Main content area

Deterministic and stochastic economic analysis based on historical natural gas and CO2 allowance prices for steam reforming of methanol

Heo, Juheon, Kim, Sehwa, Yeon, Wonmo, Lee, Hyunjun, Lee, Boreum, Lim, Hankwon
Energy conversion and management 2019 v.193 pp. 140-148
Monte Carlo method, adsorption, carbon dioxide, climate, economic feasibility, electrolytes, fuel cells, greenhouse gases, hydrogen, hydrogen production, methanol, natural gas, polymers, prices, steam, temperature, uncertainty analysis, Europe, Korean Peninsula
As an appropriate hydrogen supply system for high temperature polymer electrolyte membrane fuel cells, steam reforming of methanol (SRM) is proposed because reformate gas including low quality H2 with some impurities can be directly used as the fuel. In this study, we compare two SRM systems with and without the use of tail gas from pressure swing adsorption and comprehensive economic analysis is performed for the SRM process with the use of tail gas to estimate a unit H2 production cost (CUHP) based on historical data of natural gas and the CO2 allowance prices for Korea, Europe, Western Climate Initiative (WCI), and Regional Greenhouse Gas Initiative (RGGI). From deterministic economic analysis with a H2 production capacity of 700 m3 h−1, the CUHP values are 6.88 $ kgH2−1 for Korea, 6.84 $ kgH2−1 for Europe, 6.50 $ kgH2−1 for WCI, and 6.54 $ kgH2−1 for RGGI, respectively. Furthermore, additional two scenarios, pessimistic and optimistic ones (Scenario 1 and 2, respectively), are investigated to evaluate the current level of CUHP values for H2 production capacities from 30 to 700 m3 h−1. With a Monte-Carlo simulation method, stochastic economic analysis is carried out to predict the ranges of potential CUHP values for each region. The CUHP values for WCI and RGGI show the narrow distributions meaning lower change of CUHP; however, a wide range of distribution for Korea and Europe suggest that there is considerably higher variation, demonstrating the necessity of stochastic uncertainty analysis when assessing the economic feasibility.