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Harmonic sensing method, system and device and storage medium

A technology of harmonics and various harmonics, applied in the fields of harmonic sensing methods, systems, devices and storage media, can solve the problems of low harmonic sensing calculation accuracy and failure to consider the mutual influence of related nodes in the connection relationship of system branches. , to achieve the effect of fast speed, less measurement and high calculation accuracy

Pending Publication Date: 2022-07-12
STATE GRID BEIJING ELECTRIC POWER +1
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Problems solved by technology

However, the existing harmonic detection methods based on artificial neural networks, such as BP network and LSTM network, do not consider the connection relationship between system branches and the mutual influence of associated nodes, and the accuracy of harmonic perception and calculation is not high.

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  • Harmonic sensing method, system and device and storage medium
  • Harmonic sensing method, system and device and storage medium
  • Harmonic sensing method, system and device and storage medium

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Embodiment approach

[0037] The first aspect of the embodiments of the present invention provides a harmonic sensing method. Based on a graph convolutional neural network, an undirected graph is used to describe the relationship between the measured electrical node and related branches in the power grid, and a graph is constructed and trained. Convolutional neural network, which uses a trained graph convolutional neural network to calculate data such as harmonic real-time and predicted values. It can quickly and effectively calculate the fundamental current component, total harmonic component, 2nd, 5th, and 7th harmonic components of the measured point, which realizes the real-time and rapidity of harmonic detection, and helps to realize power grid operation status awareness and Risk prediction. When the load current changes abruptly, the algorithm has a smaller delay and a faster convergence speed.

[0038] like figure 1 As shown, the harmonic sensing method provided by the embodiment of the pr...

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Abstract

The invention discloses a harmonic wave sensing method, system and device and a storage medium, and the method comprises the steps: firstly obtaining the topological data of a power grid; constructing an undirected graph based on the power grid topological data, wherein vertexes in the undirected graph correspond to electrical nodes in the power grid; the node features of the electrical nodes are used as input, a pre-trained graph convolutional neural network model is adopted for recognition, and the graph convolutional neural network model outputs harmonic real-time values and predicted values of the electrical nodes. Compared with the conventional common detection method based on instantaneous reactive power, the harmonic sensing method provided by the invention breaks through the limitation that the conventional time domain detection method can only detect the total harmonic current, can calculate each harmonic component in a single step, and has the advantages of high calculation precision, less measurement, high speed and the like.

Description

technical field [0001] The invention belongs to the technical field of power grid operation, and in particular relates to a harmonic sensing method, system, device and storage medium. Background technique [0002] Graph Convolutional Neural Network (Graph Convolutional Network) is a method that can perform deep learning on graph data. [0003] With the continuous development of the power system, the extensive use of power electronic components makes the power system inevitably affected by harmonics. Harmonics reduce the operating efficiency of the power grid, and it is easy to form a resonant circulating current, which may burn out electrical equipment such as motors in severe cases. Harmonics pollute the operation quality of the power grid, threaten the safe, stable and economical operation of the power grid, and affect the surrounding electrical environment. It has become one of the main public safety hazards of the current power grid. Effective, timely and accurate dete...

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Application Information

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IPC IPC(8): G01R23/16G06N3/04G06N3/08
CPCG01R23/16G06N3/08G06N3/045Y02E40/40
Inventor 陈泽西贾东强王朴肖万芳王波杨立田建南毋凡冯洋徐弈昕李森徐啸野张志远孙玉树张志兵梅海军冯笑董腾飞
Owner STATE GRID BEIJING ELECTRIC POWER
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