Fast-apply deep autoregressive recurrent proximal policy optimization for controlling hot water systems-Reference-Cited by-同舟云学术

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Fast-apply deep autoregressive recurrent proximal policy optimization for controlling hot water systems

Published:2024-08 Issue: Volume:367 Page:123348
ISSN:0306-2619
Container-title:Applied Energy
language:en
Short-container-title:Applied Energy

Author:

Yin Linfei,Xiong Yi

Publisher

Elsevier BV

Reference44 articles.

1. China’s flexibility challenge in achieving carbon neutrality by 2060;Li;Renew Sustain Energy Rev,2022

2. Carbon reduction technology pathways for existing buildings in eight cities;Ang;Nat Commun,2023

3. Machine learning-assisted heat transport modelling for full-scale emplacement experiment at Mont Terri underground laboratory;Hu;Int J Heat Mass Transf,2023

4. Design optimization on characteristics of packed-bed thermal energy storage system coupled with high temperature gas-cooled reactor pebble-bed module;Hu;Energ Conver Manage,2022

5. Stochastic simulation of occupant-driven energy use in a bottom-up residential building stock model;Chen;Appl Energy,2022

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