Hydrogen energy deployment in decarbonizing transportation sector using multi-supply-demand integrated scenario analysis with nonlinear programming — A Shanxi case study. (22nd May 2022)

• Record Type: Journal Article
• Authors: Zhao, Ying-jie; Liu, Qian; Duan, Yuan-yuan; Zhang, Yu-ke; Cui, Yang; Huang, Yi; Gao, Dan; Shi, Li-juan; Wang, Jian-cheng; Yi, Qun
• Is Part Of: International journal of hydrogen energy. Volume 47:Number 44(2022)
• Page Start: 19338
• Page End: 19352
• Publication Date: 2022-05-22
• Subjects: Hydrogen energy -- Decarbonization -- Transportation sector -- Nonlinear programming -- CO2 emission; Hydrogen as fuel -- Periodicals; Hydrogène (Combustible) -- Périodiques; Hydrogen as fuel; Periodicals; 665.81
• DOI: 10.1016/j.ijhydene.2022.04.102
• Languages: English
• ISSNs: 0360-3199

Abstract

Abstract: Peaking CO2 emissions and reaching carbon neutrality create a major role for hydrogen in the transportation field where decarbonization is difficult. Shanxi, as a microcosm of China in the systematic transformation of energy end-use consumption, is selected to investigate the hydrogen energy development forecast for decarbonization in the transportation sector. Multi-supply-demand integrated scenario analysis with nonlinear programming (NLP) model is established to analyze hydrogen energy deployment in varied periods and regions under minimum environmental, energy and economic objectives, to obtain CO2 emission reduction potential. Results reveal that green hydrogen contributes most to low-carbon hydrogen development strategies. In high-hydrogen demand scenarios, carbon emission reduction potential is significantly higher under environmental objectives, estimated at 297.68 × 10 4 –848.12 × 10 4 tons (2025–2035). The work provides a strategy to forecast hydrogen energy deployment for transportation decarbonization, being of vital significant guide for planning of hydrogen energy transportation in other regions. Graphical abstract: Image 1 Highlights: Hydrogen energy deployment for transportation decarbonization of Shanxi is proposed. Multi-supply-demand integrated scenario analysis with NLP is used for H2 deployment. Optimization of H2 deployment of Shanxi's transport under different 3E objectives. CO2 reduction potential of Shanxi's transport within H2 deployment is analyzed.