Power distribution network scheduling foundation data integrating method

Abstract

The invention relates to a power distribution network scheduling foundation data integrating method.The method includes the steps of extracting data, wherein integrated system data is extracted, and the numbers of a PMS, a GIS, a scheduling service system and other service systems are transmitted to a front machine from a source end through the ETL process and converted into structural relation data to be uniformly stored and managed; verifying data, wherein converted data is extracted, and a verification rule is applied for the data to detect the integrity, correctness and logicality of the data; fusing data, wherein a fusion rule is applied for verified data to establish a logic relation among isomerous data; simplifying data, wherein data of isomerous systems is extracted on the basis of the logic relation among data, a simplifying rule is applied for the data, the content and connection relation of the data are simplified according to the simplifying rule, and data meeting scheduling requirements is output.The 'Spark+EDA' data integrating method which is suitable for meeting characteristics and requirements of all stages of power distribution networks and scheduling the power distribution networks in a targeted, adapted and operable mode is provided and can be widely applied in isomerous data integration.

Description

technical field [0001] The invention relates to a power grid data processing method, in particular to a distribution network planning basic data integration method based on "memory computing + event-driven architecture + big data". Background technique [0002] With the continuous improvement of the power industry's requirements for distribution network construction and planning, the collection of basic data for distribution network planning has become the main bottleneck for improving the lean level of distribution network planning. Distribution network data comes from multiple professional systems such as dispatching automation, production management, power grid GIS, and marketing business (SG186), with a large amount of data and complex sources; at the same time, due to the inconsistent data models and formats of each business system, the systems are independent of each other , the access interfaces are different, which makes the information exchange of the system difficu...

AI Technical Summary

Problems solved by technology

[0003] The current data integration and processing are only aimed at the large amount of data itself, but the distribution network planning data comes from multiple business systems, and the current research has less consideration for the following aspects: 1. The data sources of the distribution network are complex and the repetition rate is high and uneven

There are many distribution network business systems. Due to the lack of overall planning, in addition to GIS and PMS to achieve the same source maintenance of main equipment data, and the procurement system and marketing system to achieve the same source maintenance of metering point data, there is generally a lack of connection between various business systems , a large amount of data needs to be maintained repeatedly in different systems, and the data repetition rate is high

2. Poor data consistency and difficult linkage

Different business departments have different numbering and naming habits for data information, resulting in low data consistency and difficulty in linkage

At the same time, there are many information system research and development units, and the data standards are inconsistent with the models, resulting in the inability to unify the interface standards between systems

3. High real-time requirements for data processing

Therefore, if the above problems cannot be effectively solved, it will greatly limit the data support effect of distribution network basic data on distribution network planning.

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