This thesis addresses the challenge of decarbonizing industrial and territorial systems by proposing a transition to direct current (DC) microgrids controlled by a Digital Twin. Faced with the saturation of alternating current (AC) grids due to the growth of photovoltaics, energy storage, and electric mobility, DC allows for a reduction in conversion losses (5 to 15%), improved flexibility, and a simplification of the electrical architecture.
The project is based on the development of a high-fidelity Digital Twin synchronized in real-time simulation. More than just a monitoring tool, it acts as a proactive decision-making system integrating advanced optimization algorithms, such as artificial intelligence and predictive control. It anticipates voltage instabilities, which are particularly critical in low-inertia DC grids, and continuously optimizes power flows to maximize self-consumption while preserving battery life.
Experimental validation relies on a Hardware-in-the-Loop approach within the CEA-Liten/G2Elab ecosystem, integrating physical converters. This methodology guarantees robustness, security, and resilience before any real-world deployment.
The expected outcomes are scientific (stability and real-time modeling), operational (provision of technical guides and decision-making tools), and strategic (strengthening French technological sovereignty in Smart Grids and accelerating the 2050 carbon neutrality trajectory advocated by ADEME).