Dynamic Characteristics Analysis And Diagnosis Methodes For Open Circuit Faults In Converter Of PMSG System

Developing new energy sources is an important way to meet sustainable development.Wind farms are usually in deserts,islands,and mountains.These surroundings are complex and bad for the safe of wind farms.The full power gridconnected system with a permanent magnet synchronous generator(PMSG)is one of the mainstream wind power grid-connected topologies.The full power converter,as one of the main components of PMSG system,has many power electronic devices,which hurt easily in the harsh environment.According to statistics,the economic losses caused by converter faults have reached 13% of the total cost.In converter faults,the open-circuit fault(OCF)is one of the most common faults and are not easily found.If an OCF occurs and exists secretly,the other power devices will get much pressure,the risk of secondary faults rise,and the security of the power grid is threatened.Therefore,analyzing the dynamic characteristics of the system after an OCF in a converter,and locating the fault accurately are much important tasks for the safe of the wind power system.On the basis of the existing research and analysis theory of dynamic characteristics for an OCF in a converter,this dissertation reveals the dynamic distortion characteristics and studys on the fault diagnosis for the faults in a converter of PMSG system.In the previous research on the voltage characteristics of the PMSG system after an OCF happened in a converter,the current in the zero-crossing section is often ignored,and the multi-switch OCFs are not analyzed.For remedying these problems,both of the single-switch faults and the multi-switch faults are taken as examples.The study of the multi-switch OCF is enriched.Besides,the research for all the examples are classified by the polarity of the faulty phase current and its on-off condition.So,the single-switch OCF and the multi-switch OCF are analyzed in 3 and 8 kinds of operation modes,respectively.The characteristic analysis during the zero-crossing section of stator current are improved.So,the operating characteristics of PMSG system after an OCF happened in a converter are revealed,and the mathematical expressions of the lower tube voltage,the DC link to ground voltage and the stator voltage are obtained.The accuracy and effectiveness of the method are verified by experimental simulations.Due to the strong nonlinearity and the coupling of the wind power system,the analysis for three-phase current is difficult.Aiming at this problem,this paper proposes a current characteristic analysis method based on Mixed Logic Dynamic Model(MLD).After the dynamic logic relationship analysis of PMSG system,several MLD models under different fault modes,surely,containing under a one-phase multi-switch OCF mode,are obtained.That makes up for the shortcomings of the switch function mode l in the analysis of the one-phase multi-switch OCFs.The dynamic analysis of the trigger pulse that is usually ignored also is included in this study.And the rule of probability variation for each pulse combination is obtained.In order to deal with the coupling relationship between the system and the external environment,the closed loop control strategy for the converter in PMSG system and the PWM control strategy are analyzed,which solves the problem that the current analysis is difficult to do.The data-based fault diagnosis method is always sensitive to external features.However,in the past research,the characteristics of signal are rarely analyzed in-depth,which leads to difficulty highlight the external features.So the data-based fault diagnosis method cannot be ensured the high perform.Due to this reason,a fault diagnosis method is proposed after the signal analysis in-depth.In the process of signal analysis,many features,such as the load characteristics,the robustness,the separation,are compared and analyzed during an OCF occurred in PMSG system.Then,the appearance time,appearance condition and appearance frequency of external feature in signal are studied to make ensure the capture of external features in-depth.According to the research results of signal,a voltage-based fault diagnosis method is proposed.This method does not need threshold.The calculation of voltage deviation is unnecessary.The test and analysis results show that the proposed voltage-base method can correctly detect the single-switch and multi-switch OCFs under different wind speed.the current-based method does not require additional sensors.However,the external feature also affects the perform of a current-based fault diagnosis method.The current is sensitive to the load and other factors from environments.The fault diagnosis ratio of a current-based method always shows lower than the voltage-based method.So,in order to enhance the robustness of the current signal,this dissertation focuses on the constraint relationship between three-phase currents.A novel current-based neural network fault diagnosis method is proposed.This proposed method takes the three-phase current correlation features as the input of the neural network.Therefore,the diagnosis result shows with little effects from the current load,and its achievement does not need a large calculated amount.The required storage space also is not large.Compared with the neural network fault diagnosis method based on DQ current and three-phase current waveform,the proposed method has obvious advantages in diagnosis rate,robustness,and dependence on neural network structure and algorithm.