17 citations · 32 across the 3 of their papers we have counts for
3 papers
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…
Direct Load Control of Thermostatically Controlled Loads Based on Sparse Observations Using Deep Reinforcement Learning
Frederik Ruelens, Bert J. Claessens, Peter Vrancx +2
This paper considers a demand response agent that must find a near-optimal sequence of decisions based on sparse observations of its environment. Extracting a relevant set of featu…
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…