skip to main content
DOE PAGES title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Gnu-RL: A Practical and Scalable Reinforcement Learning Solution for Building HVAC Control Using a Differentiable MPC Policy

Authors:
; ;
Publication Date:
Sponsoring Org.:
USDOE
OSTI Identifier:
1712809
Resource Type:
Published Article
Journal Name:
Frontiers in Built Environment
Additional Journal Information:
Journal Name: Frontiers in Built Environment Journal Volume: 6; Journal ID: ISSN 2297-3362
Publisher:
Frontiers Media SA
Country of Publication:
Country unknown/Code not available
Language:
English

Citation Formats

Chen, Bingqing, Cai, Zicheng, and Bergés, Mario. Gnu-RL: A Practical and Scalable Reinforcement Learning Solution for Building HVAC Control Using a Differentiable MPC Policy. Country unknown/Code not available: N. p., 2020. Web. https://doi.org/10.3389/fbuil.2020.562239.
Chen, Bingqing, Cai, Zicheng, & Bergés, Mario. Gnu-RL: A Practical and Scalable Reinforcement Learning Solution for Building HVAC Control Using a Differentiable MPC Policy. Country unknown/Code not available. https://doi.org/10.3389/fbuil.2020.562239
Chen, Bingqing, Cai, Zicheng, and Bergés, Mario. Fri . "Gnu-RL: A Practical and Scalable Reinforcement Learning Solution for Building HVAC Control Using a Differentiable MPC Policy". Country unknown/Code not available. https://doi.org/10.3389/fbuil.2020.562239.
@article{osti_1712809,
title = {Gnu-RL: A Practical and Scalable Reinforcement Learning Solution for Building HVAC Control Using a Differentiable MPC Policy},
author = {Chen, Bingqing and Cai, Zicheng and Bergés, Mario},
abstractNote = {},
doi = {10.3389/fbuil.2020.562239},
journal = {Frontiers in Built Environment},
number = ,
volume = 6,
place = {Country unknown/Code not available},
year = {2020},
month = {11}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
https://doi.org/10.3389/fbuil.2020.562239

Save / Share:

Works referenced in this record:

Advanced Building Control via Deep Reinforcement Learning
journal, February 2019


OpenBuild : An integrated simulation environment for building control
conference, September 2015

  • Gorecki, Tomasz T.; Qureshi, Faran A.; Jones, Colin N.
  • 2015 IEEE Conference on Control Applications (CCA)
  • DOI: 10.1109/CCA.2015.7320826

Practical implementation and evaluation of deep reinforcement learning control for a radiant heating system
conference, November 2018

  • Zhang, Zhiang; Lam, Khee Poh
  • BuildSys '18: The 5th ACM International Conference on Systems for Built Environments, Proceedings of the 5th Conference on Systems for Built Environments
  • DOI: 10.1145/3276774.3276775

Model-predictive control for non-domestic buildings: a critical review and prospects
journal, March 2016


Real-Time Fine Grained Occupancy Estimation Using Depth Sensors on ARM Embedded Platforms
conference, April 2017

  • Munir, Sirajum; Arora, Ripudaman Singh; Hesling, Craig
  • 2017 IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS)
  • DOI: 10.1109/RTAS.2017.8

Deep Reinforcement Learning for Building HVAC Control
conference, June 2017

  • Wei, Tianshu; Wang, Yanzhi; Zhu, Qi
  • DAC '17: The 54th Annual Design Automation Conference 2017, Proceedings of the 54th Annual Design Automation Conference 2017
  • DOI: 10.1145/3061639.3062224

Learning from Demonstration for Autonomous Navigation in Complex Unstructured Terrain
journal, June 2010

  • Silver, David; Bagnell, J. Andrew; Stentz, Anthony
  • The International Journal of Robotics Research, Vol. 29, Issue 12
  • DOI: 10.1177/0278364910369715

Optimizing zone temperature setpoint excitation to minimize training data for data-driven dynamic building models
conference, July 2016


Evaluation of Reinforcement Learning for Optimal Control of Building Active and Passive Thermal Storage Inventory
journal, October 2006

  • Liu, Simeng; Henze, Gregor P.
  • Journal of Solar Energy Engineering, Vol. 129, Issue 2
  • DOI: 10.1115/1.2710491

Ten questions concerning model predictive control for energy efficient buildings
journal, August 2016


Review of building energy modeling for control and operation
journal, September 2014


Reducing Transient and Steady State Electricity Consumption in HVAC Using Learning-Based Model-Predictive Control
journal, January 2012


Reinforcement learning for optimal control of low exergy buildings
journal, October 2015


Development of whole-building energy performance models as benchmarks for retrofit projects
conference, December 2011

  • Karaguzel, Omer Tugrul; Lam, Khee Poh
  • 2011 Winter Simulation Conference - (WSC 2011), Proceedings of the 2011 Winter Simulation Conference (WSC)
  • DOI: 10.1109/WSC.2011.6147810

Sim-to-Real Transfer of Robotic Control with Dynamics Randomization
conference, May 2018

  • Peng, Xue Bin; Andrychowicz, Marcin; Zaremba, Wojciech
  • 2018 IEEE International Conference on Robotics and Automation (ICRA)
  • DOI: 10.1109/ICRA.2018.8460528

EKF based self-adaptive thermal model for a passive house
journal, January 2014


Modeling and forecasting energy consumption for heterogeneous buildings using a physical–statistical approach
journal, April 2015


Experimental analysis of data-driven control for a building heating system
journal, June 2016


Modeling and identification of a large multi-zone office building
conference, September 2011

  • Privara, Samuel; Vana, Zdenek; Gyalistras, Dimitrios
  • Control (MSC), 2011 IEEE International Conference on Control Applications (CCA)
  • DOI: 10.1109/CCA.2011.6044402

Reinforcement learning for energy conservation and comfort in buildings
journal, July 2007


Building modeling as a crucial part for building predictive control
journal, January 2013


Gnu-RL: A Precocial Reinforcement Learning Solution for Building HVAC Control Using a Differentiable MPC Policy
conference, November 2019

  • Chen, Bingqing; Cai, Zicheng; Bergés, Mario
  • BuildSys '19: The 6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation, Proceedings of the 6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation
  • DOI: 10.1145/3360322.3360849

Parameter identifiability for multi-zone building models
conference, December 2012

  • Agbi, Clarence; Song, Zhen; Krogh, Bruce
  • 2012 IEEE 51st Annual Conference on Decision and Control (CDC), 2012 IEEE 51st IEEE Conference on Decision and Control (CDC)
  • DOI: 10.1109/CDC.2012.6425995

Handling model uncertainty in model predictive control for energy efficient buildings
journal, July 2014