TY - THES

T1 - Techno-Economic Assessment of H2-Supply for an Industrial Site

AU - Wechner, Lukas

N1 - no embargo

PY - 2024

Y1 - 2024

N2 - To advance the mitigation of global warming by decarbonization, the industrial sector has to transform towards low emission energy sources. Green hydrogen is seen as an important part of this transformation. However, the absence of a well-established hydrogen transport infrastructure slows the implementation of production capacities and industrial applications. Moreover, investments in hydrogen infrastructure align close to the production of hydrogen and the industrial demand. Therefore, companies willing to transform toward clean energy have to make a strategic decision, if the supply should rely on regional infrastructure or if an investment in on-site production facilities should be considered. To support this decision-making process a calculation model is developed to evaluate the techno-economic concept for hydrogen supply of an industrial site.The model is created within the Python programming environment utilizing the Open Energy Modelling Framework “OEMOF”. It is further supported by Excel spreadsheets to ease user interaction, result processing and graphical representation. The model can be tailored to investigate different scenarios focusing on on-site hydrogen production strategies through water electrolysis. Furthermore, an aboveground hydrogen storage as a flexibility option is taken into account evaluating the economic influence. The model is cost optimized by a mixed linear integer solver in regard of fluctuating electricity prices. Moreover, the flows, the capacities of the components component and their corresponding costs are determined to enable a detailed analysis.Additionally, an exemplary calculation is carried out by providing technical and economic parameters for hydrogen production in near future. Together with an electricity price profile and a load profile the influences on costs and on the operational strategy are determined.It turns out that the utilization of a hydrogen storage can reduce the hydrogen supply costs up to a certain point depending on the storage capacity. However, the implementation of larger hydrogen storage leads to a rise in hydrogen supply costs. Increasing the storage capacity by compressing or liquifying the hydrogen turned out to be not favourable under these assumptions.The electricity price was identified as the main cost driver necessitating a further expansion of renewable energy sources to reduce electricity prices and utilize fluctuations.For an industrial site with an annual hydrogen demand of 72 GWh the hydrogen supply costs for merchant hydrogen delivered by different transport routes and the on-site production lie within the same range. Depending on the underlying assumptions on-site production can be a competitive alternative for merchant hydrogen.

AB - To advance the mitigation of global warming by decarbonization, the industrial sector has to transform towards low emission energy sources. Green hydrogen is seen as an important part of this transformation. However, the absence of a well-established hydrogen transport infrastructure slows the implementation of production capacities and industrial applications. Moreover, investments in hydrogen infrastructure align close to the production of hydrogen and the industrial demand. Therefore, companies willing to transform toward clean energy have to make a strategic decision, if the supply should rely on regional infrastructure or if an investment in on-site production facilities should be considered. To support this decision-making process a calculation model is developed to evaluate the techno-economic concept for hydrogen supply of an industrial site.The model is created within the Python programming environment utilizing the Open Energy Modelling Framework “OEMOF”. It is further supported by Excel spreadsheets to ease user interaction, result processing and graphical representation. The model can be tailored to investigate different scenarios focusing on on-site hydrogen production strategies through water electrolysis. Furthermore, an aboveground hydrogen storage as a flexibility option is taken into account evaluating the economic influence. The model is cost optimized by a mixed linear integer solver in regard of fluctuating electricity prices. Moreover, the flows, the capacities of the components component and their corresponding costs are determined to enable a detailed analysis.Additionally, an exemplary calculation is carried out by providing technical and economic parameters for hydrogen production in near future. Together with an electricity price profile and a load profile the influences on costs and on the operational strategy are determined.It turns out that the utilization of a hydrogen storage can reduce the hydrogen supply costs up to a certain point depending on the storage capacity. However, the implementation of larger hydrogen storage leads to a rise in hydrogen supply costs. Increasing the storage capacity by compressing or liquifying the hydrogen turned out to be not favourable under these assumptions.The electricity price was identified as the main cost driver necessitating a further expansion of renewable energy sources to reduce electricity prices and utilize fluctuations.For an industrial site with an annual hydrogen demand of 72 GWh the hydrogen supply costs for merchant hydrogen delivered by different transport routes and the on-site production lie within the same range. Depending on the underlying assumptions on-site production can be a competitive alternative for merchant hydrogen.

KW - Hydrogen Production

KW - Hydrogen Transport

KW - Electrolysis

KW - Industrial Use of Hydrogen

KW - Supply Costs

KW - Cost Optimization

KW - Hydrogen Storage Option

KW - Renewable Energy Sources

KW - Wasserstoffproduktion

KW - Wasserstofftransport

KW - Elektrolyse

KW - Industrielle Wasserstoff Nutzung

KW - Versorgungskosten

KW - Kostenoptimierung

KW - Wasserstoffspeicher

KW - Erneuerbare Energie

U2 - 10.34901/mul.pub.2024.166

DO - 10.34901/mul.pub.2024.166

M3 - Master's Thesis

ER -