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Process Parameter Optimization via RSM of a PEM based Water Electrolysis Cell for the Production of Green Hydrogen

  • P Bhavya Teja Reddy (Department of Chemical Engineering and Technology, Indian Institute of Technology (Banaras Hindu University)) ;
  • Hiralal Pramanik (Department of Chemical Engineering and Technology, Indian Institute of Technology (Banaras Hindu University))
  • 투고 : 2023.12.18
  • 심사 : 2024.03.15
  • 발행 : 2024.08.31

초록

In the present work, the operating parameters were optimized using Box Behnken Design (BBD) in response surface methodology (RSM) to maximize the hydrogen production rate (R1) and hydrogen production rate per unit watt consumed (R2) of a proton exchange membrane electrolysis cell (PEMEC), a third response (R3) which was the sum of the scaled values of R1 and R2 were selected to be maximized so that both hydrogen production rate and hydrogen production rate per unit watt consumed could be maximized. The major parameters which were influencing the experiment for enhancing the output responses were oxygen electrode/anode electrocatalyst loading (A), current supplied (B) and water inlet temperature (C). The commercial proton exchange membrane Nafion® was used as the electrolyte. The acetylene black carbon (CAB) supported IrO2 was used as the electrocatalyst for preparing oxygen electrode/anode whereas commercial Pt (40 wt%)/CHSA was used as the H2 electrode/cathode electrocatalyst. The quadratic model was developed to predict the output/ responses and their proximity to the experimental output values. The developed model was found to be significant as the P values for both the responses were < 0.0001 and F values were greater than 1. The optimum condition for both the responses were O2 electrode/anode electrocatalyst loading of 1.78 mg/cm2, supplied current of 0.33 A and water inlet temperature of 54℃. The predicted values for hydrogen production rate (R1) and hydrogen production rate per unit watt consumed (R2) were 2.921 mL/min and 2.562 mL/(min·W), respectively obtained from the quadratic model. The error % between the predicted response values and experimental values were 1.47% and 3.08% for R1 and R2, respectively. This model predicted the optimum conditions reasonably in good agreement with the experimental conditions for the enhancement of the output responses of the developed PEM based electrolyser.

키워드

과제정보

The authors acknowledge financial support by the Science and Engineering Research Board (Sanction order No. EEQ/2018/000246 dated 26.02.2019), Govt. of India.

