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A decision-making method to choose optimal systems considering financial and environmental aspects: Application in hybrid CCHP systems

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  • Melo, F.M.
  • Magnani, F.S.
  • Carvalho, M.

Abstract

This work presents a decision-making method based on a multiobjective optimization model that integrates renewable and nonrenewable energy equipment and considers environmental and financial combined gains. Parametric studies optimize the system for other energy tariffs, and an investment risk analysis provides additional information about the systems identified by the decision-making method and in the parametric studies. The energy system is located in northeastern Brazil. The bicriteria optimal solution comprises a gas boiler, solar collector, photovoltaic panels, wind turbines, and absorption and compression chillers. This optimal solution had a reasonable commitment to financial and environmental present values. Another energy system was identified in the parametric study, where an engine-generator set and a recovery boiler were included. Both systems presented a significant gain in environmental present value versus a slight decrease in financial present value. In the risk analysis, these systems demonstrated high adaptability, mainly due to the integration of the absorption chiller and engine-generator set and cascading use of energy. This high adaptability led to low investment risks.

Suggested Citation

  • Melo, F.M. & Magnani, F.S. & Carvalho, M., 2022. "A decision-making method to choose optimal systems considering financial and environmental aspects: Application in hybrid CCHP systems," Energy, Elsevier, vol. 250(C).
    • Handle: RePEc:eee:energy:v:250:y:2022:i:c:s0360544222007198
    DOI: 10.1016/j.energy.2022.123816
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    References listed on IDEAS

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    1. Bruno Campos Teixeira de Carvalho & Caio Tácito Miranda Castro Bezerra C.T.M.C.B. de Melo & Alberto Romero Freire & Shoaib Khanmohammadi & Monica Carvalho, 2019. "Multicriteria optimization of renewable-based polygeneration system for tertiary sector buildings," ULB Institutional Repository 2013/308977, ULB -- Universite Libre de Bruxelles.
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    Cited by:

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    2. Junchao Cheng & Yongyi Huang & Hongjing He & Abdul Matin Ibrahimi & Tomonobu Senjyu, 2023. "Optimal Operation of CCHP System Combined Electric Vehicles Considering Seasons," Energies, MDPI, vol. 16(10), pages 1-21, May.
    3. Justyna Kozłowska & Marco Antônio Benvenga & Irenilza de Alencar Nääs, 2022. "Investment Risk and Energy Security Assessment of European Union Countries Using Multicriteria Analysis," Energies, MDPI, vol. 16(1), pages 1-28, December.
    4. Jie Ji & Fucheng Wang & Mengxiong Zhou & Renwei Guo & Rundong Ji & Hui Huang & Jiayu Zhang & Muhammad Shahzad Nazir & Tian Peng & Chu Zhang & Jiahui Huang & Yaodong Wang, 2022. "Evaluation Study on a Novel Structure CCHP System with a New Comprehensive Index Using Improved ALO Algorithm," Sustainability, MDPI, vol. 14(22), pages 1-20, November.
    5. Pourmoghadam, Peyman & Kasaeian, Alibakhsh, 2023. "Economic and energy evaluation of a solar multi-generation system powered by the parabolic trough collectors," Energy, Elsevier, vol. 262(PA).
    6. Dai, Yiru & Zeng, Yipu, 2022. "Optimization of CCHP integrated with multiple load, replenished energy, and hybrid storage in different operation modes," Energy, Elsevier, vol. 260(C).

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