Toward Physics-Guided Safe Deep Reinforcement Learning for Green Data Center Cooling Control-Reference-Cited by-同舟云学术

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Toward Physics-Guided Safe Deep Reinforcement Learning for Green Data Center Cooling Control

Published:2022-05 Issue: Volume: Page:
ISSN:
Container-title:2022 ACM/IEEE 13th International Conference on Cyber-Physical Systems (ICCPS)
language:
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Author:

Wang Ruihang¹,Zhang Xinyi¹,Zhou Xin¹,Wen Yonggang¹,Tan Rui¹

Affiliation:

1. Nanyang Technological University,Singapore

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9797459/9797464/09797658.pdf?arnumber=9797658

Reference31 articles.

1. Building HVAC Scheduling Using Reinforcement Learning via Neural Network Based Model Approximation

2. PID autotuner and its application in HVAC systems;wang;ACC,2001

3. EnergyPlus: energy simulation program;crawley;ASHRAE J,2000

4. MB2C

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1. Context-aware reinforcement learning for cooling operation of data centers with an Aquifer Thermal Energy Storage;Energy and AI;2024-09

2. TESLA: Thermally Safe, Load-Aware, and Energy-Efficient Cooling Control System for Data Centers;Proceedings of the 53rd International Conference on Parallel Processing;2024-08-12

3. Radiative free cooling for energy and water saving in data centers;Applied Energy;2024-04

4. Passive daytime radiative cooling: Moving beyond materials towards real-world applications;Next Energy;2024-04

5. Computationally Efficient Reinforcement Learning: Targeted Exploration leveraging Simple Rules;2023 62nd IEEE Conference on Decision and Control (CDC);2023-12-13

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