Hydrogen is generally considered as one of the potential fuels of the future transportation. However the high production cost has remained a barrier that is yet to be overcome. There are various H2 production routes based on thermo-chemical, electrolytic and biological processes. These include steam methane reforming (SMR), coal gasification (CG), biomass gasification (BG) and water electrolysis (WE). Within the context of H2 production, while SMR, CG and WE are commercially available, BG is still in the development/demonstration stage (Ball and Wietschel, 2009).
While SMR is currently the cheapest production technology, all these technologies are characteristically different in their cost foot-print. For instance, gasification can be twice as much capital intensive as reforming technology (NAE, 2004). On the other hand, the common feed-stocks used in gasification (i.e., coal and biomass) are usually less expensive than the feed-stock (i.e., natural gas, NG) used in SMR. Since the total production cost depends on both the capital investment and the price of raw-materials, the actual production cost in the future depends on the technological advancements and the future feed-stock price. While both the technological advancements and the feed-stock prices in future are uncertain, a recent study by Kramer and co-workers (Schoots, et al., 2008) has concluded, based on an extensive historical data since 1940, that the cost reduction potential on the basis of technology learning for SMR, CG and WE is limited. While they did not rule out the possibility of potential to reduce the electrolytic H2 production costs due to technological advancements (such as PEM-based electrolysis), the challenges on electrolysis are twofold as it is both capital and energy intensive. Subsequently, the renewable electricity driven H2 production route will have even more challenges (which is partly due to the competition from electricity sector) to overcome. Thus, in future, the feedstock price can play an even more critical role and it is important to quantitatively understand the circumstances under which the other technologies can be economically competitive compared to SMR. Such analyses in the literature are mostly qualitative - For instance, some studies foresee that CG becoming more economically competitive compared to SMR as NG prices tend to increase more rapidly than that of coal (Stiegel and Ramezan, 2005; Mueller-Langer et al., 2007; Ball and Wietschel, 2009). However, an objective quantitative analysis is lacking.
Further, the relative cost-competitiveness of these technologies can vary significantly with the plant capacity due to the economies of scale (EOS). For instance, at medium production scale (say, 150 ton/day) SMR is more cost-competitive than what it is at large production scale (say, 750 ton/day), compared to CG (NAE, 2004). Further, actual feed-stock prices can vary significantly geographically depending on the local and global (in the case of imported feed-stocks) taxes. Hence, the EOS and geographic considerations need to be explicitly considered when evaluating a technology.
Further, the relative economic merits will also depend on the future CO2 mitigation policies as these technologies have very different carbon footprint. In a market with high carbon prices, BG may become economically competitive with CG. However, though BG can play a significant role in the H2 based economy and is one of the first renewable H2 production technologies that is expected to be available at commercial scale, there will be competition for the biomass from other sectors - i.e., to produce liquid biofuels and power/heat generation (Mueller-Langer et al. 2007).
In addition to the large-scale production technologies that are used exclusively for H2 production (as discussed above), the other production options include co-production (H2 and electricity) and small-scale forecourt production. Exclusively on the basis of economic and energetic potential, it may rather be more beneficial to consider the co-production of H2 and electricity in a IGCC plant with CCS (Chiesa et al., 2005 and Kreutz et al. 2005). Forecourt production however may become redundant if the by-product (or excess capacity) H2 from the existing production facilities can be streamlined to supply the H2 in the transition period (Konda et al., 2010).
In addition to a single plant level economic analysis, the large-scale H2 production requires network of several plants optimally located, by exploiting the trade-off between production and transportation costs. Hence network-wide perspective has to be taken to understand the implications of the production technology on the layout of the network. For instance, since biomass is less energy intensive, BG based networks could be relatively less-centralized compared to the network based on, for e.g., CG. In addition, network topology also depends on the H2 form – i.e., liquid or gaseous (LH2 or GH2). As shown by Konda et al., (2009 and 2010), LH2 based networks are more centralized while the GH2 based networks are less-centralized.
Hence, in this contribution, based on the historical data and future projections, we try to quantify the future potential (and limitations) of these technologies while explicitly accounting for possible technological advancements, production scale, CO2 emissions and geographic characteristics (by considering the Netherlands as a case-study). In addition, the presentation will encompass the benefits and limitations of co-production and forecourt production routes together with the importance and the need of optimal topology within the context of network of multiple-plants. Such an objective quantitative analysis helps to understand if these technologies can ever be cost-competitive (compared to SMR) and plan future research direction and strategies for the timely realization of the ultimate potential and market introduction of these technologies.
Disclaimer: Results/comments are of the authors' and do not necessarily represent the views of the associated organizations/institutions.
Ball, M., Wietschel, M., (2009) The future of hydrogen – opportunities and challenges. International Journal of Hydrogen Energy. (34) 615 – 627.
Chiesa, Paolo., Consonni, S., Kreutz, T., Williams, R., (2005) Co-production of hydrogen, electricity and CO2 from coal with commercially ready technology. Part A: Performance and emissions. International Journal of Hydrogen Energy. (30) 747-767.
Kreutz, T., Williams, R., Consonni, S., Chiesa P., (2005) Co-production of hydrogen, electricity and CO2 from coal with commercially ready technology. Part B: Economic analysis. International Jornal of Hydrogen Energy. (30) 769 – 784.
Konda, N. V. S. N. M., Shah, N., Kramer, G.J., Brandon, N. P., (2009) Spatio-Temporal Model based Optimization Framework to Design Future Hydrogen Infrastructure Networks. Hydrogen and Fuel Cells Conference (HFC2009). Vancouver, Canada.
Konda, N. V. S. N. M., Shah, N., Kramer, G.J., Brandon, N. P., Dutch Hydrogen Economy: A Multi-billion Dollar Question? Reflections from an Optimization Framework. to be presented at PSE Asia 2010, Singapore, July 2010.
Mueller-Langer, F., Tzimas, E., Kaltschmitt, M., Peteves, S., (2007) Techno-economic assessment of hydrogen production processes for the hydrogen economy in the short and medium term. International Journal of Hydrogen Energy. (32) 3797-3810.
NAE (2004) The Hydrogen Economy: Opportunities, Costs, Barriers and R&D Needs
Schoots, K., Ferioli, F., Kramer, G.J., van der Zwaan, B.C.C., (2008). Learning curves for hydrogen technology: An assessment of observed cost reductions. International Journal of Hydrogen Energy (33) 2630 – 2645.
Stiegel, G.J. and Ramezan, M. (2005) Hydrogen from coal gasification: An economical pathway to a sustainable energy future. International journal of Coal Geology (65) 173 – 190.