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Martin Robinius

Researcher at Forschungszentrum Jülich

Publications -  136
Citations -  6111

Martin Robinius is an academic researcher from Forschungszentrum Jülich. The author has contributed to research in topics: Renewable energy & Wind power. The author has an hindex of 31, co-authored 135 publications receiving 3423 citations.

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Power to Gas: Technological Overview, Systems Analysis and Economic Assessment for a Case Study in Germany

TL;DR: In this paper, the authors present the process chains of different power-to-gas paths, including different transformation technologies, which it evaluates with regard to their suitability for applications, the optional methanation step including the necessary production of CO 2, distribution options and geological storage options as well as end-user applications.
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Seasonal storage and alternative carriers: A flexible hydrogen supply chain model

TL;DR: In this paper, the authors developed a model that draws on and extends approaches in the literature with respect to long-term storage and analyzed Liquid Organic Hydrogen Carriers (LOHC) and showed their potential impact on future hydrogen mobility.
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A Review of Post-combustion CO2 Capture Technologies from Coal-fired Power Plants

TL;DR: In this paper, the basic process designs of chemical absorption and membrane-based separation processes for CO 2 capture, as well as corresponding optimization methods including optimizing operational parameters, process modifications, membrane module types and so forth.
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The investment costs of electrolysis - A comparison of cost studies from the past 30 years

TL;DR: In this article, a literature review was conducted to evaluate the published data on investment costs and learning rates for PEM and alkaline electrolyzers from the 1990s until 2017 and the years beyond.
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Impact of different time series aggregation methods on optimal energy system design

TL;DR: It was found that regardless of the method, time series aggregation allows for significantly reduced computational resources, and averaged values lead to underestimation of the real system cost in comparison to the use of representative periods from the original time series.