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Research On Open Circuit Fault Diagnosis Of MMC Sub-module

Posted on:2021-01-29Degree:MasterType:Thesis
Country:ChinaCandidate:S C ZhangFull Text:PDF
GTID:2512306200453844Subject:Electrical engineering
Abstract/Summary:PDF Full Text Request
Modular Multilevel Converter(MMC)is considered as the best topology for voltage source converters in high voltage and high power applications due to its modularity and scalability,its widely used in high-voltage DC transmission and flexible AC transmission projects,the application of cascaded sub-modules ensure the quality,flexibility and low harmonic rate of high-voltage AC power.Because the structure of the MMC is based on stacking multiple cascaded sub-modules,a large number of capacitors and semiconductor switching devices contained therein may fail,so certain fault diagnosis must be taken to quickly remove the occurrence of the fault.Based on the above background,in order to improve the reliability of MMC and save system investment costs,the research on capacitor voltage estimation of MMC sub-modules is of great significance.This paper aims to improve the speed of open-circuit fault diagnosis of MMC sub-modules,reduce design complexity and hardware configuration costs,and conduct in-depth research on MMC fault diagnosis.The specific work is as follows:(1)This paper introduces the three-phase topology and working principle of MMC.Taking the structural and operating characteristics of the MMC as a starting point,the mathematical model of the MMC is deduced,and the MMC mathematical model in the three-phase stationary coordinate system is converted into a mathematical model based on the synchronous rotating coordinate system,thereby obtaining a control block diagram of the decoupled controller..Then,two mainstream MMC modulation strategies are compared,and simulation verification is performed in combination with the voltage balance control method.Based on this,the MMC electromagnetic transient model is built based on the PSCAD simulation platform,which lays a theoretical foundation for the following research on the MMC sub-module failure.(2)Aiming at the problems of increasing the complexity of the measurement system and the decrease of system reliability and economy due to the excessive number of MMC sensors,a capacitor voltage estimation scheme based on the improved Kalman filter is proposed.First,the relationship between the switching state of the sub-module and the voltage was analyzed and a mathematical model of the bridge arm voltage was established.Second,for themeasurement noise of the bridge arm voltage collected by the sensor,based on the Adaptive Kalman filter algorithm,the linear minimum variance criterion was established.The mathematical model of the capacitor voltage monitoring information of the MMC sub-module,so as to obtain the real-time capacitor voltage observation,reduce the number of sensors and reduce the impact of noise.Finally,the proposed method for estimating the capacitor voltage of the sub-module is verified on the PSCAD/ EMTDC simulation platform.(3)The open-circuit fault characteristics of the MMC sub-module are analyzed.Based on the characteristic that the capacitor voltage of the open-circuit fault sub-module will deviate from the normal value,a fault diagnosis method using the estimated capacitor voltage value for correlation analysis is proposed.For open circuit faults,using the lack of sub-module capacitor charging and discharging circuits to make the faulty sub-module capacitor voltage deviate from the normal sub-module capacitor voltage value,the correlation analysis of the capacitor voltage observation values of each sub-module on the same bridge arm is performed.The correlation index is calculated,and the correlation index deviates from the set threshold to complete real-time and rapid fault diagnosis.This method shortens the fault diagnosis time and also improves the system reliability and economy.Finally,PSCAD / EMTDC simulations verify that the proposed strategy is correct.
Keywords/Search Tags:Modular Multilevel Converter, Capacitance Voltage Observation, Adaptive Kalman Filter, Fault Diagnosis
PDF Full Text Request
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