Power grid fault detection method and device and storage medium
A technology of power grid faults and detection methods, which is applied in the direction of measuring devices, fault locations, and fault detection according to conductor types, can solve problems such as lack of fault warning accuracy and failure to make full use of distribution network fault trends and cumulative effects. Achieve the effect of improving accuracy and stability
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Embodiment 1
[0036] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.
[0037] The specific implementation method is as follows:
[0038] Such as figure 1 As shown, it is a flowchart of a power grid fault detection method, device and storage medium of the present invention, the steps of which include:
[0039] Step 1. For a power grid, establish a data storage unit for the temperature signal of the busbar of the grid. The busbars collected include the temperature signals of all grids in the grid under different volt...
Embodiment 2
[0059] This embodiment further elaborates the implementation process and precautions of a power grid fault detection method, device and storage medium in combination with an on-site example.
[0060] There are a total of 5 power grid bus groups on a certain bus site. Now it is necessary to use the entropy weight method to establish a power grid bus fault warning system for all the buses in the above 5 power grid bus groups for the management of on-site bus equipment. The specific method is as follows:
[0061] 1. Suppose that the temperature signal Y to be measured and the reference temperature signal X are extracted under a certain voltage level, and the temperature signal Y to be measured and the reference temperature signal X are divided into 4 sections for 3-layer wavelet decomposition, so the reference temperature signal Y and the temperature signal to be measured are obtained. The measured temperature signal X is as follows:
[0062] The reference temperature signal to ...
Embodiment 3
[0087] The difference between this embodiment and Embodiment 2 is that the entropy weight method is used to perform secondary entropy weights on the feature attribute weights in the normalization matrix Q′, and the differences and connections between the final result and Embodiment 1 are compared. The following table is the feature weight in the normalization matrix Q ' obtained in embodiment 2:
[0088]
[0089] According to the weight calculation formula of each feature dimension of the bus sample feature attribute The weights of each feature dimension in the feature matrix Y can be obtained as shown in the following table:
[0090]
[0091] At this time, for the index a of fault early warning, use the formula Calculated a1, a2, a3 are: 0.05, 0.08, 0.03 respectively, at this time, the fault warning index of No. 1 busbar under this voltage level is the maximum value among the three indexes, which is 0.08. For the busbars, the above calculation and processing are als...
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