Sheng Chen

Dynamics-aware scheduling of renewable electrolyzer plants: A physics-informed reinforcement learning approach

Surrogate-Assisted Deep Reinforcement Learning for Commercial HVAC Optimal Control Considering Thermal Inertia

Commercial buildings can provide operational flexibility through HVAC control because thermal inertia enables short-term load shifting under time-of-use (TOU) electricity pricing. However, direct reinforcement learning interaction with a high-fidelity building simulator is computationally expensive and may generate und...

Frequency-Constrained Unit Commitment for Renewable-Dominated Grids Considering Electrolyzer Virtual Inertia and Primary Frequency Response

The increasing penetration of inverter-based renewable energy sources significantly reduces power system inertia, posing severe challenges to dynamic frequency stability. Traditional frequency regulation heavily relies on the primary frequency response (PFR) of thermal units, which incurs high operational costs and lim...