Qiuchi Wu / Nanjing Institute of Technology / ChinaZHU ZHENTAO / NANJING INSTITUTE OF TECHNOLOGY / CHINA
QU YAPAN / ZHEJIANG UNIVERSITY OF FINANCE & ECONOMICS / CHINA
TAN WENYI / NANJING INSTITUTE OF TECHNOLOGY / CHINA
ZHANG YAN / NANJING INSTITUTE OF TECHNOLOGY / CHINA
WU QIUCHI / NANJING INSTITUTE OF TECHNOLOGY / CHINA
DING WEN / NANJING INSTITUTE OF TECHNOLOGY / CHINA
The application of photovoltaic (PV) power to split water and to produce hydrogen can not only reduce the carbon emissions in the process of hydrogen production, but also can help decarbonize the transportation, chemical and metallurgical industries through P2X technology. It is a critical issue to establish a techno-economic model to predict the economics of the integrated PV-hydrogen technology at key time points in the future, based on the characteristics, the variability and the uncertainties of this technology. In this paper, the comprehensive technical factors (including PV tracking system coefficient, PV conversion efficiency, electrolyzer efficiency, electrolyzer degradation coefficient) of integrated PV-hydrogen system were extracted, and then a PV hydrogen production techno-economic model (PVH2 model) was constructed. The levelized cost of hydrogen production (LCOH) method was used to estimate the cost of each major equipment item during the project lifetime. The combination of PVH2 model and the learning curve model was to determine the cost trend of integrated PV-hydrogen technology. A twodimensional Monte Carlo approach was proposed to predict the variation interval of LCOH for PV-hydrogen projects in 2030 and 2050, which describes the current technology variability with variable parameters and the uncertainty of the technology advancement with uncertain parameters. The results show that the most critical factors influencing LCOH are PV conversion efficiency and capital cost of electrolyzer. The LCOH of PV to hydrogen in China will drop to CNY 16-32/kg by 2030 and CNY 8-18/kg by 2050, respectively. The combination of a learning curve model and a Monte Carlo method is an effective tool to describe the current variability in hydrogen production technologies and uncertainty in technological progress.Read more...