IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i16p5864-d887006.html
   My bibliography  Save this article

Multi-Objective Optimization of an Irreversible Single Resonance Energy-Selective Electron Heat Engine

Author

Listed:
  • Jinhu He

    (Institute of Thermal Science and Power Engineering, Wuhan Institute of Technology, Wuhan 430205, China
    Hubei Provincial Engineering Technology Research Center of Green Chemical Equipment, Wuhan 430205, China
    School of Mechanical & Electrical Engineering, Wuhan Institute of Technology, Wuhan 430205, China)

  • Lingen Chen

    (Institute of Thermal Science and Power Engineering, Wuhan Institute of Technology, Wuhan 430205, China
    Hubei Provincial Engineering Technology Research Center of Green Chemical Equipment, Wuhan 430205, China
    School of Mechanical & Electrical Engineering, Wuhan Institute of Technology, Wuhan 430205, China)

  • Yanlin Ge

    (Institute of Thermal Science and Power Engineering, Wuhan Institute of Technology, Wuhan 430205, China
    Hubei Provincial Engineering Technology Research Center of Green Chemical Equipment, Wuhan 430205, China
    School of Mechanical & Electrical Engineering, Wuhan Institute of Technology, Wuhan 430205, China)

  • Shuangshuang Shi

    (Institute of Thermal Science and Power Engineering, Wuhan Institute of Technology, Wuhan 430205, China
    Hubei Provincial Engineering Technology Research Center of Green Chemical Equipment, Wuhan 430205, China
    School of Mechanical & Electrical Engineering, Wuhan Institute of Technology, Wuhan 430205, China)

  • Fang Li

    (Institute of Thermal Science and Power Engineering, Wuhan Institute of Technology, Wuhan 430205, China
    Hubei Provincial Engineering Technology Research Center of Green Chemical Equipment, Wuhan 430205, China
    School of Mechanical & Electrical Engineering, Wuhan Institute of Technology, Wuhan 430205, China)

Abstract

Based on the model of irreversible single resonance energy-selective electron heat engine established in the previous literature, this paper applies finite-time thermodynamic theory and NSGA-II algorithm to perform multi-objective optimization. Single-, bi-, tri- and quadru-objective optimizations are performed when the energy boundary and the resonance width are taken as the optimization variables, and the power output, thermal efficiency, efficient power and ecological function are taken as the optimization objectives. The deviation indexes of different optimization objective combinations are obtained by using LINMAP, TOPSIS and Shannon entropy approaches. The results show that the values of energy boundary and resonance width can be reasonably selected according to the design requirements of the system. When power output and efficiency are optimized, the minimal deviation index is obtained by TOPSIS approach and the value is 0.0748, which is the most ideal design scheme.

