Power distribution and consumption big data information interaction system

Abstract

The invention relates to a power distribution and consumption big data information interaction system comprising a multi-source heterogeneous data information model layer, a pretreatment layer, an information transmission layer, an information organizing layer and an application layer distributed in sequence from the bottom up, wherein the multi-source heterogeneous data information model layer isused for achieving data interaction with the application layer via an API interface, and comprises multiple databases; the pretreatment layer is used for pretreating multi-source heterogeneous data;the information transmission layer is used for transmitting the pretreated data; the information organizing layer is used for providing a data interface between the databases in the multi-source heterogeneous data information model and the application layer, and synchronously updating the data in the main database and each sub-database in the multi-source heterogeneous data information model; andthe application layer is used for being connected with the multi-source heterogeneous data information model via the API application interface, and achieving data transmission and application. Compared with the prior art, the system provided by the invention has the advantages of ensuring security and reliability of data, improving data quality, being capable of recovering via self-healing and being good in adaptability and expansibility.

Description

technical field [0001] The invention relates to the technical field of power distribution and utilization information interaction and protection, in particular to a big data information interaction system for power distribution and utilization. Background technique [0002] During the construction of the smart grid, a large amount of structured and semi-structured data will be generated in the operation of power system equipment, equipment status monitoring, user electricity consumption information collection, power distribution business and marketing system. [0003] Big data is characterized by dispersion, diversity, and complexity. In order to realize functions such as power consumption forecasting, peak-shift scheduling, user power consumption behavior characteristics analysis, load forecasting, grid optimization, power-saving technology and other functions of the smart distribution network big data platform, data from multiple power distribution information systems are ...

AI Technical Summary

Problems solved by technology

The simple protection model cannot guarantee the integrity and reliability of the engineering data in the GIM model (grid information model, power grid information model). Repeatability, repeatability and incompleteness are very likely to cause problems such as slow data transmission speed and secondary data damage, and cannot guarantee the safety and reliability of engineering data

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