Author(s)

Liang Zhou ¹

Affiliation(s)

¹ State Grid Shanghai Economic Research Institute, State Grid Corporation of China Co., Ltd, Shanghai, China

Corresponding Author

Liang Zhou

ABSTRACT

The increasing demand for electricity in China necessitates expanding and optimizing power infrastructure projects. However, these projects are often complex, involving numerous stakeholders and heterogeneous data sources. This study investigates the application of digital twin technology in power infrastructure projects to address these challenges. A comprehensive framework integrating Building Information Modeling (BIM), digital twin technology, semantic web technologies, and artificial intelligence is proposed to enhance project management and operational efficiency. The framework's effectiveness was validated through a case study conducted at a power infrastructure construction site in Ma Shan. Multi-sensor platforms were deployed to collect environmental data, which was then integrated using semantic web technologies into a unified RDF format. A web-based platform was developed to display this data in real-time. This enables continuous monitoring and proactive management of environmental conditions. The results demonstrated the successful integration of heterogeneous data and the ability to monitor and manage environmental conditions in real-time. The study highlights the potential of digital twin technology to improve the design, construction, and maintenance phases of power infrastructure projects. Future research should explore the expansion of this framework to other infrastructure domains to maximize its benefits.

KEYWORDS

Digital twin, Power infrastructure projects, Semantic web, Artificial intelligence, Data integration

CITE THIS PAPER

Liang Zhou, A Digital Twinning Framework for Power Infrastructure Projects. Journal of Civil Engineering and Urban Planning (2024) Vol. 6: 157-164. DOI: http://dx.doi.org/10.23977/jceup.2024.060221.

REFERENCES

[1] J. Zhou, L. Li, and Y. Bai, "Power grid engineering data knowledge retrieval and graph construction technology," in 2022 IEEE 5th International Electrical and Energy Conference (CIEEC), 2022, pp. 104-108. https://doi.org/10. 1109/CIEEC54735.2022.9846460
[2] Q. Lu, L. Chen, S. Li, and M. Pitt, "Semi-automatic geometric digital twinning for existing buildings based on images and CAD drawings," Automation in Construction, vol. 115, 103183, 2019. https://doi.org/10.1016/j. autcon. 2020. 103183
[3] Q. Lu et al., "Developing a digital twin at building and city levels: Case study of West Cambridge campus," Journal of Management in Engineering, vol. 36, no. 3, 05020004, 2020. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000763
[4] D. Bryde, M. Broquetas, and J. M. Volm, "The project benefits of building information modelling (BIM)," International Journal of Project Management, vol. 31, no. 7, pp. 971-980, 2013. https://doi.org/10.1016/j. ijproman. 2012.12.001
[5] L. Chen, Q. Lu, and X. Zhao, "A semi-automatic image-based object recognition system for constructing as-is IFC BIM objects based on fuzzy-MAUT," International Journal of Construction Management, vol. 22, no. 1, pp. 51-65, 2022. https://doi.org/10.1080/15623599.2020.1768624
[6] C. Kiamili, A. Hollberg, and G. Habert, "Detailed assessment of embodied carbon of HVAC systems for a new office building based on BIM," Sustainability, vol. 12, no. 8, 3372, 2020. https://doi.org/10.3390/su12083372
[7] D. Chen, S. Cheng, J. Hu, M. Kasoar, and R. Arcucci, "Explainable global wildfire prediction digital twin model using graph neural networks," arXiv preprint arXiv: 2402.07152, 2024. https://arxiv.org/abs/2402.07152
[8] T. Berners-Lee, J. Hendler, and O. Lassila, "The semantic web," Scientific American, 2001. https://doi.org/ 10. 1038/scientificamerican0501-34
[9] M. Alazab, S. Khan, S. S. R. Krishnan, Q. V. Pham, M. P. K. Reddy, and T. R. Gadekallu, "A multidirectional LSTM model for predicting the stability of a smart grid," IEEE Access, vol. 8, pp. 85454-85463, 2020. https://doi.org/10. 1109/ACCESS.2020.2992995

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