boilers and each capacity, and the quantity of flow of the hot-water circulating pump were investigated, and the operation plan of each piece of equipment was considered.

Suggested Citation

  • Obara, Shin’ya, 2007. "Equipment arrangement planning of a fuel cell energy network optimized for cost minimization," Renewable Energy, Elsevier, vol. 32(3), pages 382-406.
    • Handle: RePEc:eee:renene:v:32:y:2007:i:3:p:382-406
    DOI: 10.1016/j.renene.2006.02.012
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    Citations

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    Cited by:

    1. Zhang, Di & Samsatli, Nouri J. & Hawkes, Adam D. & Brett, Dan J.L. & Shah, Nilay & Papageorgiou, Lazaros G., 2013. "Fair electricity transfer price and unit capacity selection for microgrids," Energy Economics, Elsevier, vol. 36(C), pages 581-593.
    2. Basrawi, Firdaus & Yamada, Takanobu & Obara, Shin’ya, 2014. "Economic and environmental based operation strategies of a hybrid photovoltaic–microgas turbine trigeneration system," Applied Energy, Elsevier, vol. 121(C), pages 174-183.
    3. Ding, Yan & Wang, Qiaochu & Tian, Zhe & Lyu, Yacong & Li, Feng & Yan, Zhe & Xia, Xi, 2023. "A graph-theory-based dynamic programming planning method for distributed energy system planning: Campus area as a case study," Applied Energy, Elsevier, vol. 329(C).
    4. Zhang, Di & Evangelisti, Sara & Lettieri, Paola & Papageorgiou, Lazaros G., 2015. "Optimal design of CHP-based microgrids: Multiobjective optimisation and life cycle assessment," Energy, Elsevier, vol. 85(C), pages 181-193.
    5. 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.
    6. Guerrero Moreno, Nayibe & Cisneros Molina, Myriam & Gervasio, Dominic & Pérez Robles, Juan Francisco, 2015. "Approaches to polymer electrolyte membrane fuel cells (PEMFCs) and their cost," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 897-906.
    7. 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.
    8. Sameti, Mohammad & Haghighat, Fariborz, 2018. "Integration of distributed energy storage into net-zero energy district systems: Optimum design and operation," Energy, Elsevier, vol. 153(C), pages 575-591.
    9. Wouters, Carmen & Fraga, Eric S. & James, Adrian M., 2015. "An energy integrated, multi-microgrid, MILP (mixed-integer linear programming) approach for residential distributed energy system planning – A South Australian case-study," Energy, Elsevier, vol. 85(C), pages 30-44.

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