Non-invasive household electrical appliance load identification method and device and storage medium

Abstract

The invention discloses a non-invasive household electrical appliance load identification method. The method comprises the steps of calculating a second target parameter according to an acquired firsttarget parameter; performing normalization processing on the second target parameter; carrying out FFT on the normalized second target data to obtain a harmonic spectrum and an amplitude, and takingthe harmonic spectrum and the amplitude as sample data; constructing a neural network model according to the sample data, and training the neural network model; and identifying the load of the household electrical appliance according to the trained neural network model. According to the method, after the second target data is calculated, normalization processing is carried out on the second targetdata, FFT conversion is carried out on the processed second target data, the accuracy of the sample data can be ensured, a neural network model with high accuracy can be obtained, and then the load identification accuracy of the household appliance can be improved. In addition, the invention also provides a non-invasive household electrical appliance load identification device and a storage medium, and the effects are as mentioned above.

Description

technical field [0001] The present application relates to the field of power system identification, in particular to a non-invasive household electrical appliance load identification method, device and storage medium. Background technique [0002] There are usually two methods for electrical load detection and identification, namely intrusive load detection and non-invasive load detection and identification. The realization of traditional intrusive load identification is mainly to obtain the electricity consumption data of household appliances by installing detection sensors on each household appliance, and then transmit the data to the terminal through the network, and the terminal analyzes and processes the data uniformly. Although this method has relatively low technical difficulty and is easy to implement, it is a very uneconomical solution because the wiring is complicated and the cost of implementation and maintenance is high. The non-intrusive load detection and reco...

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Problems solved by technology

[0004] This application provides a non-invasive household appliance load identification method, which solves the problem of how to improve the accuracy of household appliance load identification in the prior art

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