260 citations · 371 across the 19 of their papers we have counts for
21 papers
PING: physics informed graph neural network for advection-diffusion processes with applications to solar power forecasting
Jelena Simeunović, Baptiste Schubnel, Pierre-Jean Alet +2
Advection-diffusion plays an essential role in transport phenomena such as atmospheric and cloud dynamics. Improved forecasting of cloud motion, in turn, enhances solar power produ…
SolarCrossFormer: Improving day-ahead Solar Irradiance Forecasting by Integrating Satellite Imagery and Ground Sensors
Baptiste Schubnel, Jelena Simeunović, Corentin Tissier +2
Accurate day-ahead forecasts of solar irradiance are required for the large-scale integration of solar photovoltaic (PV) systems into the power grid. However, current forecasting s…
Risk-aware Scheduling and Dispatch of Flexibility Events in Buildings
Paul Scharnhorst, Baptiste Schubnel, Rafael E. Carrillo +2
Residential and commercial buildings, equipped with systems such as heat pumps (HPs), hot water tanks, or stationary energy storage, have a large potential to offer their consumpti…
Uncertainty-aware Flexibility Envelope Prediction in Buildings with Controller-agnostic Battery Models
Paul Scharnhorst, Baptiste Schubnel, Rafael E. Carrillo +2
Buildings are a promising source of flexibility for the application of demand response. In this work, we introduce a novel battery model formulation to capture the state evolution…
Spatio-temporal graph neural networks for multi-site PV power forecasting
Jelena Simeunović, Baptiste Schubnel, Pierre-Jean Alet +1
Accurate forecasting of solar power generation with fine temporal and spatial resolution is vital for the operation of the power grid. However, state-of-the-art approaches that com…
State space models for building control: how deep should you go?
Baptiste Schubnel, Rafael E. Carrillo, Paolo Taddeo +4
Power consumption in buildings show non-linear behaviors that linear models cannot capture whereas recurrent neural networks (RNNs) can. This ability makes RNNs attractive alternat…