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Ecological function performance analysis and multi-objective optimization for an endoreversible four-reservoir chemical pump

Author

Listed:
  • Chen, Lingen
  • Shi, Shuangshuang
  • Ge, Yanlin
  • Feng, Huijun

Abstract

Ecological function (E1) based on energy analysis is introduced into endoreversible four-reservoir chemical pump model. Optimization relationship between E1 and coefficient of performance (χ) is obtained. Effects of energy distribution ratio (a) of working fluid, chemical potential ratios (μH/μM and μO/μL) of material reservoirs and mass transfer coefficient ratios (b1, b2 and b3) on the optimal E1 performance are analyzed. Using NSGA-Ⅱ, taking intermediate parameter k (k=1−μ1/μH, where μ1 is chemical potentials of working fluid corresponding to reservoir μH) as optimization variable, and taking χ, dimensionless rate of energy pumping (Σ*), dimensionless E1 (E1*) and dimensionless entropy generation rate (σ*) as objective functions, multi-objective optimization (MOO) is performed, and Pareto frontiers under different optimization schemes are obtained. Deviation indices (D s) are introduced to compare the results of different MOO combinations with three decision-making methods. Trend of E1*−χ is parabolic-like one, there is an optimal χ (χE1*) to maximize E1* (E1max*); When a and μH/μM increase or μO/μL decreases, χE1* increases and E1max* decreases; When b1, b2 and b3 increase, E1max* decreases; When two-objective (σ* and E1*) optimization is carried out, the smallest D (0.3214) is obtained by TOPSIS. MOO can better balance the contradictory relationship of cycle performance parameters and improve the comprehensive performance of chemical pump.

Suggested Citation

  • Chen, Lingen & Shi, Shuangshuang & Ge, Yanlin & Feng, Huijun, 2023. "Ecological function performance analysis and multi-objective optimization for an endoreversible four-reservoir chemical pump," Energy, Elsevier, vol. 282(C).
    • Handle: RePEc:eee:energy:v:282:y:2023:i:c:s0360544223021114
    DOI: 10.1016/j.energy.2023.128717
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    References listed on IDEAS

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    Cited by:

    1. Ma, Haiwen & Liu, Peng & Huang, Lu & Ren, Tingting & Ge, Yanlin & Chen, Lingen, 2024. "Heat transfer enhancement in parabolic trough receiver based on exergy destruction minimization," Energy, Elsevier, vol. 313(C).
    2. Su, Yiwen & Chen, Lingen & Ge, Yanlin & Shi, Shuangshuang & Feng, Huijun, 2025. "Efficient-ecological-function analyses and multi-objective optimizations for generalized irreversible Carnot heat pumps," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 679(C).
    3. Chen, Lingen & Shi, Shuangshuang & Ge, Yanlin & Feng, Huijun, 2023. "Power density performances and multi-objective optimizations for an irreversible Otto cycle with five specific heat models of working fluid," Energy, Elsevier, vol. 282(C).
    4. Yin, Yong & Fang, Xinting & Chen, Lingen & Ge, Yanlin, 2025. "Optimal performance of irreversible quantum Stirling refrigerator with extreme relativistic particles as working substance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 664(C).
    5. Qi, Congzheng & Chen, Lingen & Ge, Yanlin & Feng, Huijun, 2024. "Equivalent combined cycle modeling and performance optimization for a three-heat-reservoir thermal Brownian heat transformer with external heat-transfer," Energy, Elsevier, vol. 313(C).
    6. Xue, Xiaoqing & Ge, Yanlin & Chen, Lingen & Feng, Huijun & Zhang, Jiwen, 2025. "Finite-time thermodynamic modeling, analysis and four-objective optimizations for Rallis cycle with NSGA-II and multiple decision-making methods," Energy, Elsevier, vol. 334(C).
    7. Li, Wanfeng & Chen, Lingen & Ge, Yanlin & Feng, Huijun, 2025. "Efficient power performance analyses and multi-objective optimizations for closed regenerative gas turbine cycle based on five objectives and NSGA-II," Energy, Elsevier, vol. 329(C).
    8. Zhu, Huichao & Zhao, Pan & Ma, Ning & Shi, Zhaochun & Xue, Weihan & Wang, Jiangfeng, 2025. "A novel electro-thermal-storage system for multi-energy supply and peak shaving in off-grid areas: A theoretical design, optimization and off-design study," Energy, Elsevier, vol. 336(C).

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