Power grid fault identification method based on WAMS (Wide Area Measurement System) time sequence decomposition

Abstract

The invention discloses a power grid fault identification method based on WAMS (Wide Area Measurement System) time sequence decomposition, which comprises the following steps: S1, acquiring the real-time data of a power grid by using a phasor measurement unit and extracting after the acquired real-time data is subjected to time sequence decomposition to obtain a power grid real-time feature vector; S2, respectively comparing the power grid real-time feature vector obtained by extraction with a plurality of benchmark fault mode vectors in a preset benchmark fault mode vector set to identify whether the power grid fails or not; S3, if the power grid fails, obtaining a fault content in combination with the benchmark fault mode vector corresponding to the fault and implementing the step S4, and otherwise, implementing the step S1; and S4, updating a power grid network topology and the preset benchmark fault mode vector set according to the identified fault content. The power grid fault identification method based on the WAMS time sequence decomposition has the advantages of high and accurate identification speed and timely reflection and can be widely applied to power grid fault identification.

Description

technical field [0001] The invention relates to a power grid fault identification method, in particular to a power grid fault identification method based on WAMS time sequence decomposition. Background technique [0002] As the scale of my country's power grid becomes larger and more complex, the complex faults such as extreme weather and multi-component tripping caused by the failure of main equipment seriously threaten the security of the power grid. Some disturbances in the local power grid, especially short-circuit faults, will affect the neighboring vast areas. If handled improperly or not in time, it may expand into a systemic accident, or even lead to the collapse of the entire system, resulting in large-scale power outages. When a fault occurs, the dispatcher needs to judge the fault category and its impact in time to take appropriate countermeasures. When a fault occurs in the actual large power grid, especially when multiple complex faults occur in a short period ...

AI Technical Summary

Problems solved by technology

[0003] Most of the existing fault identification methods are based on switch SOE, protection and fault recording data, which cannot realize multi-point time synchronization of power grid data, and it is difficult to carry out online real-time identification of complex faults involving multiple sites and multiple components

In the existing identification methods, the temporal characteristics of the change in time are not considered, and the problem of false positives and missed negatives in the identification of a single fault is prominent, and it cannot meet the needs of complex fault identification

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