Flexible operation and maintenance optimization of aging cyber-physical energy systems by deep reinforcement learning

Flexible operation and maintenance optimization of aging cyber-physical energy systems by deep reinforcement learning

Cyber-Physical Energy Systems (CPESs) integrate cyber and hardware components to ensure a reliable and safe physical power production and supply. Renewable Energy Sources (RESs) add uncertainty to energy demand that can be dealt with flexible operation (e.g., load-following) of CPES; at the same tim...

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Bibliographic Details
Main Authors: Zhaojun Hao, Francesco Di Maio, Enrico Zio
Format: Article
Language:English
Published: Elsevier 2024-04-01
Series:Nuclear Engineering and Technology
Subjects:
Cyber-physical energy system (CPES)
Operation & maintenance (O&M)
Cyber aging
Deep reinforcement learning (DRL)
Nuclear power plant (NPP)
Optimization
Online Access:http://www.sciencedirect.com/science/article/pii/S1738573323005521

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http://www.sciencedirect.com/science/article/pii/S1738573323005521

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