19 citations · 43 across the 6 of their papers we have counts for
4 papers · 1 filter
Enhanced Imitation Learning of Model Predictive Control through Importance Weighting
Pere Izquierdo Gómez, Miguel E. López Gajardo, Nenad Mijatovic +1
The approximation of model predictive control (MPC) algorithms with neural network models has received significant attention in the power electronics research community, as a valua…
Optimal Day-Ahead Scheduling of Fast EV Charging Station With Multi-Stage Battery Degradation Model
Y. Wan, D. Gebbran, R. K. Subroto +1
The paper proposes a day-ahead scheduling framework with a novel multi-stage battery degradation modeling method for an electric vehicle (EV) fast charging station (FCS) equipped w…
Distributionally Robust Scheduling of Electrified Heating Under Heat Demand Forecast Uncertainty
Alessandro Quattrociocchi, Manisha Talukdar, Pere Izquierdo Gómez +1
Electrified heating systems with thermal storage, such as electric boilers and heat pumps, represent a major source of demand-side flexibility. Under current electricity market des…
Safety-Enhanced Self-Learning for Optimal Power Converter Control
Yihao Wan, Qianwen Xu, Tomislav Dragičević
Data-driven learning-based control methods such as reinforcement learning (RL) have become increasingly popular with recent proliferation of the machine learning paradigm. These me…