Abstract

This paper focuses on developing a fast-solving open-source model for dynamic power-to-X plant techno-economic analysis and analysing the method bias that occurs when using other state-of-the-art power-to-X cost calculation methods. The model is a least-cost optimisation of investments and operation-costs, taking as input techno-economic data, varying power profiles and hourly grid prices. The fuel analysed is ammonia synthesised from electrolytic hydrogen produced with electricity from photovoltaics, wind turbines or the grid. Various weather profiles and electrolyser technologies are compared. The calculated costs are compared with those derived using methods and assumptions prevailing in most literature. Optimisation results show that a semi-islanded set-up is the cheapest option and can reduce the costs up to 23% compared to off-grid systems but leads to e-fuels GHG emissions similar to fossil fuels with today’s electricity blend. For off-grid systems, estimating costs using solar or wind levelized cost of electricity and capacity factors to derive operating hours leads to costs overestimation up to 30%. The cheapest off-grid configuration reaches production costs of 842 €/tNH3. For comparison, the ”grey” ammonia price was 250 €/tNH3 in January 2021 and 1500 €/tNH3 in April 2022 (Western Europe). The optimal power mix is found to always include photovoltaic with 1-axis tracking and sometimes different types of onshore wind turbines at the same site. For systems fully grid connected, approximating a highly fluctuating electricity price by a yearly average and assuming a constant operation leads to a small cost (<4%) overestimation compared to the more advanced optimisation method applied here .

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