Martin Miltner

Chemical-oxidative scrubbing for the removal of hydrogen sulphide from raw biogas: potentials and economics

In the present work chemical-oxidative scrubbing as a novel method for the desulphurisation of raw biogas is presented with a special focus on the process potentials and economics. The selective absorption of hydrogen sulphide from gas streams containing high amounts of carbon dioxide using caustic solutions is not trivial but has been treated in literature. However, the application of this method to biogas desulphurisation has not been established so far. Based on rigorous experimental work, an industrial-scale pilot plant has been designed, erected and commissioned at a biogas plant with biogas upgrading and gas grid injection in Austria. Data collected from the 12-month monitored operation has been used to elaborate performance as well as economic parameters for the novel desulphurisation method. The proposed technology offers significant operational advantages regarding the degree of automation and the flexibility towards fluctuations in process boundary conditions. Furthermore, the economic assessment revealed the high competitiveness of the chemical-oxidative scrubbing process compared with other desulphurisation technologies with the named advantageous operational behaviour.

Biogas desulfurization and biogas upgrading using a hybrid membrane system - modeling study.

Membrane gas permeation using glassy membranes proved to be a suitable method for biogas upgrading and natural gas substitute production on account of low energy consumption and high compactness. Glassy membranes are very effective in the separation of bulk carbon dioxide and water from a methane-containing stream. However, the content of hydrogen sulfide can be lowered only partially. This work employs process modeling based upon the finite difference method to evaluate a hybrid membrane system built of a combination of rubbery and glassy membranes. The former are responsible for the separation of hydrogen sulfide and the latter separate carbon dioxide to produce standard-conform natural gas substitute. The evaluation focuses on the most critical upgrading parameters like achievable gas purity, methane recovery and specific energy consumption. The obtained results indicate that the evaluated hybrid membrane configuration is a potentially efficient system for the biogas processing tasks that do not require high methane recoveries, and allows effective desulfurization for medium and high hydrogen sulfide concentrations without additional process steps.

Reduced Model Describing Efficient Extraction of Hydrogen Transported as Co-Stream in the Natural Gas Grid

Abstract The worlds energy demand is increasing since years. Together with environmental issues (e.g. global warming) and energy security concerns, renewable energies are on the rise. As these are less predictable the importance of a cost effective and environmentally friendly energy storage and transportation system increases. A solution might be hydrogen (H 2 ), as the gas has a high energy density and might be a future energy carrier. In a power-to-gas context electrical energy is used to produce H 2 via water electrolysis. The gas can be stored and transported, most cost- and energy-efficient via pipelines. However, pipelines are capital intensive so the current natural gas-grid could be used to co-transport H 2 . According to national pipeline regulations low H 2 concentrations are already possible (e.g. 4%(v/v) in Austria). While the injection is straightforward, the extraction is challenging. In previous work a process has been identified, experimentally validated and optimised via process simulation, that is able to extract H 2 at fuel cell quality (99.97%(v/v) according to ISO 14687-2:2012). The previously gained knowledge is used in the current work to create a reduced model (combination of principal component analysis and trained artificial neural network). The model has a significantly increased performance compared to the whole process simulation. Therefore, it is computationally less expensive and can be easily implemented in further investigations like GIS based analysis and economic evaluations as done in ongoing work.