Computational intelligence approach formodeling hydrogen production: A review

Sina Faizollahzadeh Ardabili, Bahman Najafi, Shahaboddin Shamshirband, Behrouz Minaei Bidgoli, Ravinesh Chand Deo, Kwok Wing Chau

Research output: Journal article publicationJournal articleAcademic researchpeer-review

140 Citations (Scopus)

Abstract

Hydrogen is a clean energy source with a relatively low pollution footprint. However, hydrogen does not exist in nature as a separate element but only incompoundforms. Hydrogen is produced through a process that dissociates it from its compounds. Several methods are used for hydrogen production, which first of all differ in the energy used in this process. Investigating the viability and exact applicability of a method in a specific context requires accurate knowledge of the parameters involved in the method and the interaction between these parameters. This can be done using top-down models relying on complex mathematically driven equations. However, with the raise of computational intelligence (CI) and machine learning techniques, researchers in hydrology have increasingly been using these methods for this complex task and report promising results. The contribution of this study is to investigate the state of the art CI methods employed in hydrogen production, and to identify the CI method(s) that perform better in the prediction, assessment and optimization tasks related to different types of Hydrogen production methods. The resulting analysis provides in-depth insight into the different hydrogen production methods, modeling technique and the obtained results from various scenarios, integrating them within the framework of a common discussion and evaluation paper. The identified methods were benchmarked by a qualitative analysis of the accuracy of CI in modeling hydrogen production, providing extensive overview of its usage to empower renewable energy utilization.

Original languageEnglish
Pages (from-to)438-458
Number of pages21
JournalEngineering Applications of Computational Fluid Mechanics
Volume12
Issue number1
DOIs
Publication statusPublished - 1 Jan 2018

Keywords

  • Alternative fuels
  • Computational intelligent
  • Hydrogen production
  • Modeling

ASJC Scopus subject areas

  • Computer Science(all)
  • Modelling and Simulation

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