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Exergy, economic, and optimization of a clean hydrogen production system using waste heat of a steel production factory

  • Ma Shaofu
  • , Ehab Hussein Bani Hani
  • , Hai Tao
  • , Qiang Xu
  • Lanzhou City University
  • Australian College of Kuwait
  • Baoji University of Arts and Sciences
  • Universiti Teknologi MARA

Research output: Contribution to journalArticlepeer-review

22 Scopus citations

Abstract

In this present research study a multi-generation energy system which is coupled with CO2 capture unit which is based on Rankine cycle, organic Rankine cycle, ejector cooling system and absorption chiller has been analyzed via energy, exergy, exergy-economic aspects by developing MATLAB, also to achieve the optimum operating condition genetic algorithm has been applied for system optimization. The objective of this study is to propose an optimized efficient integrated energy system to recycle the energy waste of a typical industrial factory. The optimization has been illustrated on a Pareto frontier to achieve the optimum scheme of the multi-generation system regarding technical and economic viewpoints. Results indicate the optimal condition of this system has occurred at 0.37 exergy efficiency with 0.03 $/s. Furthermore, by surging the mass flow rate of waste gases up to 70 kg/s, net power output augmented up to 7500 kW. Besides, hydrogen production and produced desalinated water rise up to 8.5 g/s and 16 kg/s, respectively.

Original languageEnglish
Pages (from-to)26067-26081
Number of pages15
JournalInternational Journal of Hydrogen Energy
Volume47
Issue number62
DOIs
StatePublished - 22 Jul 2022
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy
  2. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure
  3. SDG 13 - Climate Action
    SDG 13 Climate Action

Keywords

  • Exergy economic optimization
  • Exergy efficiency
  • Genetic algorithm
  • Multi-generation energy system
  • Steel factory

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