Power distribution network big data zoning processing method based on Spark calculation engine

A big data processing and data partitioning technology, which is applied in the direction of electric digital data processing, data processing applications, special data processing applications, etc., can solve the problems of data retention in distribution network, etc., and achieve the effect of improving work efficiency and fast and accurate calculation

Active Publication Date: 2018-03-16
LISHUI POWER SUPPLY COMPANY OF STATE GRID ZHEJIANG ELECTRIC POWER +1
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Problems solved by technology

[0003] It is not uncommon to apply big data technology to distribution network data analysis at home and abroad, but the current use of this framework is only limited to the clustering prediction of distribution network data, and there is no analysis of distribution network data according to the power supply unit. Carry out classification planning statistics, provide a precedent for cell load statistical analysis indicators display services directly related to users

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  • Power distribution network big data zoning processing method based on Spark calculation engine
  • Power distribution network big data zoning processing method based on Spark calculation engine
  • Power distribution network big data zoning processing method based on Spark calculation engine

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Embodiment Construction

[0038] The present invention will be described in detail below in conjunction with the accompanying drawings.

[0039] A method for processing big data partitions of distribution network based on Spark computing engine, comprising the following steps:

[0040] Step 1: Build a distribution network big data processing platform, and use the power consumption information collection system and PMS as data sources to analyze urban loads;

[0041] The distribution network big data processing platform, such as figure 1As shown, using Linux Ubuntu as the operating system, based on Hadoop and Spark framework, is divided into data storage layer, data management layer and data calculation layer; Discrete storage and query; the data management layer uses the Hive component of Hadoop to build a data table for the load data, including distribution transformer ID, date, distribution transformer load data, distribution transformer longitude, and distribution transformer latitude; Convert the...

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Abstract

The invention discloses a power distribution network big data zoning processing method based on a Spark calculation engine. According to a power supply cell, mass load data is subjected to statisticalanalysis, and a power index with a practical value for power distribution network planning management is extracted. The method comprises the following steps that: S1: building a power distribution network big data processing platform, and carrying out city load analysis by taking a power utilization information collection system and a PMS PMS(Production Management System) as a data source; S2: importing data in the data source into Spark to serve as RDD (Resilient Distributed Datasets), and preprocessing the city load data in the RDD; S3: according to a power distribution transformer coordinate in the city load data, distinguishing the cell for the power distribution transformer; and S4:according to S2 and S3, calculating the city load index.

Description

technical field [0001] The invention relates to a calculation method for processing and calculating big data of distribution network by using computer technology, and aims to extract power indicators with practical value for distribution network planning and management from massive distribution network data, which belongs to big data value mining In particular, it relates to a large data partition processing method of distribution network based on Spark computing engine. Background technique [0002] With the State Grid Corporation's strategic goal of building a strong power grid, the number of smart power consumption terminals and collection terminals is increasing day by day, which makes various types of power automation data grow geometrically, showing "large volume" and "multiple types". , "low density" and "fast growth" typical big data characteristics. In the process of distribution network management and planning, a series of data such as power load statistical indic...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30G06Q50/06
CPCG06Q50/06G06F16/182G06F16/24532G06F16/2471
Inventor 钱江宋艳杨成钢蒋玮赵汉鹰林旭义徐璟傅颖吴新华程翔陈少波
Owner LISHUI POWER SUPPLY COMPANY OF STATE GRID ZHEJIANG ELECTRIC POWER
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