Technological learning and the future of solar H2: A component learning comparison of solar thermochemical cycles and electrolysis with solar PV

Nicodemus, Julia Haltiwanger

doi:10.1016/j.enpol.2018.04.072

Cited by 36 publications

(12 citation statements)

References 44 publications

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“…The LCOH of ceria in the best case accounts to 6.68 €/kg. The results compare well with the figures recently presented by Nicodemus [25].…”

Section: Case Studysupporting

confidence: 91%

“…The calculated price for thermochemical cycles ranged from 3.5 €/kg to 12.8 €/kg in an optimistic and conservative scenario, respectively. Recently, Nicodemus compared again solar thermochemical cycles and solar PV electrolysis [25]. The focus was on the learning curves for each of the main plant components.…”

Section: Technology and Literature Reviewmentioning

confidence: 99%

“…First ones typically focus on very specific technical aspects such as new materials or component design and do not include economic analysis [20][21][22]. In the second ones, which to the best of our knowledge assume fixed or reference plant configurations, the inter-dependence between economic input parameters and optimal plant design are neglected [24,25].…”

Section: Intentionmentioning

confidence: 99%

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Techno-Economic Assessment of Solar Hydrogen Production by Means of Thermo-Chemical Cycles

2019

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This paper presents the system analysis and the techno-economic assessment of selected solar hydrogen production paths based on thermochemical cycles. The analyzed solar technology is Concentrated Solar Power (CSP). Solar energy is used in order to run a two-step thermochemical cycle based on two different red-ox materials, namely nickel-ferrite and cerium dioxide (ceria). Firstly, a flexible mathematical model has been implemented to design and to operate the system. The tool is able to perform annual yield calculations based on hourly meteorological data. Secondly, a sensitivity analysis over key-design and operational techno-economic parameters has been carried out. The main outcomes are presented and critically discussed. The technical comparison of nickel-ferrite and ceria cycles showed that the integration of a large number of reactors can be optimized by considering a suitable time displacement among the activation of the single reactors working in parallel. In addition the comparison demonstrated that ceria achieves higher efficiency than nickel-ferrite (13.4% instead 6.4%), mainly because of the different kinetics. This difference leads to a lower LCOH for ceria (13.06 €/kg and 6.68 €/kg in the base case and in the best case scenario, respectively).

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“…The LCOH of ceria in the best case accounts to 6.68 €/kg. The results compare well with the figures recently presented by Nicodemus [25].…”

Section: Case Studysupporting

confidence: 91%

Section: Technology and Literature Reviewmentioning

confidence: 99%

Section: Intentionmentioning

confidence: 99%

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Techno-Economic Assessment of Solar Hydrogen Production by Means of Thermo-Chemical Cycles

2019

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“…Another approach is the estimation of future cost reduction according to technological learning [4]. Nicodemus [5] investigated the impact of policy support on technological learning for PV powered PEM electrolysis resulting in the production costs of < 3 $/kg H2 by 2030. Similar results could be reached using high-temperature electrolysis [6].…”

Section: Introductionmentioning

confidence: 99%

Projecting cost development for future large-scale power-to-gas implementations by scaling effects

et al. 2020

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Power-togas (PtG) is widely expected to play a valuable role in future renewable energy systems. In addition to partly allowing a further utilization of the existing gas infrastructure for energy transport and storage, hydrogen or synthetic natural gas (SNG) from electric power represents a high-density energy carrier and important feedstock material for further processing. This premise leads to a significant demand for large-scale PtG plants, which was evaluated with an amount of up to 14.2 TWel at a global scale. Together with the upscaling of single-MW plants available today, this will enable to achieve appropriate cost reduction effects through technological learning. These effects were evaluated in the present paper via a holistic techno-economic assessment of different PtG plant configurations, resulting in the reduction of SNG production costs down to 100 €/MWhSNG by 2030 and below 60 €/MWhSNG by 2050, according to the supplying electricity source.

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“…The former may result in wrong assumptions on the overall learning rate through an omitted variable bias [16]. The latter requires the utilization of composite learning curves, which for a one-factor model is given by [9,17]:…”

Section: Introduction To Learning Curve Modelsmentioning

confidence: 99%

Applying Endogenous Learning Models in Energy System Optimization

et al. 2021

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Conventional energy production based on fossil fuels causes emissions that contribute to global warming. Accurate energy system models are required for a cost-optimal transition to a zero-emission energy system, which is an endeavor that requires a methodical modeling of cost reductions due to technological learning effects. In this review, we summarize common methodologies for modeling technological learning and associated cost reductions via learning curves. This is followed by a literature survey to uncover learning rates for relevant low-carbon technologies required to model future energy systems. The focus is on (i) learning effects in hydrogen production technologies and (ii) the application of endogenous learning in energy system models. Finally, we discuss methodological shortcomings of typical learning curves and possible remedies. One of our main results is an up-to-date overview of learning rates that can be applied in energy system models.

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Technological learning and the future of solar H2: A component learning comparison of solar thermochemical cycles and electrolysis with solar PV

Cited by 36 publications

References 44 publications

Techno-Economic Assessment of Solar Hydrogen Production by Means of Thermo-Chemical Cycles

Techno-Economic Assessment of Solar Hydrogen Production by Means of Thermo-Chemical Cycles

Projecting cost development for future large-scale power-to-gas implementations by scaling effects

Applying Endogenous Learning Models in Energy System Optimization

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