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Thermo-economic and environmental optimization of solar assisted heat pump by using multi-objective particle swam algorithm

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  • Khorasaninejad, Ehsan
  • Hajabdollahi, Hassan

Abstract

In this paper, a solar assisted heat pump is modelled and optimized. Solar panel surface areas, evaporator pressure, condenser pressure, capacity of heat storage tank as well as the value of superheating/subcooling in evaporator/condenser are selected as design parameters. MOPSO (Multi-objective Particle Swarm Optimization) algorithm is used to find the optimum value of design parameters where TAC (total annual cost) and COP (coefficient of performance) taken as two objective functions. TAC is included with sum of investment, operation and environmental costs. The optimization is separately performed for five working fluids including R123, R134a, R245fa, R407C and R22. The optimization results showed that the best studied working fluid is R245fa in both thermo-economical and environmental view point with 1746.1 $/year as TAC, 3.76 for COP and annual environmental cost of 81.825. The optimum results of R245fa as working fluid, showed 15.22%, 21.28%, 22.31% and 44.66% improvement in TAC compared with R134a, R123, R22 and R407C, respectively. Furthermore, COP improvement for R245fa was obtained 26.77%, 30.92%, 34.31% and 48.12% compared with R134a, R123, R22 and R407C, respectively.

Suggested Citation

  • Khorasaninejad, Ehsan & Hajabdollahi, Hassan, 2014. "Thermo-economic and environmental optimization of solar assisted heat pump by using multi-objective particle swam algorithm," Energy, Elsevier, vol. 72(C), pages 680-690.
    • Handle: RePEc:eee:energy:v:72:y:2014:i:c:p:680-690
    DOI: 10.1016/j.energy.2014.05.095
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    10. Jorge E. De León-Ruiz & Ignacio Carvajal-Mariscal & Antonin Ponsich, 2019. "Feasibility Analysis and Performance Evaluation and Optimization of a DXSAHP Water Heater Based on the Thermal Capacity of the System: A Case Study," Energies, MDPI, vol. 12(20), pages 1-38, October.
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    12. Zhang, Ying & Deng, Shuai & Zhao, Li & Lin, Shan & Ni, Jiaxin & Ma, Minglu & Xu, Weicong, 2018. "Optimization and multi-time scale modeling of pilot solar driven polygeneration system based on organic Rankine cycle," Applied Energy, Elsevier, vol. 222(C), pages 396-409.
    13. Myeong Jin Ko, 2015. "Multi-Objective Optimization Design for Indirect Forced-Circulation Solar Water Heating System Using NSGA-II," Energies, MDPI, vol. 8(11), pages 1-25, November.
    14. Ding, Yan & Wang, Qiaochu & Kong, Xiangfei & Yang, Kun, 2019. "Multi-objective optimisation approach for campus energy plant operation based on building heating load scenarios," Applied Energy, Elsevier, vol. 250(C), pages 1600-1617.
    15. Sun, Li & Hua, Qingsong & Shen, Jiong & Xue, Yali & Li, Donghai & Lee, Kwang Y., 2017. "Multi-objective optimization for advanced superheater steam temperature control in a 300MW power plant," Applied Energy, Elsevier, vol. 208(C), pages 592-606.
    16. Poppi, Stefano & Sommerfeldt, Nelson & Bales, Chris & Madani, Hatef & Lundqvist, Per, 2018. "Techno-economic review of solar heat pump systems for residential heating applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 22-32.
    17. Mohammad Shafiey Dehaj & Hassan Hajabdollahi, 2021. "Multi-objective optimization of hybrid solar/wind/diesel/battery system for different climates of Iran," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(7), pages 10910-10936, July.
    18. Manoj Verma & Harish Kumar Ghritlahre & Surendra Bajpai, 2023. "A Case Study of Optimization of a Solar Power Plant Sizing and Placement in Madhya Pradesh, India Using Multi-Objective Genetic Algorithm," Annals of Data Science, Springer, vol. 10(4), pages 933-966, August.

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