# Knowledge-Graph-Based Integrated Line Loss Evaluation Management System
## 6 Conclusions  
This paper constructs a comprehensive evaluation system of line loss based on a knowledge graph, and the main conclusions are as follows:  
1. A new comprehensive evaluation management knowledge map of line loss is constructed, which is divided into three modules to effectively target the existing line loss characteristics; it is more refined than the traditional map library and describes the analysis when selecting indicators in a more detailed way.
2. A new comprehensive evaluation management system for line loss reduction is proposed based on the extraction of indicators from the knowledge map of line loss management, from which four categories and 13 types of indicators are selected to build a comprehensive evaluation model for line loss reduction. The model reacts more comprehensively to the correlation between indicators, achieves the accurate positioning of existing problems, and reduces the problem of the redundancy of similar line loss problems to increase the amount of calculation.
3. A combined evaluation method based on DEMATEL-Entropy Weight-TOPSIS is proposed, and the reliability of the evaluation method is verified through ablation experiments. After the case study of line loss in Nanning City, the authenticity and reliability of the comprehensive evaluation system for evaluating the line loss is tested, and the strengths and weaknesses of the index system are judged more accurately, reducing the probability of misjudgment.  
In the paper, the comprehensive evaluation and management system of line loss reduction is studied; with the increasingly large scale of the distribution network, the line loss situation is becoming more and more complex, and the line loss in the same area will also be due to cyclical changes in the characteristics and laws of the users' electricity consumption in the area, so it is necessary to further study to accurately grasp the real situation of the area's line loss.  
The following supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/app14209462/s1](https://www.mdpi.com/article/10.3390/app14209462/s1)]([https://www.mdpi.com/article/10.3390/app14209462/s1](https://www.mdpi.com/article/10.3390/app14209462/s1)).  
Conceptualization, B.L. and W.W.; methodology, W.W.; software, W.W.; validation, B.L. and W.W., formal analysis, W.W.; investigation, W.W.; resources, B.L.; data curation, B.L.; writing--original draft preparation, W.W.; writing--review and editing, W.W.; visualization, W.W.; supervision, B.L.; funding acquisition, B.L. All authors have read and agreed to the published version of the manuscript.  
This work was supported in part by the Natural Science Foundation of Guangxi Province under grant 2020 GXNSFAA297117.  
Not applicable.  
The data used in this study were obtained from China Southern Power Grid and have been licensed for sharing with other researchers upon request. Restrictions may apply to the availability of these data, which were used under license for this study and are not publicly available. Data are, however, available from the authors upon reasonable request and with permission from China Southern Power Grid.  
The authors declare no conflicts of interest.