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Non-invasive electrical load identification method based on quantum genetic optimization

A quantum genetic algorithm and quantum genetic technology, applied in the field of non-intrusive electrical load identification based on quantum genetic optimization, can solve the problems of transient characteristic accuracy influence, single entry point, etc., to reduce the number of iterations and time complexity, Optimize the obvious effect of improving the recognition accuracy

Active Publication Date: 2021-04-06
SICHUAN CHANGHONG ELECTRIC CO LTD
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AI Technical Summary

Problems solved by technology

[0005] The above methods all achieve load identification by extracting and transforming transient feature quantities, but because the entry point is relatively single, considering the uncertainty of transient features in the actual environment, the accuracy will be affected. Transient, steady-state Feature combination methods have also received attention

Method used

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  • Non-invasive electrical load identification method based on quantum genetic optimization
  • Non-invasive electrical load identification method based on quantum genetic optimization
  • Non-invasive electrical load identification method based on quantum genetic optimization

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Embodiment

[0042]Such asfigure 1As shown, a non-invasive electrical load recognition method based on quantum genetically optimized, specifically includes the following steps:

[0043]Step 1: Install non-invasive power monitoring system devices to resident users who need monitoring and load recognition;

[0044]Step 2: Preset a collection period N, collect the current and voltage data of the electrical device in the acquisition period N time period, and the time length of the specific acquisition period N can be set according to the specific requirements, as in the present embodiment It is 20 seconds.

[0045]Step 3: Preprocessing the collected current and voltage data is to calculate the acquired direct data to obtain effective data, such as data, power, etc., and is obtained by each electrical device After the effective current data is aligned by the voltage phase, the current start point of the M domain is logged, calculate the maximum value, minimum value, etc. of the current amplitude in each type ...

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Abstract

The invention discloses a non-invasive electrical load identification method based on quantum genetic optimization. Specifically, the effective value of the current is obtained by using the measured load current and voltage data, and the optimal solution is obtained by comparing and optimizing through the quantum genetic algorithm, and finally determines the electrical load. specific load type. In the non-intrusive electrical appliance load identification method of the present invention, the quantum genetic algorithm is applied to the non-invasive electrical appliance identification technology on the genetically optimized electrical appliance identification algorithm, which increases the number of solution spaces for finding the optimal solution, and improves the identification results. The accuracy of multiple devices running at the same time also reduces the time complexity.

Description

Technical field[0001]The present invention relates to the field of non-invasive electric power load recognition, and in particular, to a non-invasive electrical load recognition method based on quantum genetically optimized.Background technique[0002]With the development of the smart grid, the proportion of resident users' electricity load in electricity load is increasing, as an important part of the power load, and the user domain load is increasingly concerned. Load online monitoring of residential domains is the basis for realizing electricity visualization of resident users. It helps users understand the specific energy consumption of electrical equipment in different times in the family. According to this, it is necessary to develop a reasonable power plan, improve energy consumption structure. Promote energy efficient use to reduce family electricity bills. The residential user domain load online monitoring plays an important role in promoting energy conservation and emission ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01R31/00G01R21/00G06N3/12
CPCG01R21/001G01R31/00G06N3/126
Inventor 瞿杏元余志斌刘杰宋佶聪何金辉
Owner SICHUAN CHANGHONG ELECTRIC CO LTD
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