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<p>Accompanied by the rapid development of the economy and the great strides of reform, the whole society puts forward higher and higher requirements for the safety and stability of the power grid, and the frequent power outage events will bring great losses to the power enterprises. In this paper, we employ the linear encoding function in the MAGNN method to linearly process the risk factors associated with frequent power outages in electric power enterprises. We then assign weights to these linearly processed risk factor vectors using a graph attention mechanism. Finally, we apply the correction matrix of outage risk factors to identify the risk of power outages in electric power enterprises and design an intelligent power outage control system. The study discovered that 10 kV system failure is the primary cause of frequent outages in Power Enterprise-A. The number of failures occurred 129 times due to 10kV feeder system failures in rural distribution networks. The study also reveals that the implementation of an intelligent outage control system resulted in a 73.60% year-over-year decrease in the reliability loss of fault outages in power enterprise A, thereby effectively addressing the issue of frequent outages and reducing the economic losses incurred by power enterprises. This paper provides an effective method for resolving frequent power outages in electric power enterprises and provides a guiding direction for improving power supply reliability in electric power enterprises.</p>
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Accompanied by the rapid development of the economy and the great strides of reform, the whole society puts forward higher and higher requirements for the safety and stability of the power grid, and the frequent power outage events will bring great losses to the power enterprises. In this paper, we employ the linear encoding function in the MAGNN method to linearly process the risk factors associated with frequent power outages in electric power enterprises. We then assign weights to these linearly processed risk factor vectors using a graph attention mechanism. Finally, we apply the correction matrix of outage risk factors to identify the risk of power outages in electric power enterprises and design an intelligent power outage control system. The study discovered that 10 kV system failure is the primary cause of frequent outages in Power Enterprise-A. The number of failures occurred 129 times due to 10kV feeder system failures in rural distribution networks. The study also reveals that the implementation of an intelligent outage control system resulted in a 73.60% year-over-year decrease in the reliability loss of fault outages in power enterprise A, thereby effectively addressing the issue of frequent outages and reducing the economic losses incurred by power enterprises. This paper provides an effective method for resolving frequent power outages in electric power enterprises and provides a guiding direction for improving power supply reliability in electric power enterprises.

Research on the Root Cause Analysis and Governance Measures of Frequent Power Outages in Electric Power Enterprises

Limited Smart Distribution Network Center State Grid Jibei Electric Power Company, Qinhuangdao

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

Accompanied by the rapid development of the economy and the great strides of reform, the whole society puts forward higher and higher requirements for the...

Research on the Root Cause Analysis and Governance Measures of Frequent Power Outages in Electric Power Enterprises

Publié en ligne: 05 août 2024

Pages: -

Reçu: 30 mars 2024

Accepté: 25 juin 2024

DOI: https://doi.org/10.2478/amns-2024-1861

Mots clés
MAGNN, Linear coding function, Graph attention mechanism, Correction matrix, Frequent power outage, Electric power enterprise

© 2024 Zhixin Wang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Research on the Root Cause Analysis and Governance Measures of Frequent Power Outages in Electric Power Enterprises

Publié en ligne: 05 août 2024

Pages: -

Reçu: 30 mars 2024

Accepté: 25 juin 2024

DOI: https://doi.org/10.2478/amns-2024-1861

Mots clésMAGNN, Linear coding function, Graph attention mechanism, Correction matrix, Frequent power outage, Electric power enterprise

© 2024 Zhixin Wang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Mots clés
MAGNN, Linear coding function, Graph attention mechanism, Correction matrix, Frequent power outage, Electric power enterprise