Europe stated the ambitious target of becoming carbon neutral by 2050 to combat climate change and meet the requirements imposed by the Paris Agreement, and renewable energy has proved to be a promising solution for the decarbonization of many sectors. Nonetheless, their aleatory nature leads to grid unbalances due to the difference between supply and demand. Storage solutions are needed, and electrofuels become a key factor in this context: they are fuels produced from electricity, which leads to carbon-neutral fuels if it originates from renewable sources. These can constitute a key solution to store the surplus energy and to decarbonize the so-called hard-to-abate sectors. Electrofuel production technologies have not yet been fully developed, and, in this context, extensive study of the state-of-the-art of existing projects can be very useful for researchers and developers. This work researches the European projects funded by the Horizon 2020 Programme regarding electrofuel production. The projects were analyzed in-depth using specific features, and the results were presented.

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The need to reduce greenhouse gas emissions is leading to an increase in the use of renewable energy sources. Due to the aleatory nature of these sources, to prevent grid imbalances, smart management of the entire system is required. Industrial refrigeration systems represent a source of flexibility in this context: being large electricity consumers, they can allow large-load shifting by varying separator levels or storing surplus energy in the products and thus balancing renewable electricity production. The work aims to model and control an industrial refrigeration system used for freezing food by applying the Model Predictive Control technique. The controller was developed in Matlab® and implemented in a Model-in-the-Loop environment. Two control objectives are proposed: the first aims to minimize total energy consumption, while the second also focuses on utilizing the maximum amount of renewable energy. The results show that the innovative controller allows energy savings and better exploitation of the available renewable electricity, with a 4.5% increase in its use, compared to traditional control methods. Since the proposed software solution is rapidly applicable without the need to modify the plant with additional hardware, its uptake can contribute to grid stability and renewable energy exploitation.

The fluid-structure interaction (FSI) problem has been extensively studied, and many papers and books are available in the literature on the subject. In this work, we consider some optimal FSI pressure boundary control applications by using a membrane model derived from the Koiter shell equations where the thickness of the solid wall can be neglected and the computational cost of the numerical problem reduced. We study the inverse problem with the aim of achieving a certain objective by changing some design parameters (e.g. forces, boundary conditions or geometrical domain shapes) by using an optimal control approach based on Lagrange multipliers and adjoint variables. In particular, a pressure boundary optimal control is presented in this work. The optimality system is derived from the first-order optimality condition by taking the Fréchet derivatives of the Lagrangian with respect to all the variables involved. This system is solved by using a finite element code with mesh-moving capabilities. In order to support the proposed approach, we perform numerical tests where the pressure on a fluid domain boundary controls the displacement that occurs in a well-defined region of the solid domain.