Optimizing Operations in Europe's Largest e-SAF Initiative

  • Due No due date
  • Points None

Background of the project

Sustainable Aviation Fuel is critical to reducing CO2 emissions, cutting lifecycle carbon emissions by 90% compared to conventional jet fuel. Europe’s ReFuelEU Aviation Regulation mandates the increased use of Sustainable Aviation Fuel (SAF), including e-SAF from 2030 onwards. The suggested hydrogen hub will contribute 40% of the required e-SAF volume when it starts up around the turn of the decade, making it a crucial player in Europe’s energy transition.

The Power2X production facility will be able to produce over 250,000 tonnes/year of e-SAF, a non-fossil, synthetic fuel made from green hydrogen. It will be the largest e-SAF facility announced to date, making sufficient ultra-low carbon fuel to fully power approximately 7,000 flights between Amsterdam and New York annually.  The facility will use imported green methanol produced from green hydrogen and biogenic carbon as feedstock as well as locally produced green hydrogen. Green methanol will be imported from locations where renewable energy and green hydrogen are abundant. The strategic location in the Port of Rotterdam offers direct access to European airports,  including Amsterdam Airport Schiphol, making it a key hub for the distribution of sustainable aviation fuels and e-fuels.

Tasks

  • Analyze and comprehend the operational processes involved in the entire production chain of eSAF.
  • Enhance and expand a mixed-integer optimization model, implemented in Python with Gurobi solver, to optimize the operation of large-scale energy systems, exploring coupling hydrogen production with other sectors.
  • Determine the eSAF selling price with and without green subsidy themes by applying price-driven or demand-driven optimization strategies.
  • (If two people contribute to the project.) Develop and implement a stochastic optimization framework to account for uncertainties in renewable energy supply, demand fluctuations, and market volatility in the production and pricing of eSAF.

Necessary experience

Programming (Python), Mathematical Modelling, Techno-economic analysis, Operation research

Source

eFuels Rotterdam (Power2X.com) Links to an external site.

Interested?

Contact PhD student Diamantis Almpantis at: diamantis.almpantis@energy.lth.se

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