With the increasing number of generation and consumption units connected through power electronic converters, the electrical grid is evolving toward a more dynamic and decentralized structure. This transformation strengthens both the need and the potential for these converters to actively contribute to system flexibility and stability—particularly in compensating for renewable energy fluctuations and maintaining the balance between supply and demand.

Optimized coordination of their control functions offers significant potential to improve grid resilience, by intelligently leveraging their capabilities in voltage regulation, frequency support, and reactive power control. However, to integrate these contributions effectively at scale, it is essential to develop holistic modeling approaches that capture multi-scale interactions—both in time and space.

The modeling work in this thesis aims to represent the relationship between the active/reactive power flexibility of power electronic converters and the stability margin they provide to the grid, as well as to model the aggregation of their actions for system-wide contribution. Building on this foundation, coordinated control architectures and algorithms between the distribution and transmission networks will be investigated, developed, and validated.

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).