Big-data storage method based on Neo4j graph database

Abstract

The invention relates to a big-data storage method based on a Neo4j graph database. A modeling manner of a public information model in a power system is used as a reference to uniformity model physical network topology of an energy internet system with the power system as a core; a topology model including comprehensive data of equipment configurations, machine accounts and geographic locations, real-time data of measurement, electricity prices and weather and relationships among the same is stored into the Neo4j graph database; and data such as history data and prediction data of which complex relationships with other objects in an energy internet do not exist are stored into a relational database, and location information of the relational database is stored in the graph database. According to the method of the invention, the respective advantages of the Neo4j graph database and the relational database are combined to carry out classified storage on big data in the energy internet, aPB-level amount of data therein can be effectively processed, and access efficiency of the data is improved; and at the same time, the storage manner is very good in extensibility, and has wide application prospects.

Description

technical field [0001] The invention belongs to the field of big data analysis of the energy internet, and relates to a big data storage method based on a Neo4j graph database. Background technique [0002] With the development of the Energy Internet, the energy power system, which is characterized by the closed-loop operation of various network systems such as electricity, distributed renewable energy, and transportation, will gradually integrate with the information system into a large energy system. Reliable, high-efficiency, and low-cost storage is the premise for discovering the value hidden in energy Internet big data, and the basis for supporting the coordinated utilization of new energy and the economic operation of multi-source systems. The data sources of the Energy Internet not only cover hundreds of millions of devices in energy production, transmission, trading, and consumption, but also include external data sources such as weather, traffic, and electricity pri...

AI Technical Summary

Problems solved by technology

The relational model is suitable for storing structured data and provides a convenient data query method through the SQL query language. It is mainly used in the operational processing of transactions, but it cannot meet the needs of fast access and analysis of energy Internet big data. The limitations are: ① storage Due to capacity limitations, relational databases can effectively handle TB-level data, but it is currently difficult to handle PB-level data volumes in large energy systems; Poor scalability and application-specific design features make it difficult to deal with massive and complex data

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