105 citations · 265 across the 13 of their papers we have counts for
5 papers · 1 filter
Physically Consistent Neural Networks for building thermal modeling: theory and analysis
Loris Di Natale, Bratislav Svetozarevic, Philipp Heer +1
Due to their high energy intensity, buildings play a major role in the current worldwide energy transition. Building models are ubiquitous since they are needed at each stage of th…
Physics-informed linear regression is competitive with two Machine Learning methods in residential building MPC
Felix Bünning, Benjamin Huber, Adrian Schalbetter +5
Because physics-based building models are difficult to obtain as each building is individual, there is an increasing interest in generating models suitable for building MPC directl…
Experimental implementation of an emission-aware prosumer with online flexibility quantification and provision
Hanmin Cai, Philipp Heer
Active building energy management holds potential to reduce global energy-related emissions and support flexible operations of future low-carbon systems. This requires to integrate…
Data-Driven Demand-Side Flexibility Quantification: Prediction and Approximation of Flexibility Envelopes
Nami Hekmat, Hanmin Cai, Thierry Zufferey +2
Real-time quantification of residential building energy flexibility is needed to enable a cost-efficient operation of active distribution grids. A promising means is to use the so-…
Data-driven control of room temperature and bidirectional EV charging using deep reinforcement learning: simulations and experiments
B. Svetozarevic, C. Baumann, S. Muntwiler +3
This work presents a fully data-driven, black-box pipeline to obtain an optimal control policy for a multi-loop building control problem based on historical building and weather da…