Optimization of hydrogen production by using genetic algorithm
DOI:
https://doi.org/10.14808/sci.plena.2016.054205Keywords:
Steam reforming, CFD, Genetic AlgorithmAbstract
The research for new alternatives and energy generating processes has become crucial to understand the global demand for sustainable and less aggressive energy sources to the environment. Facing these facts, the production of hydrogen becomes a viable alternative, since it is considered a clean and high density energy fuel. The main industrial route for obtaining hydrogen is the steam methane reforming. This is an endothermic process, in which methane reacts with steam at high temperature and pressure conditions to yield hydrogen. Recently, advances in modeling and simulation field, especially applying computational fluid dynamics technique, is aiding in the investigation and optimization of these processes, with low expenses. In this context, this study aimed to simulate a reactor with membrane by applying commercial software, in order to perform the optimization of its operational conditions. The Genetic Algorithm (GA) was applied in order to maximize the productivity of the process. Simulated profiles of the reactor for the conversion of methane and hydrogen recovery were obtained reaching values of 100%, which proves the effectiveness of the methodology presented for optimizing the main process variables.
Downloads
Published
How to Cite
Issue
Section
License
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work