Multilayer perception based reinforcement learning supervisory control of energy systems with application to a nuclear steam supply system-Reference-Cited by-同舟云学术

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Multilayer perception based reinforcement learning supervisory control of energy systems with application to a nuclear steam supply system

Published:2020-02 Issue: Volume:259 Page:114193
ISSN:0306-2619
Container-title:Applied Energy
language:en
Short-container-title:Applied Energy

Author:

Dong Zhe^ORCID,Huang Xiaojin,Dong Yujie,Zhang Zuoyi

Funder

National S&T Major Project of China

Natural Science Foundation of China

Opening Fund of State Key Laboratory of Nuclear Power Safety Monitoring Technology and Equipment

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Mechanical Engineering,General Energy,Building and Construction

Reference59 articles.

1. Application of the second law of thermodynamics to control: a review;Sangi;Energy,2019

2. Optimal control based algorithms for energy management of automotive power systems with battery/supercapacitor storage devices;Nguyen;Energy Convers Manage,2014

3. Optimal supervisory control of steam generator in parallel;Costanza;Energy,2015

4. H2-optimal transactive control of electric power regulation from fast-acting demand response in the presence of high renewables;Chassin;Appl Energy,2017

5. Combination of Markov chain and optimal control solved by Pontryagin’s minimum principle for a fuel cell/supercapacitor vehicle;Hemi;Energy Convers Manage,2015

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1. Coordinated discrete-time super-twisting sliding mode controller coupled with time-delay estimator for PWR-based nuclear steam supply system;Energy;2024-08

2. Possibilities of reinforcement learning for nuclear power plants: Evidence on current applications and beyond;Nuclear Engineering and Technology;2024-06

3. Uncertainty-aware deep learning for reliable health monitoring in safety-critical energy systems;Energy;2024-03

4. Deep learning prediction of photocatalytic water splitting for hydrogen production under natural light based on experiments;Energy Conversion and Management;2024-02

5. Small Modular Reactors: An Overview of Modeling, Control, Simulation, and Applications;IEEE Access;2024

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