# Knowledge-Graph-Based Integrated Line Loss Evaluation Management System
## 2 Constructing a Knowledge Graph for Comprehensive Line Loss Evaluation Management
### Configuring Line Loss Management Evaluation Indicator Data Sources  
During the process of electricity transmission, electrical energy loss is caused by a number of factors, including resistance and inductance. This type of loss is an unavoidable consequence of the operation of the power system. Nevertheless, through a comprehensive understanding of the underlying causes and evolution of this phenomenon, it is possible to implement effective strategies to mitigate losses and enhance energy efficiency. Line loss is a pervasive phenomenon that affects the entire value chain of the power system. Reducing the line loss rate is a fundamental objective in the pursuit of comprehensive cost reduction and efficiency enhancement for power grid enterprises. It is also an indispensable prerequisite for attaining the \"dual carbon\" objectives [18]. In accordance with the stipulations set forth in the \"Line Loss Management Measures\" of the China Southern Power Grid, this paper seeks to collaborate with power grid enterprises in leveraging efficacious information technology tools and computational methodologies to procure, process, and analyze substantial data pertaining to the characteristics and behaviors of power grids. In light of the findings from the literature review on various indicator systems, a knowledge graph is employed to extract and construct an indicator dataset for the line loss management indicator system. In order to obtain multi-time series big data related to line loss in electricity production, this project employs distributed computing technology to collect and analyze data from three principal platforms: the power grid operation and equipment monitoring platform, the power enterprise marketing platform, and the power  
Figure 1: Knowledge graph of line loss comprehensive evaluation management.  
enterprise management platform [19]. The data types can be broadly classified into four categories, as illustrated below:  
The data set comprises information pertaining to the equipment in question. The model and rated voltage of lines, transformers, other AC/DC components, and other objects under normal operating conditions, as well as other equipment parameter information, are to be included in the model.  
Operational data comprises the following: information pertaining to operational parameters, including the voltage, current, and power, is also collected for various electrical components and objects under normal operating conditions.  
Capacity data comprise the following: the capacity data of lines, transformers, other AC/DC components, and other objects under normal operating conditions is to be provided on an hourly, daily, or monthly basis. Additionally, information on the quantity and types of electricity meters is to be included.  
Topological data may be defined as the information pertaining to the configuration and connectivity of a given system. Information pertaining to the topological connections of lines, transformers, other AC/DC components, and other objects under normal operating conditions.