Construction of Hydrogen Safety Evaluation Model Based on Analytic Hierarchy Process (AHP)

Jianlun Xu, Minghao Wang, Ping Guo

Abstract


With the large consumption of traditional primary energy, hydrogen as a clean and renewable energy has been widely studied by scholars around the world. Hydrogen is mainly used in hydrogen internal combustion engine and hydrogen fuel cell. Hydrogen internal combustion engine is the direct combustion of hydrogen as fuel, with the advantages of easy use. Alternatively, hydrogen fuel cell converts the chemical energy of hydrogen into electrical energy by electrochemical reaction, which has the advantages of high efficiency and zero pollution. Regardless of the use method, the safety of hydrogen use needs to be considered. However, in the whole life cycle of hydrogen, the process from hydrogen production to the use of hydrogen in automobiles is extremely complex. There are many factors affecting the safety of hydrogen use, and a single factor cannot be used as an evaluation. In order to make the evaluation of hydrogen safety more complete and accurate, the weight of four primary evaluation indexes and eight secondary evaluation indexes affecting hydrogen safety is determined by analytic hierarchy process, and a reliable hydrogen safety evaluation model is established.

Citation: Xu, J., Wang, M., and Guo, P. (2022). Construction of Hydrogen Safety Evaluation Model Based on Analytic Hierarchy Process (AHP). Trends in Renewable Energy, 8(2), 84-95. DOI: http://dx.doi.org/10.17737/tre.2022.8.2.00140


Keywords


Analytic Hierarchy Process (AHP); Multi-objective evaluation; Hydrogen safety grade; Hydrogen fuel cell; Alternative energy sources

Full Text:

FULL TEXT (PDF)

References


BP p.l.c. (2019). BP Statistical Review of World Energy 2019: an unsustainable path https://www.bp.com/en/global/corporate/news-and-insights/press-releases/bp-statistical-review-of-world-energy-2019.html (accessed on 3/22/2022)

Peng, L., Liu, F., Zhou, M., Li, M., Zhang, Q., and Denise, L. (2021). Alternative-energy-vehicles deployment delivers climate, air quality, and health co-benefits when coupled with decarbonizing power generation in China. One Earth, 4(08), 1127-1140. DOI: https://doi.org/10.1016/j.oneear.2021.07.007

Chen, Z., Zhang, T., Wang, X., Chen, H., Geng, L., and Zhang, T. (2021). A comparative study of combustion performance and emissions of dual-fuel engines fueled with natural gas/methanol and natural gas/gasoline. Energy, 237, 121586. DOI: https://doi.org/10.1016/j.energy.2021.121586

Karthikeyan, S., and Periyasamy, M. (2021). Impact on the power and performance of an internal combustion engine using hydrogen. Materials Today: Proceedings. DOI: https://doi.org/10.1016/j.matpr.2021.02.356

Gürsel, Ş., and Mert, A.Ö. (2022). Experimental and numerical study of energy and thermal management system for a hydrogen fuel cell-battery hybrid electric vehicle. Energy, 28(B), 121794. DOI: https://doi.org/10.1016/j.energy.2021.121794

Tang, Q., Yang, Y., Luo, C., Yang, Z., and Fu, C. (2022). A novel electro-hydraulic compound braking system coordinated control strategy for a four-wheel-drive pure electric vehicle driven by dual motors. Energy, 241, 122750. DOI: https://doi.org/10.1016/j.energy.2021.122750

Nuthan Prasad, B. S., Pandey, J. K., and Kumar, G. N. (2020). Impact of changing compression ratio on engine characteristics of an SI engine fueled with equi-volume blend of methanol and gasoline. Energy, 191, 116605. DOI: https://doi.org/10.1016/j.energy.2019.116605

Verma, A., Dugala, N. S., and Singh, S. (2022). Experimental investigations on the performance of SI engine with Ethanol-Premium gasoline blends. Materials Today: Proceedings, 48, 1224-1231. DOI: https://doi.org/10.1016/j.matpr.2021.08.255

Qin, G., Zhang, M., Yan, Q., Xu, C., and Daniel, M.K. (2021). Comprehensive evaluation of regional energy internet using a fuzzy analytic hierarchy process based on cloud model: A case in China. Energy, 228, 120569. DOI: https://doi.org/10.1016/j.energy.2021.120569

Nachiappan, S. and Ramakrishnan, R. (2012). A review of applications of Analytic Hierarchy Process in operations management. International Journal of Production Economics, 138(2): 215-241. DOI: https://doi.org/10.1016/j.ijpe.2012.03.036

Zhang, C., Sung-Kwun, O., and Fu, Z. (2021). Hierarchical polynomial-based fuzzy neural networks driven with the aid of hybrid network architecture and ranking-based neuron selection strategies. Applied Soft Computing, 113(B), 107865. DOI: https://doi.org/10.1016/j.asoc.2021.107865

Gan, Y., Meng, B., Chen, Y., and Sun, F. (2022). An intelligent measurement method of the resonant frequency of ultrasonic scalpel transducers based on PSO-BP neural network. Measurement, 190, 110680. DOI: https://doi.org/10.1016/j.measurement.2021.110680

Zheng, Y., and Wang, D. (2022). A survey of recommender systems with multi-objective optimization. Neurocomputing, 474, 141-153.

Grošelj, P. (2021). Symmetric projection group approach for promoting homogeneity in the analytic hierarchy process. Computers & Operations Research, 133, 105343. DOI: https://doi.org/10.1016/j.cor.2021.105343

Havle, C.A. and Kılıç, B. (2019). A hybrid approach based on the fuzzy AHP and HFACS framework for identifying and analyzing gross navigation errors during transatlantic flights. Journal of Air Transport Management, 76, 21-30. DOI: https://doi.org/10.1016/j.jairtraman.2019.02.005.

Hassan, I.A., Haitham, S.R, Mohamed, A.S., and Daniel, H. (2021). Hydrogen storage technologies for stationary and mobile applications: Review, analysis and perspectives. Renewable and Sustainable Energy Reviews, 149, 111311. DOI: https://doi.org/10.1016/j.rser.2021.111311.

Jeffrey, V., Lim, F., Liu, L., Sonia, J., Zhou, Q., Ruth, K., Zhang, M., Li, H., Dong, F., Matthew, S.D., and Andrej, A. (2020). Hydrogen embrittlement of an automotive 1700 MPa martensitic advanced high-strength steel. Corrosion Science, 171, 108726. DOI: https://doi.org/10.1016/j.corsci.2020.108726.




DOI: http://dx.doi.org/10.17737/tre.2022.8.2.00140

Refbacks

  • There are currently no refbacks.


Copyright (c) 2022 Jianlun Xu, Minghao Wang, Ping Guo

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Creative Commons License This work is licensed under a Creative Commons Attribution 4.0 License.
Copyright @2014-2025 Trends in Renewable Energy (ISSN: 2376-2136, online ISSN: 2376-2144)