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Multi-task deep reinforcement learning for intelligent multi-zone residential HVAC control

Journal Article · · Electric Power Systems Research
 [1];  [1];  [2];  [2];  [2];  [2];  [2]
  1. Univ. of Tennessee, Knoxville, TN (United States)
  2. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
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In this short communication, a data-driven deep reinforcement learning (deep RL) method is applied to minimize HVAC users’ energy consumption costs while maintaining users’ comfort. The applied deep RL method's efficiency is enhanced by conducting multi-task learning that can achieve an economic control strategy for a multi-zone residential HVAC system in both cooling and heating scenarios. The applied multi-task deep RL method is compared with a rule-based benchmark case and a single-task deep deterministic policy gradient algorithm to verify its effective and generalized application in optimizing HVAC operation.
Research Organization:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Sponsoring Organization:
USDOE; National Science Foundation (NSF)
Grant/Contract Number:
AC05-00OR22725
OSTI ID:
1807287
Alternate ID(s):
OSTI ID: 1781191
Journal Information:
Electric Power Systems Research, Journal Name: Electric Power Systems Research Vol. 192; ISSN 0378-7796
Publisher:
ElsevierCopyright Statement
Country of Publication:
United States
Language:
English

References (5)

Deep Reinforcement Learning for Smart Home Energy Management journal April 2020
DeepComfort: Energy-Efficient Thermal Comfort Control in Buildings Via Reinforcement Learning journal September 2020
From AlphaGo to Power System AI: What Engineers Can Learn from Solving the Most Complex Board Game journal March 2018
An Evaluation of the HVAC Load Potential for Providing Load Balancing Service journal September 2012
On-Line Building Energy Optimization Using Deep Reinforcement Learning journal July 2019

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Related Subjects

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION
Data-driven
Deep deterministic policy gradient (DDPG)
Multi-task deep reinforcement learning
Multi-zone HVAC