Shipping the sunshine: An open-source model for costing renewable hydrogen transport from Australia

Green hydrogen (H2) is emerging as a future clean energy carrier. While there exists significant analysis on global renewable (and non-renewable) hydrogen generation costs, analysis of its transportation costs, irrespective of production method, is still limited. Complexities include the different forms in which hydrogen can be transported, the limited experience to date in shipping some of these carrier forms, the trade routes potentially involved and the possible use of different shipping fuels. Herein, we present an open-source model developed to assist stakeholders in assessing the costs of shipping various forms of hydrogen over different routes. It includes hydrogen transport in the forms of liquid hydrogen (LH2), ammonia, liquified natural gas (LNG), methanol and liquid organic hydrogen carriers (LOHCs). It considers both fixed and variable costs including port fees, possible canal usage charges, fuel costs, ship capital and operating costs, boil-off losses and possible environmental taxes, among many others. The model is applied to the Rotterdam-Australia route as a case study, revealing ammonia ($0.56/kgH2) and methanol ($0.68/kgH2) as the least expensive hydrogen derivatives to transport, followed by liquified natural gas ($1.07/kgH2), liquid organic hydrogen carriers ($1.37/kgH2) and liquid hydrogen ($2.09/kgH2). While reducing the transportation distance led to lower shipping costs, we note that the merit order of assumed underlying shipping costs remain unchanged. We also explore the impact of using hydrogen (or the hydrogen carrier) as a low/zero carbon emission fuel for the ships, which led to lowering of costs for liquified natural gas ($0.88/kgH2), a similar cost for liquid hydrogen ($2.19/kgH2) and significant increases for the remainder. Given our model is open-sourced, it can be adapted globally and updated to match the changing cost dynamics of the emerging green hydrogen market.

» Author: Charles Johnston, Muhammad Haider Ali Khan, Rose Amal, Rahman Daiyan, Iain MacGill

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This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement Nº 768737


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