Open-circuit fault diagnosis method for MMC power device

Abstract

The invention relates to an open-circuit fault diagnosis method for an MMC power device, and belongs to the technical field of large-power converter reliability. The method comprises a fault detection step and a fault locating step. During fault detection, a method based on an increment prediction model is used to detect whether an open-circuit fault occurs in the power device of a sub-module; and during fault location after occurrence of the fault, a method by comparing a capacitive voltage gradient of a sub-module is used to locate the sub-module with the fault. According to the method, influence of interference, sampling error and inaccurate model parameters on a diagnosis result is avoided, sub-module faults can be detected and located accurately rapidly within 4ms under different load conditions without adjustment of thresholds, and the capacitive voltage of the sub-module after faults is not increased.

Description

technical field [0001] The invention relates to a method for diagnosing an open-circuit fault of an MMC power device, belonging to the technical field of high-power converter reliability. Background technique [0002] Modular multilevel converter (MMC), because of its advantages of modularization, easy expansion, good output characteristics, and common DC bus, has been widely used in the field of medium and high voltage and high power, especially in the field of high voltage DC transmission. Extensive research and application. The MMC topology is composed of a large number of sub-modules, which leads to the low reliability of the MMC itself, but its application requires its high working reliability. Therefore, the problem of working reliability has become a very important practical problem in the industrial application of MMC. [0003] Fault diagnosis is one of the ways to improve the working reliability of MMC. Power devices are one of the most fault-prone components in ...

AI Technical Summary

Problems solved by technology

The method based on artificial intelligence algorithm is to use artificial intelligence algorithm (such as clustering algorithm and state machine) to diagnose faults. This method does not depend on the model and has strong robustness, but it has the disadvantages of large amount of calculation, long diagnosis time or increased hardware cost.

The method based on the system model is divided into the method based on the state observation and the method based on the switch model. The method based on the state observation is based on the MMC converter circuit model, establishes a mathematical expression, and performs fault detection and fault location according to the difference of system parameters before and after the fault. , this method is simple and easy to implement, but it is easily affected by model parameters, sampling errors and interference, has poor robustness, and takes a long time to locate; the method based on the switch model locates the fault according to the relationship between the switch state and the module voltage. The positioning time of the method is short, but because the switch signal itself is not reliable, it is easily affected by interference and has poor robustness

None of the existing methods are robust and fast

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