Abstract：Modular multilevel converter (MMC) is drawing increasing attention in high-voltage direct- current (HVDC) transmission. Due to the numerous cascaded sub-modules (SMs), safety is one of the most important challenges for MMC. The open-circuit faults for SMs may distort the output voltage and current of MMC and even destroy the system if the faults are not handled in time. Therefore, this paper will concentrate on SM open-circuit faults. In general, the research for fault detection and location (FDL) of SM open-circuit is mainly divided into three basic approaches: (1) sensor-based, (2) model-based, and (3) machine learning (ML)-based. Sensor-based methods can realize FDL quickly but need extra hardware costs, which may also add potential points of fault. Model-based methods are relatively sensitive to uncertain system parameters and environmental noise because of the requirement for an accurate mechanism model of the circuit. This paper proposes a diagnostic strategy based on machine learning (ML) to detect and locate the sub-module open-circuit fault. Firstly, the operation principle of MMC and SMs are analyzed to find that the capacitor voltages of faulty SMs will be different from the normal capacitance voltage. SM capacitor voltages can be regarded as the indicator for fault detection and location. The sliding window divides the long original data into multiple short data fragments, and 12 features of SM capacitor voltages are extracted as the feature vectors for the anomaly detection model. Secondly, the open circuit fault diagnosis problem can be transformed into a multivariate Gaussian anomaly detection problem according to the feature extraction of the capacitor voltage of SMs. The model based on multivariate Gaussian distribution is demonstrated to make predictions for anomaly detection and trace back the predicted faulty SM. Then, the fault detection and location method based on multivariate Gaussian distribution is presented to locate the faulty SM. If the probability density of the vector to be diagnosed is greater than the threshold value, it can be determined that the SM is normal. If the probability density is less than the threshold value, the SM is in a fault state. When the open circuit fault is diagnosed for N consecutive cycles, the SM is judged as faulty. Finally, simulation and experiment verify the effectiveness of the proposed FDL method. In summary, an SM open-circuit FDL method based on multivariate Gaussian distribution is proposed in this paper. After the analysis of the fault characteristics, the voltages of SM are chosen as the indicators of FDL. Sliding window and feature extraction are used to construct the dataset for the ML model. The model based on multivariate Gaussian distribution is trained for anomaly detection. After the fault is detected, it can be located by tracing the corresponding SM number. This method can get high generalization accuracy without extra sensors or an accurate mathematical model of MMC. According to the simulation and experiment results, the effectiveness of the proposed method can be proven by the different evaluation indexes.
杨贺雅, 邢纹硕, 向鑫, 张伟, 胡宏彬. 基于多元高斯分布异常检测模型的MMC子模块开路故障诊断方法[J]. 电工技术学报, 2023, 38(10): 2744-2756.
Yang Heya, Xing Wenshuo, Xiang Xin, Zhang Wei, Hu Hongbin. A Sub-Module Open-Circuit Fault Detection and Location Strategy for Modular Multilevel Converters Based on Multivariate Gaussian Distribution. Transactions of China Electrotechnical Society, 2023, 38(10): 2744-2756.
