Vortex flow plasma reforming for hydrogen production from atomized water-methanol mixture and parameter optimization using RSM and ANN-GA

Neeraj Budhraja, Amit Pal and R.S. Mishra

Renewable Energy, 2025, vol. 247, issue C

Abstract: Hydrogen energy is the cleanest energy. It has many applications in different sectors, such as power generation, industrial, and transportation. The conventional H2 production methods are energy-consuming and generate a huge amount of pollution. Hence, a non-polluting method for H2 production is necessary to utilize the benefit of cleaner fuel. The current work used a vortex flow plasma reforming process to generate H2 from the methanol-water mixture. The process involved plasmolysis of methanol-water mixture to produce H2. Additionally, the process parameters like feed flow rate (0.5–4.5 LPM), methanol concentration (5–35 %) and voltage (4–8 V) were optimized using RSM and ANN-GA models, and the influencing parameters were determined using the ANOVA test. The results showed an optimal hydrogen production rate of 229.2 mol/day (for 0.3 MHz), 265.0 mol/day (for 1.7 MHz) and 285.8 mol/day (for 2.4 MHz) for RSM at 4.5 LPM and 35 % methanol concentration while 267.0 mol/day for ANN-GA at 4.5 LPM, 33.8 % methanol concentration and 7.4 kV input voltage. The optimized parameters were used in the experimental setup, and an error of 4–7 % was observed for the RSM model and 2.5 % for the ANN-GA model. Therefore, the ANN-GA model showed better reliability than the RSM model. Further, the results may be used for commercial-scale H2 production for various applications.

Keywords: Plasma reforming; Feed flow rate; Hydrogen production rate; Response surface methodology; Artificial neural network-genetic algorithm (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:247:y:2025:i:c:s0960148125006883

DOI: 10.1016/j.renene.2025.123026

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