참고문헌

  1. T. R. Anderson, E. Hawkins, and P. D. Jones, Endeavour, 2016, 40(3), 178-187.
  2. S. Shafiee and E. Topal, Energy Policy, 2009, 37(1), 181-189.
  3. N. Z. Muradov and T. N. Veziroglu, Int. J. Hydrogen Energy, 2005, 30(3), 225-237.
  4. A. M. Abdalla, S. Hossain, O. B. Nisfindy, A. T. Azad, M. Dawood, and A. K. Azad. Energy Convers. Manag., 2018, 165, 602-627.
  5. S. S. Kumar and V. Himabindu, Mater. Sci. Energy Technol., 2019, 2(3), 442-454.
  6. Z. Chen, X. Wang, C. Liu, L. Gu, L. Yin, C. Xu, Z. Liao, and Z. Wang, Int. J. Hydrogen Energy, 2022, 47(78), 33177-33194.
  7. S. Zhigang, Y. Baolian, and H. Ming, J Power Sources, 1999, 79(1), 82-85.
  8. J. Ahn and R. Holze, J. Appl. Electrochem., 1992, 22, 1167-1174.
  9. E. Antolini, Acs Catal., 2014, 4(5), 1426-1440.
  10. H.-Y. Jung, P. Ganesan, and B. Popov, ECS Trans., 2009, 25, 1261-1269.
  11. M.-T. Lin, C.-H. Wan, and W. Wu, Thin Solid Films, 2013, 544, 162-169.
  12. J. Peron, A. Mani, X. Zhao, D. Edwards, M. Adachi, T. Soboleva, Z. Shi, Z. Xie, T. Navessin, and S. Holdcroft, J. Membr. Sci., 2010, 356(1-2), 44-51.
  13. T. V. Nguyen and R. E. White, J. Electrochem. Soc., 1993, 140(8), 2178.
  14. J. Zhang, H. Zhang, J. Wu, and J. Zhang, Chapter 4 - The effects of temperature on PEM fuel cell kinetics and performance. In: Pem Fuel Cell Testing and Diagnosis, Elsevier, Amsterdam, 2013, 121-124.
  15. K. Darowicki and J. Orlikowski, J. Electrochem. Soc., 1999, 146(2), 663.
  16. W.-M. Yan, C.-Y. Chen, S.-C. Mei, C.-Y. Soong, and F. Chen, J. Power Sources, 2006, 162(2), 1157-1164.
  17. A. Caglar, T. Sahan, M. S. Cogenli, A. B. Yurtcan, N. Aktas, and H. Kivrak, Int. J. Hydrogen Energy, 2018, 43(24), 11002-11011.
  18. S. Toghyani, S. Fakhradini, E. Afshari, E. Baniasadi, M. Y. Jamalabadi, and M. S. Shadloo, Int. J. Hydrogen Energy, 2019, 44(13), 6403-6414.
  19. A. Verma, S. Sharma, and H. Pramanik, Arab. J. Sci. Eng., 2023, 48, 16527-16542.
  20. E. E. Kahveci and I. Taymaz, Int. J. Hydrogen Energy, 2022, 47(24), 12293-12303.
  21. M. Makela, Energy Convers. Manag., 2017, 151, 630-640.
  22. R. H. Myers, D. C. Montgomery, and C. M. Anderson-Cook, Response surface methodology, process and product optimization using designed experiments, John Wiley & Sons, 2016.
  23. G. Karanfil, Int. J. Energy Res., 2020, 44(1), 4-25.
  24. D. Bas and I. H. Boyaci, J. Food Eng., 2007, 78(3), 836-845.
  25. J. G. Carton and A. G. Olabi, Energy, 2010, 35(7), 2796-806.
  26. I. Taymaz, F. Akgun, and M. Benli, Energy, 2011, 36(2), 1155-1160.
  27. V. B. Silvia and A. Rouboa, Appl. Math. Comp., 2012, 218(12), 6733-6743.
  28. H. Kanani, M. Shams, M. Hasheminasab, and A. Bozorgnezhad, Energy Convers. Manag., 2015, 93, 9-22.
  29. D. S. Falcao and A. M. F. R. Pinto, J. Clean. Prod., 2020, 261, 121184.
  30. D. Panjiara and H. Pramanik, Int. J. Hydrogen Energy, 2020, 45(58), 33968-33979.
  31. A. K. Choudhary and H. Pramanik, Int. J. Energy Res., 2021, 45(14), 20413-20429.
  32. S. N. Ozdemir, I. Taymaz, E. Okumus, F. G. B. San, and F. Akgun, Int. J. Green Energy, 2023, 20(15), 1861-1872.
  33. Y. Zhang, C. Wang, N. Wan, and Z. Mao, Int. J. Hydrogen Energy, 2007, 32(3), 400-404.
  34. S. Altmann, T. Kaz, and K. A. Friedrich, Electrochim. Acta, 2011, 56(11), 4287-4293.
  35. N. K. Yadav and H. Pramanik, Int. J. Hydrogen Energy, 2023, 50, 1373-1394.
  36. S. L. C. Ferreira, R. E. Bruns, H. S. Ferreira, G. D. Matos, J. M. David, G. C. Brandao, E. G. P. da Silva, L. A. Portugal, P. S. dos Reis, A. S. Souza, and W. N. L. dos Santos, Anal. Chim. Acta, 2007, 597(2), 179-186.
  37. C. Ogbonnaya, C. Abeykoon, A. Nasser, and A. Turan, Clean. Eng. Technol., 2021, 4, 100241.
  38. M. N. Roudbari, R. Ojani, and J. B. Raoof, Energy, 2019, 173, 151-161.
  39. S. Barati, M. M. Ghazi, and B. Khoshandam, Korean J. Chem. Eng., 2019, 36, 146-156.
  40. J. C. Garcia-Navarro, M. Schulze, and K. A. Friedrich, J. Power Sources, 2019, 431, 189-204.
  41. H. Ito, N. Miyazaki, M. Ishida, and A. Nakano, Int. J. Hydrogen Energy, 2016, 41(45), 20439-20446.
  42. S. A. Grigoriev, V. I. Porembskiy, S. V. Korobtsev, V. N. Fateev, F. Aupretre, and P. Millet, Int. J. Hydrogen Energy, 2011, 36(3), 2721-2728.
  43. R. Omrani and B. Shabani, Electrochim. Acta, 2021, 377, 138085.
  44. M. Cappadonia, J. W. Erning, and U. Stimming, J. Electroanal. Chem., 1994, 376(1-2), 189-193.
  45. P. D. Beattie, V. I. Basura, and S. Holdcroft, J. Electroanal. Chem., 1999, 468(2), 180-192.
  46. K.-H. Choi, D.-H. Peck, C. S. Kim, D.-R. Shin, and T.-H. Lee, J. Power Sources, 2000, 86(1-2), 197-201.
  47. G. Zhang and K. Jiao, J Power Sources, 2018, 391, 120-133.
  48. A. C. Fernandes and E. A. Ticianelli, J. Power Sources, 2019, 193(2), 547-554.
  49. L. Peng and Z. Wei, Engineering, 2020, 6(6), 653-679.
  50. D. Qiu, L. Peng, S. Shen, and X. Lai, Energy Convers. Manag., 2022, 254, 115210.
  51. T. Lochner, R. M. Kluge, J. Fichtner, H. A. El-Sayed, B. Garlyyev, and A. S. Bandarenka, ChemElectroChem, 2020, 7(17), 3545-3568.
  52. W. Zheng, B. Lv, Z. Shao, B. Zhang, Z. Liu, J. Sun, J. Yuan, and C. Jiang, Int. J. Hydrogen Energy, 2024, 53, 1210-1225.
  53. X. Lu, B. Du, S. Zhou, W. Zhu, Y. Li, Y. Yang, C. Xie, B. Zhao, L. Zhang, J. Song, and Z. Deng, Int. J. Hydrogen Energy, 2023, 48(15), 5850-5872.
  54. H. Zhang, S. Su, G. Lin, and J. Chen, Int. J. Electrochem. Sci., 2012, 7(5), 4143-4157.
  55. X. Zhang, B. Wang, Y. Xu, L. Wu, F. Zhang, S. He, X. Zhang, and K. Jiao, Fuel, 2023, 332, 126090.