A method and system for power grid multi-source data fusion based on multivariate heterogeneous model

Abstract

The invention discloses a power grid multi-source data fusion method and system based on a multi-element heterogeneous model. The method comprises the following steps of multi-source data access, metadata storage, unified device modeling and data extraction, model matching degree calculation and multi-element data fusion. The system mainly comprises the five modules of multi-source data access, metadata storage, unified device modeling and data extraction, model matching degree calculation and multi-element data fusion. A unified model including multi-source system data is established by deeply analyzing the multi-source system data, automatic association is performed through model traversal comparison and model matching degree calculation according to the matching degree, automatic data integration and fusion of 90% or above is achieved, unfused data details and detailed causes are accurately analyzed, integration and fusion of various service data are achieved, and the overall fusion quality is effective managed and controlled.

Description

technical field [0001] The invention relates to a multi-source data fusion method and system based on a multivariate heterogeneous model, and belongs to the technical field of intelligent control. Background technique [0002] With the continuous development of computer technology in the electric power industry, a large number of specialized information systems have appeared in the electric power industry, running through all links of power generation, power transmission, power transformation, power distribution, and power consumption. Each professional system has played a pivotal role in its own field. , in the system of State Grid Corporation, PMS, EMS, GIS, intelligent distribution network monitoring platform, electricity information collection and other systems have been widely used in the fields of transportation inspection, dispatching, marketing, etc., accumulating a large amount of data resources, and respectively through The data center provides real-time / quasi-real...

AI Technical Summary

Problems solved by technology

Although this method can achieve data fusion, there are the following problems. First, the grid equipment is large in size, and the data correspondence work is cumbersome, which requires a lot of manpower and material resources.

Second, the personnel of each data management department are not familiar with the data models and business processes of other departments, which may easily lead to high data association error rate and low association efficiency

The third is that the business process integration of each department is difficult. When the data interface of each department is changed and upgraded, the data fusion bus needs to be frequently updated and upgraded, which increases the complexity of the business process of each department.

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