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Performance investigation of a SOFC-primed micro-combined hybrid cooling and power system in hot and humid regions

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  • Fong, K.F.
  • Lee, C.K.

Abstract

The provision of cooling in a high-capacity trigeneration system is challenging due to the huge difference in the energy performance between heat-driven and electricity-driven cooling equipment. A micro-scale application can be more attractive, particularly when the recovered waste heat is solely used to drive a desiccant dehumidification cycle in a hybrid cooling system which offers better energy performance for use in hot and humid regions. Thus, given the availability of small-capacity solid oxide fuel cells (SOFCs), a SOFC-primed micro-combined hybrid cooling and power (mCHyCP) system was developed, and its performance in a 24-h restaurant in Singapore and in Hong Kong was analyzed. It was found that by performing year-round dynamic simulations using TRNSYS, a 10% reduction in the total electricity demand could be achieved in the tropical Singaporean climate compared to a 5% reduction in demand in the sub-tropical Hong Kong climate. This reflected the effect of different seasons on the performance of the mCHyCP system. In addition, at most 24% and 38% reductions in the primary energy consumption and carbon dioxide emissions for both regions could be achieved, which indicated the potential of such system as a sustainable distributed energy source.

Suggested Citation

  • Fong, K.F. & Lee, C.K., 2019. "Performance investigation of a SOFC-primed micro-combined hybrid cooling and power system in hot and humid regions," Energy, Elsevier, vol. 189(C).
    • Handle: RePEc:eee:energy:v:189:y:2019:i:c:s0360544219319930
    DOI: 10.1016/j.energy.2019.116298
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    References listed on IDEAS

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    Cited by:

    1. Gao, D.C. & Sun, Y.J. & Ma, Z. & Ren, H., 2021. "A review on integration and design of desiccant air-conditioning systems for overall performance improvements," Renewable and Sustainable Energy Reviews, Elsevier, vol. 141(C).
    2. Changhee Song & Sanghoon Lee & Bonhyun Gu & Ikwhang Chang & Gu Young Cho & Jong Dae Baek & Suk Won Cha, 2020. "A Study of Anode-Supported Solid Oxide Fuel Cell Modeling and Optimization Using Neural Network and Multi-Armed Bandit Algorithm," Energies, MDPI, vol. 13(7), pages 1-11, April.
    3. Roselli, C. & Marrasso, E. & Tariello, F. & Sasso, M., 2020. "How different power grid efficiency scenarios affect the energy and environmental feasibility of a polygeneration system," Energy, Elsevier, vol. 201(C).

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