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Blockchain, digital twins and AI: the energy transition calls for the development of new technologies.


Published 03 Avril 2020



T[/leap_dropcaphe Think Smartgrids Data and Digital Transformation Working Group looked at the opportunities offered by new technologies based on artificial intelligence to improve the efficiency and sustainability of energy networks. A growing number of pioneering projects are already being deployed in France and these technologies seem very promising, provided that cybersecurity issues are not overlooked.


Digital twinning, Automatic or Deep Learning, Reinforced Learning, or Blockchain: those technologies have experienced tremendous growth in recent years and are accompanying the deployment of smart grids. They were described in a study published last November by the Think Smartgrids Data and Digital Transformation working group, led by Cosmo Tech and DCbrain.

Thanks to learning techniques, a machine can become capable of acting autonomously on its environment or become a valuable decision support tool. Several examples of the use of machine learning and deep learning technologies for the energy sector have been successfully implemented: thanks to these technologies, it is possible to adapt the network to consumer demand based on the analysis of a certain number of parameters (weather data, the history of peaks and troughs in hourly consumption, storage capacities, etc.), it also becomes possible to detect new energy resources, or even to optimise energy consumption.

Among the pioneering projects deployed in France, we can mention a project runned by RTE (Réseau de Transport d’Electricité, the French transmission system operator) with digital twins: JUMP (JUMeaux numériques Postes – or digital twins of electric substations).

JUMP aims to provide a common technical base and processes for the 3D modelling of assets, with a collaborative use that can meet the priority needs of RTE’s various business