Non-invasive electric appliance 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 feature accuracy influence, single entry point, etc., to reduce the number of iterations and time complexity, Significant optimization and improved recognition accuracy

Active Publication Date: 2019-04-16
SICHUAN CHANGHONG ELECTRIC CO LTD
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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, conside...

Method used

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

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Embodiment

[0042] Such as figure 1 As shown, a non-invasive electrical load identification method based on quantum genetic optimization, specifically includes the following steps:

[0043] Step 1: Install non-intrusive power monitoring system devices to residential users who need monitoring and load identification;

[0044] Step 2: Preset a collection cycle N, and collect the current and voltage data of the electrical equipment within the time period of the collection cycle N. Generally, the specific collection cycle N can be set according to specific needs. For example, in this embodiment, set Set at 20 seconds.

[0045] Step 3: Preprocessing the collected current and voltage data is to calculate and process the collected direct data to obtain the required effective data, such as current effective value, power and other required data, and obtain the data of each electrical equipment After the effective current data, the current starting point of the M domain is found through voltage pha...

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Abstract

The invention discloses a non-invasive electric appliance load identification method based on quantum genetic optimization. Specifically, an actually-measured load current and voltage data are used, acurrent effective value is obtained, the optimal solution is obtained through comparison and optimization through a quantum genetic algorithm, and finally the specific load type of an electric appliance is determined. According to the non-invasive electric appliance load identification method based on a genetic optimization identification algorithm, a quantum genetic optimization electric appliance identification algorithm is applied to non-invasive electric appliance identification technology, so that the number of solution spaces for finding the optimal solution is increased, the accuracy rate of simultaneous operation of multiple kinds of equipment is improved on recognition results, and meanwhile the time complexity is also reduced.

Description

technical field [0001] The invention relates to the technical field of non-invasive electrical load identification, in particular to a non-invasive electrical load identification method based on quantum genetic optimization. Background technique [0002] With the development of smart grids, the proportion of residential users' electricity loads in the power load is increasing. As an important part of the power load, residential user domain loads have increasingly attracted widespread attention from the society. On-line load monitoring in the residential user domain is the basis for realizing the visualization of residential electricity consumption. It helps users understand the specific energy consumption of various electrical equipment in the home at different times, and based on this, they can formulate reasonable electricity consumption plans and improve the energy consumption structure. , Promote efficient use of energy and reduce household electricity bills. On-line mo...

Claims

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Application Information

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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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