Direct Load Control of Thermostatically Controlled Loads Based on Sparse Observations Using Deep Reinforcement Learning

no code implementations • 26 Jul 2017 • Frederik Ruelens, Bert J. Claessens, Peter Vrancx, Fred Spiessens, Geert Deconinck

This paper considers a demand response agent that must find a near-optimal sequence of decisions based on sparse observations of its environment.

Time Series Time Series Analysis

Model-Free Control of Thermostatically Controlled Loads Connected to a District Heating Network

no code implementations • 27 Jan 2017 • Bert J. Claessens, Dirk Vanhoudt, Johan Desmedt, Frederik Ruelens

Optimal control of thermostatically controlled loads connected to a district heating network is considered a sequential decision- making problem under uncertainty.

Decision Making

Convolutional Neural Networks For Automatic State-Time Feature Extraction in Reinforcement Learning Applied to Residential Load Control

1 code implementation • 28 Apr 2016 • Bert J. Claessens, Peter Vrancx, Frederik Ruelens

Direct load control of a heterogeneous cluster of residential demand flexibility sources is a high-dimensional control problem with partial observability.