Excitation surge current identification method based on support vector classifier

Abstract

Provided is an excitation surge current identification method based on a support vector classifier. The method selects seven characteristics of a secondary second harmonic, a third harmonic, a current dead angle, a wave width, a waveform distortion amount, a waveform correlation coefficient and an excitation side measured impedance as inputs of a support vector machine, then various running states of a transformer are trained, and a decision function identifying an excitation surge current and a fault current is constructed. When the transformer is out of order, data collected by a protection device collection system is calculated to obtain seven characteristics, the seven characteristics are put into the decision function and determination of an excitation surge current and a fault current is carried out. The identification method integrates advantages of principles of harmonic wave braking, a dead angle, waveform similarity and the like and avoids respective limitation, and the surge current identification credibility is raised. An algorithm can be converted into a convex optimization problem finally, and the local minimum problem which cannot be solved by a neural network is avoided. The method is free from a transformer wiring mode and is free from model parameters, the applicability is strong and the flexibility is good.

Description

technical field [0001] The invention relates to an excitation inrush identification method, in particular to an excitation inrush identification method based on a support vector classification machine. Background technique [0002] In recent years, with the construction of ultra-high voltage and large power grids, more and more large-capacity transformers have been put into use, which also makes the role of transformers in the stable operation of power grids more and more important, making transformer protection bear more and more test. However, studies have shown that the correct action rate of 220kV and above power transformer protection has been hovering at 70% to 80%, which is far lower than the correct action rate of generator and 220kV and above line protection. The reason is that the transformer protection cannot distinguish the exciting inrush current and the fault current very accurately, which has become a big mountain in the way of improving the operation rate of...

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Problems solved by technology

[0004] The second harmonic braking is convenient and simple to implement, and it is the most widely used in transformer protection, but the influence of parallel capacitors for reactive power compensation and distributed capacitance of high-voltage transmission lines makes the transformer fault also have high second harmonics; large transformers The reduction of saturation magnetic flux makes the second harmonic content sometimes reduced to less than 10% during the excitation inrush current

[0005] The principle of discontinuous angle identification is also a commonly used method for identifying inrush currents, but it is greatly affected by CT saturation, non-periodic components, and sampling frequency. The artificial neural network method is affected by local minimum points and has a high degree of dependence on training samples. It is difficult to determine the weight of each criterion based on the principle of multi-criteria

[0006] The equivalent circuit method avoids the influence of differential current, but is restricted by parameters such as transformer transient model and transformer leakage inductance

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