The Design and Implementation of an Intelligent Carbon Data Management Platform for Digital Twin Industrial Parks

Lingyu Wang, Hairui Wang, Yingchuan Li, Xingyun Yan, Min Wang, Meixing Guo, Mingzhu Fang, Yue Kong and Jie Hu ()
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Lingyu Wang: School of Design, Shanghai Jiao Tong University, No. 800, Dongchuan Road, Minhang District, Shanghai 200240, China
Hairui Wang: School of Design and Art, Lanzhou University of Technology, No. 287, Lan Gongping Road, Qilihe District, Lanzhou 730050, China
Yingchuan Li: School of Design and Art, Lanzhou University of Technology, No. 287, Lan Gongping Road, Qilihe District, Lanzhou 730050, China
Xingyun Yan: School of Design, Shanghai Jiao Tong University, No. 800, Dongchuan Road, Minhang District, Shanghai 200240, China
Min Wang: School of Design and Art, Lanzhou University of Technology, No. 287, Lan Gongping Road, Qilihe District, Lanzhou 730050, China
Meixing Guo: School of Design and Art, Lanzhou University of Technology, No. 287, Lan Gongping Road, Qilihe District, Lanzhou 730050, China
Mingzhu Fang: School of Design, Shanghai Jiao Tong University, No. 800, Dongchuan Road, Minhang District, Shanghai 200240, China
Yue Kong: School of Design and Art, Lanzhou University of Technology, No. 287, Lan Gongping Road, Qilihe District, Lanzhou 730050, China
Jie Hu: School of Mechanical and Power Engineering, Shanghai Jiao Tong University, No. 800, Dongchuan Road, Minhang District, Shanghai 200030, China

Energies, 2024, vol. 17, issue 23, 1-22

Abstract: In the face of increasing environmental challenges, carbon emissions from industrial parks have become a global focal point, particularly as electricity consumption serves as a major source of carbon emissions that requires effective management. Despite proactive efforts by governments and industry stakeholders to transition industrial parks toward cleaner production methods, traditional energy management systems exhibit significant limitations in data collection, real-time monitoring, and intelligent analysis, making it difficult to meet the urgent demands for carbon reduction. To address these challenges, this study proposes a carbon data management approach for industrial parks based on digital twin technology and develops an intelligent system that integrates monitoring, environmental surveillance, energy management, and carbon emission monitoring. The system supports efficient energy-saving and carbon-reducing decision making by real-time collection of energy consumption data. By incorporating Building Information Modeling (BIM) and Internet of Things (IoT) technologies, the system facilitates the integration and visualization of multi-source data, significantly enhancing the transparency of carbon data. The results of the carbon reduction validation system demonstrate that the application of this platform and its associated facilities can significantly reduce carbon emissions in the park, providing robust support for the transition of industrial parks toward low-carbon and sustainable development.

Keywords: carbon emissions; digital twin; control systems; intelligent systems; Internet of Things (IoT); Building Information Modeling (BIM); sustainability; environmental monitoring (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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