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Keywords

Neo4j graph database; power system; comprehensive energy; search engine; knowledge graph; front-end coding; back-end coding; search efficiency

Abstract

At present, the scale of the power grid is expanding, and the amount of knowledge in power systems is increasing explosively. In order to organize, manage, and utilize mass knowledge effectively, knowledge graph technology is introduced into the field of power systems and comprehensive energy systems. Common relational databases of Oracle and structured query language (SQL) need to use tables to store data and query and analyze data through complex relationships, which is more complicated when dealing with complex relationships. The Neo4j graph database represents data as nodes and edges, which makes the correlation between entities and relationships intuitively expressed and stored, and it is especially suitable for application scenarios that need to deal with complex relationships and conduct graph analysis. Therefore, a research method for power system and comprehensive energy system knowledge graph based on the Neo4j graph database is proposed. By introducing knowledge graph technology into the power system and comprehensive energy, the power knowledge is stored in an orderly manner by using the Neo4j graph database. Then, a knowledge graph of the power field is built, and a search engine with a B/S framework is designed, realizing the interactive function between users and knowledge graph through front-end coding and handling the data related to knowledge graph through back-end coding, including data storage, query, update, and other operations. The test results show that this method can effectively improve the search efficiency of knowledge graphs of power systems and comprehensive energy systems and enhance the retrieval speed of massive data.

DOI

10.19781/j.issn.1673-9140.2025.03.023

First Page

211

Last Page

221

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