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Improved line loss analysis method for K-means clustering

An analysis method, K-means technology, applied in data processing applications, instruments, calculations, etc., can solve the problem of line loss difference, large error, etc.

Inactive Publication Date: 2015-07-01
NANJING UNIV OF SCI & TECH
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  • Description
  • Claims
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AI Technical Summary

Problems solved by technology

This line loss method is convenient for statistics, but the error is large, and the calculated line loss is far from the actual line loss.

Method used

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  • Improved line loss analysis method for K-means clustering
  • Improved line loss analysis method for K-means clustering
  • Improved line loss analysis method for K-means clustering

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Experimental program
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Embodiment Construction

[0021] The line loss calculation process of the present invention is divided into three parts in conjunction with the accompanying drawings:

[0022] 1. Build the dataset

[0023] 1) Obtain basic and mode data: record the operation mode of the entire network on time every day, obtain telemetry and telesignal data from the dispatching SCADA and distribution network SCADA systems at certain time intervals, and transfer multiple Different types of related data of the system are integrated, analyzed in a unified manner, and transferred to the system database in a certain format to provide basic data for line loss analysis applications. The main data include Circuit, Voltage, Start Date, Close Date, Supplied Power, Sold Power, Line Loss Rate ( MLLR) etc.

[0024] 2. Build a line loss calculation model

[0025] Construct a feature index set that reflects the line loss status,

[0026] Select the average line loss rate (Average Line-Loss Rate), line loss rate standard deviation (...

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Abstract

The invention provides an improved line loss analysis method for K-means clustering. The method comprises the following steps: integrating different types of relevant data of a plurality of systems, performing unified resolution, dumping the resolved data into a system database according to a certain format to form a feature data set, and sampling the data set; determining the number of line-loss parameters, and constructing a line-loss estimation model by taking the three indexes of average line-loss rate, line-loss rate SD and line-loss rate slope as feature parameters; determining the number of clustering seeds based on an improved clustering model in order to finish classification of an initial data set; and completing line-loss estimation of each type of clustered sub-data-sets according to the line-loss estimation model, and forming a unified line-loss analysis result according to an estimation result for relevant personnel to analyze.

Description

1. Technical field: [0001] The invention relates to an improved K-means clustering line loss analysis method, belonging to the fields of data processing and electric power automation. 2. Background technology: [0002] Line loss is a comprehensive economic and technical index of power supply enterprises, involving many aspects such as power planning, design, infrastructure, renovation, operation and maintenance, maintenance, measurement, and management. The line loss rate is an important technical and economic index for the national assessment of power supply enterprises, and it is also an important symbol to measure the management level of power supply enterprises. With the further deepening of the power system reform, the market competition is becoming increasingly fierce. Doing a good job in line loss management is an important means for power supply companies to increase operating income, achieve more supply and less loss, and save energy and reduce consumption. [0003...

Claims

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Application Information

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IPC IPC(8): G06Q50/06
Inventor 曹杰李秀怡王有权毛波陶海成
Owner NANJING UNIV OF SCI & TECH
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