Reinforcement learning for whole-building HVAC control and demand response
This paper proposes a novel reinforcement learning (RL) architecture for the efficient scheduling and control of the heating, ventilation and air conditioning (HVAC) system in a commercial building while harnessing its demand response (DR) potentials. With advances in automated building management s...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2020-11-01
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| Series: | Energy and AI |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666546820300203 |