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Multi-objective optimization of a multi water-to-water heat pump system using evolutionary algorithm

Author

Listed:
  • Murr, R.
  • Thieriot, H.
  • Zoughaib, A.
  • Clodic, D.

Abstract

This paper deals with the energy recovery in the dairy industry. Thermodynamic, economic and environmental optimization of three water-to-water heat pumps has been studied in order to replace totally or partially a fuel boiler used to produce heat at different temperature levels in a cheese factory. These heat pumps have their evaporators connected to one effluents source and two of them are equipped by storage tanks at the condenser side. Multi-objective optimization permits optimal repartition of mass flow rates of effluents and optimal choice of electrical power of the compressors and volumes of storage tanks. The thermodynamic objective is based on the exergy destruction in the whole system. The economic objective is based on the investment cost and the operating cost obtained with the heat pump system. The environmental impact objective has been defined and expressed in cost terms by considering a CO2 taxation (carbon tax) on the GHG emissions. This objective has been integrated with the economic objective. Multi-objective genetic algorithms are used for Pareto approach optimization.

Suggested Citation

  • Murr, R. & Thieriot, H. & Zoughaib, A. & Clodic, D., 2011. "Multi-objective optimization of a multi water-to-water heat pump system using evolutionary algorithm," Applied Energy, Elsevier, vol. 88(11), pages 3580-3591.
    • Handle: RePEc:eee:appene:v:88:y:2011:i:11:p:3580-3591
    DOI: 10.1016/j.apenergy.2011.04.013
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    References listed on IDEAS

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    1. Saidur, R. & Ahamed, J.U. & Masjuki, H.H., 2010. "Energy, exergy and economic analysis of industrial boilers," Energy Policy, Elsevier, vol. 38(5), pages 2188-2197, May.
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    Cited by:

    1. Cheung, Brian C. & Carriveau, Rupp & Ting, David S.K., 2014. "Multi-objective optimization of an underwater compressed air energy storage system using genetic algorithm," Energy, Elsevier, vol. 74(C), pages 396-404.
    2. Namuli, R. & Jaumard, B. & Awasthi, A. & Pillay, P., 2013. "Optimisation of biomass waste to energy conversion systems for rural grid-connected applications," Applied Energy, Elsevier, vol. 102(C), pages 1013-1021.
    3. Kang, Lixia & Liu, Yongzhong, 2015. "Multi-objective optimization on a heat exchanger network retrofit with a heat pump and analysis of CO2 emissions control," Applied Energy, Elsevier, vol. 154(C), pages 696-708.
    4. Breen, M. & Murphy, M.D. & Upton, J., 2019. "Development of a dairy multi-objective optimization (DAIRYMOO) method for economic and environmental optimization of dairy farms," Applied Energy, Elsevier, vol. 242(C), pages 1697-1711.
    5. Sorgüven, Esra & Özilgen, Mustafa, 2012. "Energy utilization, carbon dioxide emission, and exergy loss in flavored yogurt production process," Energy, Elsevier, vol. 40(1), pages 214-225.
    6. Yang, Minbo & Li, Ting & Feng, Xiao & Wang, Yufei, 2020. "A simulation-based targeting method for heat pump placements in heat exchanger networks," Energy, Elsevier, vol. 203(C).

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