C013 -- Winter Natural Ventilation Control With Operable Windows: Application Of Statistical Simulation in the Transformation From Predictive Control To Reinforcement Learning Control PDF

C013 -- Winter Natural Ventilation Control With Operable Windows: Application Of Statistical Simulation in the Transformation From Predictive Control To Reinforcement Learning Control PDF

Name:
C013 -- Winter Natural Ventilation Control With Operable Windows: Application Of Statistical Simulation in the Transformation From Predictive Control To Reinforcement Learning Control PDF

Published Date:
2022

Status:
Active

Description:

Publisher:
ASHRAE

Document status:
Active

Format:
Electronic (PDF)

Delivery time:
10 minutes

Delivery time (for Russian version):
200 business days

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Natural ventilation is a promising passive technology to improve building energy performance and indoor air quality. However, the control of natural ventilation is a challenge in building technology and is often missing in building system advanced control design. This paper proposes the application of Model Predictive Control (MPC) and Reinforcement Learning (RL) control for winter natural ventilation control and evaluates both through on-site control experiments. Furthermore, this paper suggests the internal connection between MPC and RL control as simulation-based control, by transforming the MPC design into RL control design. This paper also highlights the RL control as a potential solver-free solution in deployment for building systems.


File Size : 1 file , 7.9 MB
Note : This product is unavailable in Russia, Belarus
Number of Pages : 13
Product Code(s) : D-BCS22-C013
Published : 2022
Units of Measure : Dual

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