Carbon emission monitoring model of digital power grid user side based on cloud platform

Yingjie Li; Zeqi Zhang; Zhe Chen

doi:10.1117/12.3004395

25 September 2023 Carbon emission monitoring model of digital power grid user side based on cloud platform

Yingjie Li, Zeqi Zhang, Zhe Chen

Proceedings Volume 12788, Second International Conference on Energy, Power, and Electrical Technology (ICEPET 2023); 1278826 (2023) https://doi.org/10.1117/12.3004395
Event: Second International Conference on Energy, Power, and Electrical Technology (ICEPET 2023), 2023, Kuala Lumpur, Malaysia

Abstract

Conventional digital grid user side power carbon emission monitoring model mainly determines model parameters based on autoregressive condition heteroscedasticity, which is vulnerable to the lag effect of constraints, resulting in poor monitoring effect of the model. Therefore, a new digital grid user side power carbon emission monitoring model needs to be designed based on the cloud platform. That is to say, the cloud platform is used to obtain the monitoring data of power carbon emissions at the grid user side, and then combined with the carbon load active power relationship, the digital grid user side power carbon emissions monitoring mathematical model is constructed, which realizes effective carbon emissions monitoring. The case analysis results show that the designed carbon emission monitoring model on the user side of the digital power grid based on the cloud platform has a good monitoring effect, and the carbon emission intensity of each node monitored is more consistent with the actual carbon emission intensity, which proves that the designed model has good performance, reliability, and certain application value, and has made certain contributions to the development of subsequent grid operation schemes.

Citation Download Citation

Yingjie Li, Zeqi Zhang, and Zhe Chen "Carbon emission monitoring model of digital power grid user side based on cloud platform", Proc. SPIE 12788, Second International Conference on Energy, Power, and Electrical Technology (ICEPET 2023), 1278826 (25 September 2023); https://doi.org/10.1117/12.3004395

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