Compensation grounding power grid adaptive line selection method using rough set theory for classification

Abstract

The invention discloses a compensation grounding power grid adaptive line selection method using a rough set theory for classification; the method comprises the following steps: using a transient zero sequence current in one cycle after a fault to calculate a transient factor; 2, calculating a post-fault half cycle transient zero sequence current frequency band energy factor; 3, using the rough set theory to fuse the transient factor with the frequency band energy factor, forming decision rules, and dividing single-phase grounding faults into strong, middle and weak types; 4, adaptively selecting a corresponding line selection method according to different fault types. Compared with a single-criteria line selection method, the method is stronger in applicability and higher in accuracy; compared with a multi-criteria fusion line selection method, the method can reduce unnecessary fusions, thus greatly reducing data processing amount, and ensuring the line selection accuracy.

Description

technical field [0001] The invention belongs to the field of fault line selection methods in power system relay protection, and relates to an adaptive line selection method for a compensation grounding power grid, in particular to an adaptive line selection method for a compensation grounding power grid classified by rough set theory. Background technique [0002] In my country's 6~66kV distribution network, the neutral point mainly adopts the non-effective grounding method, that is, the neutral point is not grounded or the neutral point is grounded through the arc suppression coil. With the development of the economy, the capacity of the system continues to increase, and the number of feeder lines continues to increase, resulting in an increase in the ground capacitance current when a single-phase ground fault occurs. In order to curb the ground current, in the distribution network, the neutral point is grounded through the arc suppressing coil, which is more and more popul...

AI Technical Summary

Problems solved by technology

The scope of application of the single-criterion line selection method is limited. For example, the line selection method based on the steady state quantity is suitable for the fault situation with weak transient information, and the line selection method based on the transient quantity is more accurate for the fault situation with strong transient information. The line selection method of multi-criteria fusion, such as: neural network, support vector machine and other fusion methods, to a certain extent, solves the problem of limited applicability of single criterion, but at the same time, there are large amount of data processing, information redundancy and Problems that require a large number of training samples

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