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A Smart Grid Data Decomposition Method Based on Non-negative Matrix Factorization

A non-negative matrix decomposition, smart grid technology, applied in complex mathematical operations and other directions, can solve problems such as difficulty in accuracy and large error in the decomposition results of electricity consumption data.

Active Publication Date: 2019-09-03
BEIJING UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, these traditional technologies are difficult to apply to more and more complex electricity consumption data, and the errors in the decomposition results of electricity consumption data are relatively large, and the accuracy is difficult to be accepted by users.

Method used

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  • A Smart Grid Data Decomposition Method Based on Non-negative Matrix Factorization
  • A Smart Grid Data Decomposition Method Based on Non-negative Matrix Factorization
  • A Smart Grid Data Decomposition Method Based on Non-negative Matrix Factorization

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Embodiment Construction

[0050] Such as Figure 5 As shown, the present invention provides a smart grid data decomposition method based on non-negative matrix decomposition, comprising the following steps:

[0051] Step 1. Data Acquisition: Acquire Power Consumption Data

[0052] Obtain electricity consumption data, which consists of user ID, time stamp and power data.

[0053] Step 2. Data preprocessing: power consumption data preprocessing

[0054] Step 2.1, data cleaning: filter out abnormal data with too much missing time, too much missing power consumption information and unknown user ID.

[0055] Step 2.2. Remove abnormal users: Remove users whose power consumption data is not consistent with common sense; for example, users with excessive power consumption or users with no power consumption for a long time; these users may not be ordinary household users, or may be due to information collection error caused.

[0056] Step 2.3, data completion: complete a small amount of missing power data, ...

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Abstract

The invention discloses a smart power grid data decomposition method based on non-negative matrix factorization. On the basis of a non-negative matrix decomposition algorithm, the similarity featuresamong users are introduced, the performance of the algorithm is improved, so that the decomposition result is closer to actual electricity information of the users, and more precise feedback is provided for the users. As is proved by the experiment result, compared with an existing method, by means of the smart power grid data decomposition method, the performance is obviously improved.

Description

technical field [0001] The invention belongs to the field of data mining, and in particular relates to a smart grid data decomposition method based on non-negative matrix decomposition. Background technique [0002] The Internet of Things technology has been widely used in e-government, e-commerce and community services and other fields that are related to the national economy and the people's livelihood. It plays a decisive role in promoting the upgrading of traditional industries, improving production efficiency and safety production capacity, and improving the level of social public management and people's quality of life. effect. Smart grid as a typical application of the Internet of Things (such as figure 1 (shown) generates a huge amount of electricity consumption data, involving many users, through the full mining of smart grid data, users can be provided with more accurate and effective services. Studies have shown that when users obtain detailed electricity consum...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/16
Inventor 杨震何通海
Owner BEIJING UNIV OF TECH