Transforming Energy Management with an AI-Enabled Digital Twin
Преобразование управления энергией с помощью цифрового двойника на основе искусственного интеллекта
2025-01-01
SCID: 54.1/ez5xman9
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AI-enabled digital twincyber-physical systemdistrict heatingenergy efficiencyreal-time network representation
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Abstract (AI)
Digital twins (DTs) are increasingly adopted by organizations across various sectors. We report on how one of Europe’s largest district heating providers implemented an AI-assisted DT in pursuit of energy efficiency and sustainability. The solution enabled the company to modernize its complex cyber-physical system (CPS) and tap into its rich data capabilities to gain a comprehensive real-time representation of the entire district heating network. Reflecting on the case study, we provide six recommendations for executives in other domains aiming to implement DTs.
Key Findings
1
A European district heating provider implemented an AI-assisted digital twin to pursue improved energy efficiency and sustainability.
2
The case study derives six recommendations for executives implementing digital twins in other domains.
3
The digital twin modernized the provider’s complex cyber-physical system and integrated its extensive data capabilities.
4
The solution created a comprehensive real-time representation of the entire district heating network.
Research Object
the district heating network and its AI-assisted digital twin
Research Subject
real-time energy management for energy efficiency and sustainability through AI-assisted digital-twin-enabled modernization of the network’s cyber-physical system
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Publication Date
2025-01-01
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