Enhancement of Power Equipment Management Using Knowledge Graph
This work addresses data management inefficiencies for power system asset managers, but it is incremental as it applies an existing knowledge graph method to a specific domain.
The study tackled the problem of inefficient power equipment management due to data issues like duplication and decentralization by constructing a knowledge graph from multi-source heterogeneous data, demonstrating improved search efficiency in a 500 kV station case.
Accurate retrieval of the power equipment information plays an important role in guiding the full-lifecycle management of power system assets. Because of data duplication, database decentralization, weak data relations, and sluggish data updates, the power asset management system eager to adopt a new strategy to avoid the information losses, bias, and improve the data storage efficiency and extraction process. Knowledge graph has been widely developed in large part owing to its schema-less nature. It enables the knowledge graph to grow seamlessly and allows new relations addition and entities insertion when needed. This study proposes an approach for constructing power equipment knowledge graph by merging existing multi-source heterogeneous power equipment related data. A graph-search method to illustrate exhaustive results to the desired information based on the constructed knowledge graph is proposed. A case of a 500 kV station example is then demonstrated to show relevant search results and to explain that the knowledge graph can improve the efficiency of power equipment management.