Paper
1 June 2023 Research on time-varying state prediction of distribution lines based on support vector machine algorithm
Qingfu Su
Author Affiliations +
Proceedings Volume 12625, International Conference on Mathematics, Modeling, and Computer Science (MMCS2022); 126252N (2023) https://doi.org/10.1117/12.2671156
Event: International Conference on Mathematics, Modeling and Computer Science (MMCS2022),, 2022, Wuhan, China
Abstract
Because the distribution line will be affected by internal and external factors in the working state, leading to the transition of the operating state, so the accurate prediction of the distribution line working state, is the current distribution network regulation and operation of the basic condition. According to the distribution circuit of power supply in recent years, as an important part of power distribution system, the basic role bear the substation and distribution of electrical energy, electric energy to power unit, research on power distribution line inspection regularly, can fully grasp the running state of the circuit, discover the problems of these defects, in order to improve the reliability of power supply system, Reduce the probability of line accidents. Therefore, on the basis of understanding the research status of distribution line state prediction, according to the basic content of support vector machine algorithm, this paper puts forward a time-varying state prediction method of distribution line based on support vector machine algorithm. Finally, the experimental results show that the algorithm is effective in the distribution system.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Qingfu Su "Research on time-varying state prediction of distribution lines based on support vector machine algorithm", Proc. SPIE 12625, International Conference on Mathematics, Modeling, and Computer Science (MMCS2022), 126252N (1 June 2023); https://doi.org/10.1117/12.2671156
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KEYWORDS
Support vector machines

Education and training

Statistical analysis

Data modeling

Machine learning

Detection and tracking algorithms

Evolutionary algorithms

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