Non-intrusive resident load identification method based on S_Kohonen

Abstract

The present invention discloses a non-intrusive resident load identification method based on S_Kohonen. The method comprises the steps: the step 1: determining a switching event according to the changing of an active power at a home electric power inlet, and when the switching event happens, collecting current samples of electric appliances having generation of the switching events at the home electric power inlet; the step 2: performing frequency-domain analysis of the collected electric appliance current samples, extracting the frequency-domain harmonic amplitudes of the collected electric appliance current samples as load features of each electric appliance, and forming a load feature base; the step 3: designing an S_Kohonen neural network suitable for resident load identification, and determining the number of nerve cells of the input layer and the output layer of the S_Kohonen neural network and the scale of the competition layer to determine a selection mode for obtaining the nerve cells and a learning algorithm of weight regulation; the step 4: performing parameter initialization; the step 5: performing training of the S_Kohonen network through a training set and performing test of the training set; and the step 6: regulating the network parameters to realize optimal network performances.

Description

technical field [0001] The invention relates to the technical field of power grid load monitoring, in particular to a S_Kohonen-based non-invasive resident load identification method. Background technique [0002] The development of smart grid technology enables power users and the grid to coordinate and cooperate. Among them, smart electricity consumption is one of the important links of smart grid and the core of interactive service system. To achieve smart electricity consumption, power users need to better understand their own electricity consumption characteristics and obtain energy consumption information of electrical equipment in a timely manner. Load monitoring is the key technology to realize intelligent power consumption. Through load monitoring, the power consumption information of various power consumption equipment can be analyzed, so as to guide power users to change power consumption habits and optimize power consumption behavior, so as to achieve the purpos...

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to provide a non-intrusive residential load identification method to solve the problem that the identification accuracy of household appliances is not high in non-invasive load monitoring, and it is difficult to correctly identify low-power electrical appliances, multi-state electrical appliances and electrical appliances with similar characteristics

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