Page 42 - LSR vuosikertomus 2020

Optimising the Next Generation
Renewable Fuel Supply Chains for
Resilient and Sustainable Operations

Tulevaisuuskestävä ympäristö 30 000 €

Hossein Mostafaei, PhD
Aalto-yliopisto
Matematiikan ja systeeminalyysin laitos

VÄITÖSKIRJAN JÄLKEINEN TUTKIMUS

”Despite being Despite being a promising key player in the decarbonisation pathway
a promising key laid out in the Paris agreement, the production of renewable diesel
player in the still faces several challenges that curb its wider spread development. Bio-
decarbonisation and renewable fuels have a remarkable potential of being one of the
pathway laid central elements in the decarbonisation of the transportation section.
out in the Paris In general, biofuels refer to traditional fatty acid methyl esters (FAME)-based
agreement, road transportation diesel produced from vegetable oils and residual fat
the production and/or waste and renewable fuels refer to jet and marine (bunker) fuel,
of renewable propane, ethanol and diesel that are produced (partially or entirely) from
diesel still faces organic matter such as vegetable oils and residual fat and/or waste using
several challenges hydrotreating processes. Among these, bio- and renewable diesel is the
that curb its most disseminated, being already widely used all over the world. In the
wider spread European Union, bio- and renewable diesel accounts for approximately
development.” 93 % of all renewable energy used for transportation in 2018.
To remain competitive and achieve a sustainable profitability, companies
42 operating renewable fuel supply chains are required to operate at highly
optimised settings. Small marginal cost reductions can represent consi-
derable savings given the typical large-scale of the refinery operations.
However, achieving and retaining optimal operation levels is virtually im-
possible without taking into account the uncertainty embedded in these
uncertain factors.
In this project, we will construct state-of-the-art mathematical model-
ling methods, developing a data-driven robust optimisation model that
can be employed to support decision making in renewable fuel supply
chain (RFSC) management. This model will be capable of identifying
cost-efficient RFSC designs that are optimised focusing on minimising
operational costs and satisfy robustness requirements in terms of biomass
supply security risks. We anticipate that the outcomes of this project will
aggregate significant value to planning activities of oil refining companies
producing renewable fuels (e.g., Neste) and provide substantial improve-
ments to their supply chain overall performance, thereby contributing to
the decarbonisation of the transportation sector.