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A large data partition processing method for distribution network based on spark computing engine

A technology of big data processing and data partitioning, applied in electrical digital data processing, data processing applications, special data processing applications, etc., can solve problems such as staying in distribution network data, and achieve the effect of improving work efficiency and fast and accurate calculation

Active Publication Date: 2021-11-19
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

Method used

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  • A large data partition processing method for distribution network based on spark computing engine
  • A large data partition processing method for distribution network based on spark computing engine
  • A large data partition processing method for distribution network based on spark computing 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 distribution network large data partition processing method based on the Spark computing engine, which performs statistical analysis on massive load data according to the power supply unit cells, and extracts power indicators that have practical value for distribution network planning and management, including the following Steps: Step 1: Build a big data processing platform for the distribution network, and use the power consumption information collection system and PMS as data sources to analyze urban loads; Step 2: Import the data in the data source into Spark to become an elastic distributed data set RDD. The urban load data in the RDD is preprocessed; step 3: divide the distribution transformer into cells according to the distribution transformer coordinates in the urban load data; step 4: calculate the urban load index according to step 2 and step 3.

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...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/182G06F16/2453G06F16/2458G06Q50/06
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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