17 citations · 32 across the 3 of their papers we have counts for
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eess.SY2022★ 7 cited
Combined Peak Reduction and Self-Consumption Using Proximal Policy Optimization
Thijs Peirelinck, Chris Hermans, Fred Spiessens +1
Residential demand response programs aim to activate demand flexibility at the household level. In recent years, reinforcement learning (RL) has gained significant attention for th…
eess.SY2017★ 17 cited
Using Reinforcement Learning for Demand Response of Domestic Hot Water Buffers: a Real-Life Demonstration
Oscar De Somer, Ana Soares, Tristan Kuijpers +3
This paper demonstrates a data-driven control approach for demand response in real-life residential buildings. The objective is to optimally schedule the heating cycles of the Dome…