203 citations · 527 across the 13 of their papers we have counts for
4 papers · 1 filter
Reinforcement Learning Applied to an Electric Water Heater: From Theory to Practice
Frederik Ruelens, Bert Claessens, Salman Quaiyum +3
Electric water heaters have the ability to store energy in their water buffer without impacting the comfort of the end user. This feature makes them a prime candidate for residenti…
Experimental analysis of data-driven control for a building heating system
Giuseppe Tommaso Costanzo, Sandro Iacovella, Frederik Ruelens +2
Driven by the opportunity to harvest the flexibility related to building climate control for demand response applications, this work presents a data-driven control approach buildin…
Learning Agent for a Heat-Pump Thermostat With a Set-Back Strategy Using Model-Free Reinforcement Learning
Frederik Ruelens, Sandro Iacovella, Bert J. Claessens +1
The conventional control paradigm for a heat pump with a less efficient auxiliary heating element is to keep its temperature set point constant during the day. This constant temper…
Residential Demand Response Applications Using Batch Reinforcement Learning
Frederik Ruelens, Bert Claessens, Stijn Vandael +3
Driven by recent advances in batch Reinforcement Learning (RL), this paper contributes to the application of batch RL to demand response. In contrast to conventional model-based ap…