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Learning curves for hydrogen production technology: An assessment of observed cost reductions

机译:制氢技术的学习曲线:观察到的成本降低评估

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At present three key energy carriers have the potential to allow a transition towards a sustainable energy system: electricity, biofuels and hydrogen. All three offer great opportunity, but equally true is that each is limited in different ways. In this article we focus on the latter and develop learning curves using cost data observed during the period 1940-2007 for two essential constituents of a possible 'hydrogen economy': the construction of hydrogen production facilities and the production process of hydrogen with these facilities. Three hydrogen production methods are examined, in decreasing order of importance with regards to their current market share: steam methane reforming, coal gasification and electrolysis of water. The fact that we have to include data in our analysis that go far back in time, as well as the uncertainties that especially the older data are characterized by, render the development of reliable learning curves challenging. We find only limited learning at best in a couple of cases, and no cost reductions can be detected for the overall hydrogen production process. Of the six activities investigated, statistically meaningful learning curves can only be determined for the investment costs required for the construction of steam methane reforming facilities, with a learning rate of 11 ± 6%, and water electrolysis equipment, with a learning rate of 18 ± 13%. For past coal gasification facility construction costs no learning rate can be discerned. The learning rates calculated for steam methane reforming and water electrolysis equipment construction costs have large error margins, but lie well in the range of the learning reported in the literature for other technologies in the energy sector.
机译:目前,三个主要的能源载体有潜力实现向可持续能源系统的过渡:电力,生物燃料和氢。这三者都提供了巨大的机会,但同样真实的是,它们各自以不同的方式受到限制。在本文中,我们将重点放在后者上,并使用在1940-2007年期间观察到的成本数据,为可能的“氢经济”的两个基本组成部分开发学习曲线:氢生产设施的建设和使用这些设施的氢生产过程。考察了三种制氢方法,从其当前的市场份额来看,其重要性从高到低依次为:甲烷蒸汽重整,煤气化和水电解。我们必须在分析中包括时光倒流的数据这一事实,以及尤其是较早的数据所具有的不确定性,使得可靠学习曲线的开发具有挑战性。我们发现,在某些情况下,充其量只能进行有限的学习,并且无法检测到整个制氢过程的成本降低。在所调查的六项活动中,只有对于建设蒸汽甲烷重整设施所需的投资成本(学习率为11±6%)和水电解设备的建设成本为18±的情况下,才能确定具有统计意义的学习曲线。 13%。对于过去的煤气化设施建设成本,无法看出学习率。为蒸汽甲烷重整和水电解设备的建造成本计算的学习率具有较大的误差范围,但恰好在文献中针对能源行业其他技术的学习范围之内。

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