Hydrogen is the only carbon-free storable fuel. When combined with
renewable energy sources, it has the potential to become one of the main
contributors of a sustainable future as a green energy vector.
This PhD thesis will focus on a Wind-to-Hydrogen (W2H2) system where
hydrogen is produced through electrolysis of water and electricity is
provided by a wind farm. After production, hydrogen should be stored,
transported and distributed in an optimal way, given the numerous
technology alternatives available.
In this system, there will be two decision makers: wind farm operator
and hydrogen producer with conflicting interests in a hierarchical
setting. This type of problems is usually modeled as a Stackelberg game
(bilevel programming) in the literature and it will be direction of this
thesis as well.
Uncertainties of the system notably come from electricity generation
(due to changing weather conditions), variability of energy prices in
the day-ahead spot market and demand fluctuation. These uncertainties
will be addressed in the modelling part.
We are offering a 3-year CIFRE contract PhD thesis in collaboration with
PersEE Innovation, a Paris based startup company (Sezin Afsar) and
Laboratory CERMICS, Ecole des Ponts Paris Tech (Michel De Lara). The
thesis will be based on modeling and solving different versions of this
problem described above. Different types of real-life or realistic data
will be available for testing.
Keywords: supply chain management, wind energy, hydrogen, stochastic
optimization, bilevel programming
Required Technical Skills:
• Master's degree or equivalent in Industrial Eng, Computer Science,
Applied Math or any relevant subject
• Experience in Python/C/C++ and solvers such as GAMS, CPLEX or Gurobi
• General knowledge of mathematical programming and optimization.
Expertise in stochastic and bilevel programming is an advantage.
• Familiarity with at least one of relevant fields (energy systems,
renewable energy, scheduling, supply chain management…)
Behavioral Skills:
• Adaptability to team work
• Curiosity and enthusiasm to learn
• Flexibility
• Being open to new ideas and innovations
• Willingness to contribute to a cleaner future
• Speaking French is a plus
Candidates may send their CV, transcript, motivation letter and
references to saf@pers-ee.fr until July 15th, 2017. Start date will be
October 2017 or later.
--
Dr. Sezin AFSAR
PersEE - Optimization Scientist
(+33)1 40 05 04 03
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