Paper
6 February 2024 Study on distribution network operation state evaluation based on set pair analysis and evidence theory
Shijing Chen, Jingfen Zhang, Yingcai Wei, Minqiang Li, Fei Xiao
Author Affiliations +
Proceedings Volume 12979, Ninth International Conference on Energy Materials and Electrical Engineering (ICEMEE 2023); 129796N (2024) https://doi.org/10.1117/12.3015501
Event: 9th International Conference on Energy Materials and Electrical Engineering (ICEMEE 2023), 2023, Guilin, China
Abstract
In recent years, with the continuous improvement of China's comprehensive national strength, the requirements for the safe and stable operation of the distribution network in the power system have been continuously increasing. The distribution network is the part of the power system that directly connects with the users, and the improvement of its safety and reliability implies an improvement in people's living standards. In this study, based on relevant regulations at home and abroad, and combined with expert experience, an indicator system and evaluation model for assessing the operational status of the distribution network were established. The model first adopts the set pair analysis method to handle uncertainties and generate trust distribution functions. Then, the trust distribution functions of various factors are fused with evidence to obtain the final membership relations. Subsequently, the operational status of the distribution network is evaluated using the maximum membership principle based on confidence criteria. Finally, the effectiveness of the proposed method is verified through practical case analysis, demonstrating the reliability of the evaluation results.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Shijing Chen, Jingfen Zhang, Yingcai Wei, Minqiang Li, and Fei Xiao "Study on distribution network operation state evaluation based on set pair analysis and evidence theory", Proc. SPIE 12979, Ninth International Conference on Energy Materials and Electrical Engineering (ICEMEE 2023), 129796N (6 February 2024); https://doi.org/10.1117/12.3015501
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KEYWORDS
Reliability

Data modeling

Power grids

Power supplies

Analytics

Safety

3D modeling

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