MODELING AND OPTIMIZATION OF HYDROGEN PRODUCTION PLANT VIA ARTIFICIAL NEURAL NETWORK AND GENETIC ALGORITHM

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AKBARI I.; GHOREISHI M.; RAZAVI N.; GHOREISHI M.; VAFAEI JAHAN M.

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Journal: Journal of Applied Research in Chemistry Year:2014 | Volume:7 | Issue:4 Page(s): 5-15

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Title

MODELING AND OPTIMIZATION OF HYDROGEN PRODUCTION PLANT VIA ARTIFICIAL NEURAL NETWORK AND GENETIC ALGORITHM

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Keywords

HYDROGENQ2

STEAM METHANE REFORMINGQ2

MODELINGQ2

ARTIFICIAL NEURAL NETWORKQ1

OPTIMIZATIONQ2

GENETIC ALGORITHMQ2

Abstract

The main objective of this research was to model an industrial HYDROGEN plant based on STEAM METHANE REFORMING using ARTIFICIAL NEURAL NETWORK (ANN). Two different ANN networks were developed for prediction of HYDROGEN production rate and corresponding energy consumption using 20 operating parameters as inputs of both networks. The obtained ANN resuls indicated a very close compatibility with average absolute error, average relative error, and probable error of 2.14, 1.21, and 2.9 for HYDROGEN production, 0.37, 0.84 and 0.55 for energy consumption, respectively. Based on sensitivity analysis, temperature of synthesized gas from reformer was identified as the most important parameter influencing the HYDROGEN production, and energy consumption was affected the most by the tail gas flow rate. After ANN MODELING, GENETIC ALGORITHM (GA) was used to optimize plant operating conditions. In this regard, plant gross profit was considered as objective function and GA OPTIMIZATION resulted in the profit of $42.56/h which is 25% higher than actual average profit.

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APA: Copy

AKBARI, I., GHOREISHI, M., RAZAVI, N., GHOREISHI, M., & VAFAEI JAHAN, M.. (2014). MODELING AND OPTIMIZATION OF HYDROGEN PRODUCTION PLANT VIA ARTIFICIAL NEURAL NETWORK AND GENETIC ALGORITHM. JOURNAL OF APPLIED RESEARCHES IN CHEMISTRY (JARC), 7(4), 5-15. SID. https://sid.ir/paper/180032/en

Vancouver: Copy

AKBARI I., GHOREISHI M., RAZAVI N., GHOREISHI M., VAFAEI JAHAN M.. MODELING AND OPTIMIZATION OF HYDROGEN PRODUCTION PLANT VIA ARTIFICIAL NEURAL NETWORK AND GENETIC ALGORITHM. JOURNAL OF APPLIED RESEARCHES IN CHEMISTRY (JARC)[Internet]. 2014;7(4):5-15. Available from: https://sid.ir/paper/180032/en

IEEE: Copy

I. AKBARI, M. GHOREISHI, N. RAZAVI, M. GHOREISHI, and M. VAFAEI JAHAN, “MODELING AND OPTIMIZATION OF HYDROGEN PRODUCTION PLANT VIA ARTIFICIAL NEURAL NETWORK AND GENETIC ALGORITHM,” JOURNAL OF APPLIED RESEARCHES IN CHEMISTRY (JARC), vol. 7, no. 4, pp. 5–15, 2014, [Online]. Available: https://sid.ir/paper/180032/en

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