Suggested Citation

  • Jinhu He & Lingen Chen & Yanlin Ge & Shuangshuang Shi & Fang Li, 2022. "Multi-Objective Optimization of an Irreversible Single Resonance Energy-Selective Electron Heat Engine," Energies, MDPI, vol. 15(16), pages 1-19, August.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:16:p:5864-:d:887006
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/16/5864/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/16/5864/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Arora, Ranjana & Kaushik, S.C. & Arora, Rajesh, 2015. "Multi-objective and multi-parameter optimization of two-stage thermoelectric generator in electrically series and parallel configurations through NSGA-II," Energy, Elsevier, vol. 91(C), pages 242-254.
    2. Zhou, Junle & Chen, Lingen & Ding, Zemin & Sun, Fengrui, 2016. "Analysis and optimization with ecological objective function of irreversible single resonance energy selective electron heat engines," Energy, Elsevier, vol. 111(C), pages 306-312.
    3. David Diskin & Leonid Tartakovsky, 2020. "Efficiency at Maximum Power of the Low-Dissipation Hybrid Electrochemical–Otto Cycle," Energies, MDPI, vol. 13(15), pages 1-10, August.
    4. Ding, Ze-Min & Chen, Lin-Gen & Wang, Wen-Hua & Ge, Yan-Lin & Sun, Feng-Rui, 2015. "Exploring the operation of a microscopic energy selective electron engine," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 431(C), pages 94-108.
    5. Shiyang Teng & Yong-Qiang Feng & Tzu-Chen Hung & Huan Xi, 2021. "Multi-Objective Optimization and Fluid Selection of Different Cogeneration of Heat and Power Systems Based on Organic Rankine Cycle," Energies, MDPI, vol. 14(16), pages 1-22, August.
    6. Lingen Chen & Chenqi Tang & Huijun Feng & Yanlin Ge, 2020. "Power, Efficiency, Power Density and Ecological Function Optimization for an Irreversible Modified Closed Variable-Temperature Reservoir Regenerative Brayton Cycle with One Isothermal Heating Process," Energies, MDPI, vol. 13(19), pages 1-23, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ares de Parga-Regalado, A.M. & Valencia-Ortega, G. & Barranco-Jiménez, M.A., 2023. "Thermo-economic optimization of irreversible Novikov power plant models including a proposal of dissipation cost," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 613(C).
    2. Pengchao Zang & Lingen Chen & Yanlin Ge, 2022. "Maximizing Efficient Power for an Irreversible Porous Medium Cycle with Nonlinear Variation of Working Fluid’s Specific Heat," Energies, MDPI, vol. 15(19), pages 1-12, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ahmadi, Mohammad H. & Amin Nabakhteh, Mohammad & Ahmadi, Mohammad-Ali & Pourfayaz, Fathollah & Bidi, Mokhtar, 2017. "Investigation and optimization of performance of nano-scale Stirling refrigerator using working fluid as Maxwell–Boltzmann gases," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 337-350.
    2. Pengchao Zang & Lingen Chen & Yanlin Ge, 2022. "Maximizing Efficient Power for an Irreversible Porous Medium Cycle with Nonlinear Variation of Working Fluid’s Specific Heat," Energies, MDPI, vol. 15(19), pages 1-12, September.
    3. Chen, Lingen & Liu, Xiaowei & Wu, Feng & Xia, Shaojun & Feng, Huijun, 2020. "Exergy-based ecological optimization of an irreversible quantum Carnot heat pump with harmonic oscillators," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
    4. Wang, Junyi & Wang, Yuan & Su, Shanhe & Chen, Jincan, 2017. "Simulation design and performance evaluation of a thermoelectric refrigerator with inhomogeneously-doped nanomaterials," Energy, Elsevier, vol. 121(C), pages 427-432.
    5. Yin, Yong & Chen, Lingen & Wu, Feng, 2018. "Performance of quantum Stirling heat engine with numerous copies of extreme relativistic particles confined in 1D potential well," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 58-70.
    6. Meng, Fankai & Chen, Lingen & Feng, Yuanli & Xiong, Bing, 2017. "Thermoelectric generator for industrial gas phase waste heat recovery," Energy, Elsevier, vol. 135(C), pages 83-90.
    7. Ge, Ya & Liu, Zhichun & Sun, Henan & Liu, Wei, 2018. "Optimal design of a segmented thermoelectric generator based on three-dimensional numerical simulation and multi-objective genetic algorithm," Energy, Elsevier, vol. 147(C), pages 1060-1069.
    8. Hongkun Lv & Guoneng Li & Youqu Zheng & Jiangen Hu & Jian Li, 2018. "Compact Water-Cooled Thermoelectric Generator (TEG) Based on a Portable Gas Stove," Energies, MDPI, vol. 11(9), pages 1-19, August.
    9. Chen, J.F. & Zhang, L. & Dai, Y.J., 2018. "Performance analysis and multi-objective optimization of a hybrid photovoltaic/thermal collector for domestic hot water application," Energy, Elsevier, vol. 143(C), pages 500-516.
    10. Chen, Lingen & Liu, Xiaowei & Ge, Yanlin & Wu, Feng & Feng, Huijun & Xia, Shaojun, 2020. "Power and efficiency optimization of an irreversible quantum Carnot heat engine working with harmonic oscillators," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 550(C).
    11. Yin, Qian & Du, Wen-Jing & Cheng, Lin, 2017. "Optimization design of heat recovery systems on rotary kilns using genetic algorithms," Applied Energy, Elsevier, vol. 202(C), pages 153-168.
    12. Humberto Verdejo & Rodrigo Torres & Victor Pino & Wolfgang Kliemann & Cristhian Becker & José Delpiano, 2019. "Tuning of Controllers in Power Systems Using a Heuristic-Stochastic Approach," Energies, MDPI, vol. 12(12), pages 1-25, June.
    13. Du, Jianying & Fu, Tong & Hu, Cong & Su, Shanhe & Chen, Jincan, 2020. "Entropy analyses of electronic devices with different energy selective electron tunnels," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 560(C).
    14. Li, Guoneng & Zheng, Youqu & Hu, Jiangen & Guo, Wenwen, 2019. "Experiments and a simplified theoretical model for a water-cooled, stove-powered thermoelectric generator," Energy, Elsevier, vol. 185(C), pages 437-448.
    15. Lingen Chen & Chenqi Tang & Huijun Feng & Yanlin Ge, 2020. "Power, Efficiency, Power Density and Ecological Function Optimization for an Irreversible Modified Closed Variable-Temperature Reservoir Regenerative Brayton Cycle with One Isothermal Heating Process," Energies, MDPI, vol. 13(19), pages 1-23, October.
    16. Zhang, Lei & Chen, Lingen & Sun, Fengrui, 2016. "Power optimization of chemically driven heat engine based on first and second order reaction kinetic theory and probability theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 445(C), pages 221-230.
    17. Cicconi, Paolo & Landi, Daniele & Germani, Michele & Russo, Anna Costanza, 2017. "A support approach for the conceptual design of energy-efficient cooker hoods," Applied Energy, Elsevier, vol. 206(C), pages 222-239.
    18. Yin, Yong & Chen, Lingen & Wu, Feng & Ge, Yanlin, 2020. "Work output and thermal efficiency of an endoreversible entangled quantum Stirling engine with one dimensional isotropic Heisenberg model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 547(C).
    19. Tang, Wei & Feng, Huijun & Chen, Lingen & Xie, Zhuojun & Shi, Junchao, 2021. "Constructal design for a boiler economizer," Energy, Elsevier, vol. 223(C).
    20. Yang, Fusheng & Wu, Zhen & Liu, Shengzhe & Zhang, Yang & Wang, Geoff & Zhang, Zaoxiao & Wang, Yuqi, 2018. "Theoretical formulation and performance analysis of a novel hydride heat Pump(HHP) integrated heat recovery system," Energy, Elsevier, vol. 163(C), pages 208-220.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:15:y:2022:i:16:p:5864-:d:887006. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.