Comprehensive Exergoeconomic Analysis and Optimization of a Novel Zero- Carbon-Emission Multi-Generation System based on Carbon Dioxide Cycle

  • SUN Yan ,
  • LI Hongwei ,
  • WANG Di ,
  • DU Changhe
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  • 1. School of Energy and Power Engineering, Northeast Electric Power University, Jilin 132012, China
    2. School of Automation Engineering, Northeast Electric Power University, Jilin 132012, China
    3. Xi’an Institute of Electromechanical Information Technology, Xi’an 710065, China

网络出版日期: 2024-04-30

基金资助

The authors gratefully acknowledge financial support from the Jilin provincial Development and Reform Commission (No. 2023C032-7), Science Foundation of Jilin province Science and Technology Agency (No. 20210203057SF), Science and Technology Development Program of Jilin province Science and Technology Agency (No. 20230101211JC).

版权

Science Press, Institute of Engineering Thermophysics, CAS and Springer-Verlag GmbH Germany, part of Springer Nature 2024

Comprehensive Exergoeconomic Analysis and Optimization of a Novel Zero- Carbon-Emission Multi-Generation System based on Carbon Dioxide Cycle

  • SUN Yan ,
  • LI Hongwei ,
  • WANG Di ,
  • DU Changhe
Expand
  • 1. School of Energy and Power Engineering, Northeast Electric Power University, Jilin 132012, China
    2. School of Automation Engineering, Northeast Electric Power University, Jilin 132012, China
    3. Xi’an Institute of Electromechanical Information Technology, Xi’an 710065, China

Online published: 2024-04-30

Supported by

The authors gratefully acknowledge financial support from the Jilin provincial Development and Reform Commission (No. 2023C032-7), Science Foundation of Jilin province Science and Technology Agency (No. 20210203057SF), Science and Technology Development Program of Jilin province Science and Technology Agency (No. 20230101211JC).

Copyright

Science Press, Institute of Engineering Thermophysics, CAS and Springer-Verlag GmbH Germany, part of Springer Nature 2024

摘要

本文旨在对一种新型零碳的联产系统进行全面的火用经济性分析,并提出一种结合机器学习的快速优化方法。本文对一种新型的电、冷和淡水联产系统进行了详细的火用经济性分析。运用火用流理论建立了火用经济分析模型,进行了全面的能量分析、火用分析、火用经济性分析和环境分析。研究了5个关键决策变量对该系统火用经济性的影响。提出了一种结合遗传算法和装袋神经网络的快速优化方法。将该系统与4个相似案例进行了先进性比较。结果表明,提高透平入口温度可以提高火用效率,降低总产品单位成本。该系统的火用破坏直接决定了系统的火用效率和总火用破坏成本率。在成本优化设计案例中,总产品单位成本分别比火用效率优化设计案例和基本设计案例降低7.7%和25%。与4个相似案例相比,该系统在热力学性能和火用经济性能方面具有较好的优势。本研究能够为多联产系统的性能分析和快速优化提供研究方法和思路。

本文引用格式

SUN Yan , LI Hongwei , WANG Di , DU Changhe . Comprehensive Exergoeconomic Analysis and Optimization of a Novel Zero- Carbon-Emission Multi-Generation System based on Carbon Dioxide Cycle[J]. 热科学学报, 2024 , 33(3) : 1065 -1081 . DOI: 10.1007/s11630-024-1927-y

Abstract

This paper aims to conduct a comprehensive exergoeconomic analysis of a novel zero-carbon-emission multi-generation system and propose a fast optimization method combined with machine learning. The detailed exergoeconomic analysis of a novel combined power, freshwater and cooling multi-generation system is performed in this study. The exergoeconomic analysis model is established by exergy flow theory. A comprehensive exergy, exergoeconomic and environmental analysis is carried out. Five critical decision variables are researched to bring out effects on the multi-generation system exergoeconomic performance. A novel fast optimization method combining genetic algorithm and Bagging neural network is proposed. The advanced nature comparison is made between the proposed system and four similar cases. Results display that increasing the turbine inlet temperature can improve exergy efficiency and decrease the total product unit cost. The multi-generation system exergy destruction directly determines exergy efficiency and total exergy destruction cost rate. The total product unit cost in the cost optimal design case is reduced by 7.7% and 25%, respectively, compared with exergy efficiency optimal design case and basic design case. Compared with four similar cases, the proposed multi-generation system has great advantages in thermodynamic performance and exergoeconomic performance. This paper can provide research methods and ideas for performance analysis and fast optimization of multi-generation system.

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