Multi-mode heterogeneous power big data fusion analysis management system and method

Abstract

The invention discloses a multi-mode heterogeneous power big data fusion analysis management system which comprises a multi-source data acquisition layer for data collection of multiple data sources,a data interface layer which is corresponding to multiple data types and is provided with multiple data interfaces, a power big data fusion management subsystem which includes multiple open source databases, a big data analysis engine which includes an open source algorithm library based on a Spark parallel computing framework and achieves calculation and analysis of stored data in the open sourcedatabases by calling a corresponding analysis method in the open source algorithm library, and a model access interface layer which is connected to the big data analysis engine and the open source database and includes multiple access interfaces, wherein the access to the open source algorithm library and the open source database is achieved by the corresponding access interfaces. According to the system, the performance of data processing can be improved, a data value is fully exploited and the data asset management is realized, and a fast and efficient data management guarantee is providedfor an upper power professional model.

Description

technical field [0001] The invention relates to a large data intelligent information processing method of a power system, in particular to a multi-mode heterogeneous power big data fusion analysis management system and method. Background technique [0002] With the development of the power industry, the data involved in the power system has evolved from traditional power data to power big data, and the cross-domain space-time expansion has changed the interface conditions of the power system from deterministic to time-varying, from single to complex At the same time, it also increases the dynamic transformation of multiple time scales. In addition, electric power big data also has the "4V" salient features of general big data, namely data Volume, data type Variety, processing speed Velocity and data value Value. [0003] At present, most power facilities and data processing equipment have defects such as low processing efficiency when facing big data, which is easy to cause ...

AI Technical Summary

Problems solved by technology

[0003] At present, most power facilities and data processing equipment have defects such as low processing efficiency when facing big data, which is easy to cause a waste of a large amount of data resources, and cannot grasp the status information of the power grid system and related equipment in a timely, fast and comprehensive manner. The operation management and scientific decision-making of the power grid have brought great troubles

At the same time, the research on big data platforms at home and abroad is also relatively scattered. The architecture of big data platforms is mostly based on Hadoop technology, and the relevant technical system supporting the development of big data platforms has not yet been formed. Moreover, the existing power grid data acquisition and conversion devices at home and abroad are mainly For some key equipment and key data collection, there are still a large number of key technical issues that need to be studied urgently for the acquisition of power grids, equipment, environments, and a large number of weakly correlated, spatio-temporal power big data, and how to analyze them in real time and quickly. It can be seen that the biggest challenge faced by the existing technology is the lack of an efficient big data analysis and processing platform to effectively store power big data, combined with intelligent algorithms for efficient mining operations, and finally displayed in the form of valuable information to help power operators Quick and correct decision-making judgment

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