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Improvement and optimization of a combined biomass-feed plant for power and hydrogen production

  • Tao Hai
  • , Hasan Sh Majdi
  • , Jincheng Zhou
  • , E. Solomin
  • , N. Sinaga
  • , C. Diyoke
  • Qiannan Normal College for Nationalities
  • Guizhou University
  • Al-Mustaqbal University College
  • Key Laboratory of Complex Systems and Intelligent Optimization of Guizhou Province
  • South Ural State University
  • Universitas Diponegoro
  • Enugu State University of Science and Technology, Enugu

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Climatic changes, exhaustion of resources, air and water pollution are the detrimental consequences of mismanaging the use of fossil fuels. Likewise, the low performance of the traditional energy-conversion plants encourages scientists to replace these plants with hybrid systems. Accordingly, this study suggests a biomass-based combined system encompassing a gasifier, a gas turbine, a S–CO2 unit, along with a hot water heater. This system will be analyzed from exergy, and economic point of view also using the genetic algorithm optimization tool multi-objective optimization is carried out. The parametric analysis to evaluate the influences of various variables on the plant operation. It was found that the changing rp of the compressor have a small impact on the efficiencies while it increases the total exergy efficiency and cost. The largest exergy destruction rate of the plant was for the compressor unit with 7391 kW. After that the combustion chamber with 2124 kW represents the worst performance from exergy destruction rate point of view. The optimization is done according to five decision parameters of moisture content, compressor pressure ratio, T9, T14, and P36. The objective functions were energy efficiency, exergy destruction rate, and total product cost rate. According to the results of multi-aspect optimization in the optimum point the energy efficiency, exergy destruction and cost of electricity are 33.44%, 12448.1 kw and 130.57 $/h, respectively.

Original languageEnglish
Pages (from-to)1437-1455
Number of pages19
JournalInternational Journal of Hydrogen Energy
Volume51
DOIs
StatePublished - 2 Jan 2024
Externally publishedYes

UN SDGs

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

  1. SDG 6 - Clean Water and Sanitation
    SDG 6 Clean Water and Sanitation
  2. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Biomass
  • Genetic algorithm
  • Optimum state
  • Thermodynamic analysis

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