Project cooperationUpdated on 8 December 2025

AI&Digital-Twin-Enabled Sustainable Economic Dispatch with WBG Smart Inverters for Life-Cycle-Optimized, High Power Quality PV/Battery/Fuel-Cell Hybrid Systems

Full Professor at ENSEA: École nationale supérieure de l'électronique et de ses applications

Paris-Cergy, France

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Aim & originality: go beyond conventional energy management and active filtering by coupling AI-based PV/load forecasts with battery/electrolyzer aging models within a hybrid electric–H₂ sustainable economic power dispatch (S-EPD) strategy. This S-EPD is integrated into a WBG smart inverter with SAF capabilities and a multi-active bridge (MAB) power converter, enabling high-efficiency, multi-energy management of PV, battery, electrolyzer, and fuel cell systems. The project shifts from instantaneous to life-cycle cost minimization by maximizing system lifetime at fixed energy performance, and embedding energy-efficient AI inference models on smart inverter hardware, enabling real-time, low-power operation and industrial transfer. This is complemented by an AI-enabled intelligent digital twin of battery- and hydrogen-based energy storage systems, dedicated to sustainable life-cycle management, ageing monitoring, predictive maintenance, and the optimal use of storage in the presence of RES/H₂ to support a more reliable, more resilient grid and a reduced environmental footprint, in line with grid flexibility and resilience targets. To the best of our knowledge, this is the first integrated structure of its kind.

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