Toward Smart and Green Energy Stations: A Cognitive Digital Twin Framework for Intelligent Management

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Authors: Jiaji Zhang, Jinlong Sun, Haitao Zhao, Feige Huang, Bo Xu, Qiankun Wang
Cited by: 3
References: 20

Abstract

Modern intelligent energy stations show new requirements for smart, green, and highly-efficient systems. This article presents opportunities of bridging domains of large-scale facility management and information and communication technology. By introducing cognitive digital twin technology, potential opportunities for the intelligent operation and management of energy stations can be investigated. In this study, a conceptual intelligent energy station architecture is outlined based on cognitive digital twins. Subsequently, key modules and use cases for the cognitive digital twin-aided architecture are discussed, focusing on intelligent management and optimal operations. Furthermore, this study identifies several key challenges and future research directions for realizing the proposed architecture. These include model-related, data-related, and collaboration-related issues.

Fields of Study & Subjects

Digital Transformation in Industry IoT and Edge/Fog Computing Age of Information Optimization

Publication details

Journal / source
IEEE Internet Computing
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Volume
30
Issue
2
Pages
46–55
Publication date
12 January 2026