The production of electricity by renewable energy, connected to the grid with power electronic converters is increasing. Hence, the question of dynamic stability evaluation of electricity grid is becoming more and more complex due to power electronic converters. To cope with this situation, the Transmission System Operators needs to have a good dynamic knowledge of these new devices that are connected to the grid. One solution is to have a real-time evaluation of the power converter impedance. The proposed project will use some deep learning algorithms to develop a digital twin which mimics the dynamic behavior of the power converter in case of normal operation or large events such as short circuit. This digital twin, based on metamodel will allow the TSO to control the dynamic performance of the converters which are connected to the transmission grid. Some experimentation will be developed on small-scale power electronic converters connected to a real-time simulator.

Since they have reached a sufficient level of maturity, and due to rising environmental concerns, to a decrease in their costs and, above all, to a political support resulting notably in attractive feed-in tariffs, renewable-based power generation –and particularly wind and solar photovoltaic– have been growing rapidly over the past few years. Their impacts on power systems can be classified in two categories: 1/ the “local” impacts, on distribution grids to which most of these new generation assets are connected and 2/ the “global” impacts, which is manifested by consequences on unit commitment and dispatch, as well as on the dynamic behavior of the grids. This project is aimed to deal with these two classes of problems. As regards the local impacts, the main concern that will be tackled rests on the fact that the connection of decentralized generation requires distribution grid upgrades, whose high costs could eventually jeopardize, when significant penetration levels are reached, the further development of wind and photovoltaic generation. Several innovative solutions capable of reducing or even cancelling the need for grid reinforcements have been proposed (local volt/var control, temporary curtailment, distributed energy storage systems, etc.), and their technical potential has been demonstrated. To prepare for the future, it now seems crucial to identify, within these technically promising options, the one or the few ones that will enable the connection of distributed generation at the lowest possible cost for the community and with no adverse effect on power quality. That is why one of the main goals of this project will be to develop a new approach to carry out grid connection studies of distributed generators, capable of establishing a merit order of the various conventional (i.e. grid reinforcement) and innovative options. This work will help determine, in an evolving context, the new technical/economic optima that will build future distribution systems. As regards the global aspects, the massive integration of renewable energy sources has significant impacts on system operation. Especially, impacts on unit commitment and dispatch, static security and dynamic stability could be a serious impediment for renewable energy expansion. Technical limits have been highlighted in many studies as well as the need of high investments to maintain power system security and reliability level. In order to cope with this complex issue, a new metric of power system performances taking into account the specificities of renewable energy sources together with more conventional aspects (reliability, flexibility, security and stability) will be developed. This metric will be used as a constraint in a power system operation optimization problem and, by calculating these new optima, the maximum allowable penetration level of renewable energy sources will be determined rigorously. By considering all the parameters related to system operation in the same optimization problem, we expect a better comprehension of the interactions between them and their influence on the maximum allowable penetration level. The research work that will be carried out within this project is very specialized, complex and ambitious. Since the objective functions involved herein are based on a probabilistic representation of power systems, it will notably be necessary to overcome the difficulties related to the optimization of expensive-to-evaluate functions.

Our daily life have seen the touchscreen emerge, as a cost-effective input device. As a result, vision becomes more predominant in the interaction, which leads to several disadvantages: they complicate the lives of visually impaired people, and they pose serious safety concerns in automotive application for instance. But introducing more haptic feedback into the interaction is a promising way to cope for these issues. Moreover, these past years have seen emerging technologies that adopt other material – like wood, leather or textile – to become haptic surfaces, ie. surfaces than can change how they are perceived by the users. This leads the industry to propose smart surfaces, which rendering can be set by software and changed over time. This context legitimates a huge interest in outperforming the existing haptic feedback solutions, leanding to the main goal of HASAMé: to propose new solutions to create Surfaces that integrate a compelling Haptic Feedback.

This network proposal is intended to meet the H2020 call LC-SC3-ES-6-2019. The network is composed of 6 partners from 4 European countries (Germany, Denmark, Spain and France). This network has the particularity of having 2 insular partners (Reunion Island, Gran Canary Island), members of the outermost regions (ORs) of Europe. The topic to be proposed in response to the H2020 call is the building of advanced modelling tools for forecasting energy production and for ensuring the stability of the insular electricity grids with a large share of solar and wind renewables. Currently, very little research studies the prediction of variable sources (solar, wind) in connection with the contribution of storage and voltage-frequency problems that already some island networks experience. The originality of the project lies in the fact that it already responds to the effective limitation (disconnection of production systems) encountered in some island systems. This project will therefore contribute to developing the potential of the variable energies and consequently increase, very significantly, this share of intermittent energy in the energy mix. The results of the study will contribute to the revival of renewable sectors for territories that have reached the insertion limit. This stimulus could thus generate skilled jobs in the respective energy sectors. In addition to their complementarity, the partners of the network bring specialized and internationally recognized expertise in different aspects of the project. The project coordinator has a solid experience in project management. He is actively involved in international research networks and is already working closely with some members of the proposed consortium. Regarding the planning and installation of the network initiated in June 2017, 2 seminars are planned before the project is submitted to the H2020 call. The network will benefit from the support of the project engineering unit of the University of La Réunion as well as concrete contributions from the Europe-innovation unit. Finally, thanks to the MRSEI tool, we will be able to count on the professional support of a specialized service provider in the building of European projects.

The WISSTITWIN project aims at the development of an integrated network of smart sensors within an electrical machine, that will constantly stream data in order to update the numerical model of the electrical machine, known as its ‘digital twin’. Therefore, it is highly desirable to have access to a numerical model that is constantly updated through physical multi-parameters measurements provided by a network of sensors integrated in the real machine. For this purpose, we need reliable sensors that are compatible with an integration in low space and harsh environments, along with a reliable communication for data streaming. Thus, the project will exploit the combination of advanced functional materials and Surface Acoustic Wave technology to build batteryless and wireless multiphysics sensors with performances adapted to these constraints. A demonstrator of an electrical machine with several distributed sensors for temperature, stress, and magnetic field will be developed, along with its digital twin.