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Sizing the prime mover of a residential micro-combined cooling heating and power (CCHP) system by multi-criteria sizing method for different climates

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  • Ebrahimi, Masood
  • Keshavarz, Ali

Abstract

In the present study, a multi-criteria sizing function (MCSF) is proposed for designing the optimum size and operating strategy of the prime mover of a residential micro-combined cooling heating and power (CCHP) system. The CCHP prepares the electrical, thermal, cooling, and domestic hot water demands of the same building in five different climates in Iran. The MCSF integrates fuel energy saving ratio (FESR) and exergy efficiency as the thermodynamical parameters, net present value, internal rate of return and payback period for the economical criteria, and CO2, CO and NOx reduction for the environmental evaluations. Analytical hierarchy process is used to weigh each criterion with respect to others. The engine proposed by MCSF results in considerable fuel saving and pollution reduction and a payback period of about 6 years for the 5 climates. In addition, the best strategy according to the engine size is determined for every climate.

Suggested Citation

  • Ebrahimi, Masood & Keshavarz, Ali, 2013. "Sizing the prime mover of a residential micro-combined cooling heating and power (CCHP) system by multi-criteria sizing method for different climates," Energy, Elsevier, vol. 54(C), pages 291-301.
    • Handle: RePEc:eee:energy:v:54:y:2013:i:c:p:291-301
    DOI: 10.1016/j.energy.2013.01.061
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    13. Wonchala, Jason & Hazledine, Maxwell & Goni Boulama, Kiari, 2014. "Solution procedure and performance evaluation for a water–LiBr absorption refrigeration machine," Energy, Elsevier, vol. 65(C), pages 272-284.
    14. Sara Ghaem Sigarchian & Anders Malmquist & Viktoria Martin, 2018. "Design Optimization of a Small-Scale Polygeneration Energy System in Different Climate Zones in Iran," Energies, MDPI, vol. 11(5), pages 1-19, May.
    15. Li, Miao & Mu, Hailin & Li, Nan & Ma, Baoyu, 2016. "Optimal design and operation strategy for integrated evaluation of CCHP (combined cooling heating and power) system," Energy, Elsevier, vol. 99(C), pages 202-220.
    16. Yang, Liu & Yan, Haiyan & Lam, Joseph C., 2014. "Thermal comfort and building energy consumption implications – A review," Applied Energy, Elsevier, vol. 115(C), pages 164-173.
    17. Ershadi, Hamed & Karimipour, Arash, 2018. "Present a multi-criteria modeling and optimization (energy, economic and environmental) approach of industrial combined cooling heating and power (CCHP) generation systems using the genetic algorithm,," Energy, Elsevier, vol. 149(C), pages 286-295.
    18. Fuentes-Cortés, Luis Fabián & Dowling, Alexander W. & Rubio-Maya, Carlos & Zavala, Víctor M. & Ponce-Ortega, José María, 2016. "Integrated design and control of multigeneration systems for building complexes," Energy, Elsevier, vol. 116(P2), pages 1403-1416.
    19. De Boeck, L. & Verbeke, S. & Audenaert, A. & De Mesmaeker, L., 2015. "Improving the energy performance of residential buildings: A literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 960-975.
    20. 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).
    21. Miao Li & Yiran Feng & Maojun Zhou & Hailin Mu & Longxi Li & Yajun Wang, 2019. "Economic and Environmental Optimization for Distributed Energy System Integrated with District Energy Network," Energies, MDPI, vol. 12(10), pages 1-19, May.
    22. Wang, Jiang-Jiang & Fu, Chao & Yang, Kun & Zhang, Xu-Tao & Shi, Guo-hua & Zhai, John, 2013. "Reliability and availability analysis of redundant BCHP (building cooling, heating and power) system," Energy, Elsevier, vol. 61(C), pages 531-540.
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    24. Dai, Rui & Hu, Mengqi & Yang, Dong & Chen, Yang, 2015. "A collaborative operation decision model for distributed building clusters," Energy, Elsevier, vol. 84(C), pages 759-773.

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