[1] 徐殿国, 李彬彬, 周少泽. 模块化多电平高压变频技术研究综述[J]. 电工技术学报, 2017, 32(20): 104-116. Xu Dianguo, Li Binbin, Zhou Shaoze.Overview of the modular multilevel converter based high voltage motor drive[J]. Transactions of China Electro- technical Society, 2017, 32(20): 104-116. [2] 贺永杰, 向往, 周家培, 等. LCC-MMC串联型混合直流输电系统小信号建模[J]. 电工技术学报, 2021, 36(7): 1492-1506. He Yongjie, Xiang Wang, Zhou Jiapei, et al.Small- signal modelling of LCC-MMC series hybrid HVDC transmission system[J]. Transactions of China Elec- trotechnical Society, 2021, 36(7): 1492-1506. [3] 彭浩, 邓焰, 王莹, 等. 模块化多电平变换器模型及稳态特性研究[J]. 电工技术学报, 2015, 30(12): 120-127. Peng Hao, Deng Yan, Wang Ying, et al.Research about the model and steady-state performance for modular multilevel converter[J]. Transactions of China Electrotechnical Society, 2015, 30(12): 120-127. [4] 常浩, 厉璇, 马玉龙, 等. 舟山多端柔性直流输电工程直流系统放电特性[J]. 高电压技术, 2017, 43(1): 9-15. Chang Hao, Li Xuan, Ma Yulong, et al.Discharge characteristics of DC system in Zhoushan multi-terminal VSC-HVDC transmission project[J]. High Voltage Engineering, 2017, 43(1): 9-15. [5] 谢惠藩, 付超, 李诗旸, 等. 昆柳龙多端直流线路故障恢复及换流站在线退站的系统稳定特性分析[J]. 南方电网技术, 2021, 15(6): 7-14. Xie Huifan, Fu Chao, Li Shiyang, et al.Analysis on system stability characteristic of DC line fault reco- very and converter station online disconnection of KLL MTDC[J]. Southern Power System Technology, 2021, 15(6): 7-14. [6] 张建坡, 崔涤穹, 田新成, 等. 自阻自均压模块化多电平换流器子模块拓扑及控制[J]. 电工技术学报, 2020, 35(18): 3917-3926. Zhang Jianpo, Cui Diqiong, Tian Xincheng, et al.Self-block and voltage balance modular multilevel converter sub module topology and control[J]. Transactions of China Electrotechnical Society, 2020, 35(18): 3917-3926. [7] 杨晓峰, 李泽杰, 薛尧, 等. 增强型柔性逆阻模块化多电平换流器的故障阻断特性分析[J]. 电工技术学报, 2019, 34(12): 2549-2557. Yang Xiaofeng, Li Zejie, Xue Yao, et al.Fault blocking performance analysis of enhanced flexible reverse blocking multilevel modular converter[J]. Transactions of China Electrotechnical Society, 2019, 34(12): 2549-2557. [8] 杜晓磊, 郭庆雷, 吴延坤, 等. 张北柔性直流电网示范工程控制系统架构及协调控制策略研究[J]. 电力系统保护与控制, 2020, 48(9): 164-173. Du Xiaolei, Guo Qinglei, Wu Yankun, et al.Research on control system structure and coordination control strategy for Zhangbei demonstration project of MMC- HVDC grid[J]. Power System Protection and Control, 2020, 48(9): 164-173. [9] 汤广福, 王高勇, 贺之渊, 等. 张北500kV直流电网关键技术与设备研究[J]. 高电压技术, 2018, 44(7): 2097-2106. Tang Guangfu, Wang Gaoyong, He Zhiyuan, et al.Research on key technology and equipment for Zhangbei 500kV DC grid[J]. High Voltage Engin- eering, 2018, 44(7): 2097-2106. [10] 汤广福, 罗湘, 魏晓光. 多端直流输电与直流电网技术[J]. 中国电机工程学报, 2013, 33(10): 8-17, 24. Tang Guangfu, Luo Xiang, Wei Xiaoguang.Multi- terminal HVDC and DC-grid technology[J]. Pro- ceedings of the CSEE, 2013, 33(10): 8-17, 24. [11] 邹毅军, 魏明洋. 模块化多电平换流器子模块故障模拟方法[J]. 电气技术, 2022, 23(4): 96-101. Zou Yijun, Wei Mingyang.Fault simulation method for sub-module in modular multilevel converter[J]. Electrical Engineering, 2022, 23(4): 96-101. [12] Deng Fujin, Lü Yongqing, Liu Chengkai, et al.Over- view on submodule topologies, modeling, modulation, control schemes, fault diagnosis and tolerant control strategies of modular multilevel converters[J]. Chinese Journal of Electrical Engineering, 2020, 6(1): 1-21. [13] Nami A, Liang Jiaqi, Dijkhuizen F, et al.Modular multilevel converters for HVDC applications: review on converter cells and functionalities[J]. IEEE Transactions on Power Electronics, 2015, 30(1): 18-36. [14] Choi U M, Blaabjerg F, Lee K B.Study and handling methods of power IGBT module failures in power electronic converter systems[J]. IEEE Transactions on Power Electronics, 2015, 30(5): 2517-2533. [15] Wang Zhiqiang, Shi Xiaojie, Tolbert L M, et al.A di/dt feedback-based active gate driver for smart switching and fast overcurrent protection of IGBT modules[J]. IEEE Transactions on Power Electronics, 2014, 29(7): 3720-3732. [16] Krone T, Xu Chengzhi, Mertens A.Fast and easily implementable detection circuits for short circuits of power semiconductors[J]. IEEE Transactions on Industry Applications, 2016, 53(3): 2871-2879. [17] Lamb J, Mirafzal B.Open-circuit IGBT fault detection and location isolation for cascaded multi- level converters[J]. IEEE Transactions on Industrial Electronics, 2017, 64(6): 4846-4856. [18] 于泳, 蒋生成, 杨荣峰, 等. 变频器IGBT开路故障诊断方法[J]. 中国电机工程学报, 2011, 31(9): 30-35. Yu Yong, Jiang Shengcheng, Yang Rongfeng, et al.IGBT open circuit fault diagnosis method for inver- ter[J]. Proceedings of the CSEE, 2011, 31(9): 30-35. [19] Lu Bin, Sharma S.A literature review of IGBT fault diagnostic and protection methods for power inverters[J]. IEEE Transactions on industry appli- cations, 2009, 45(5): 1770-1777. [20] Liu Chengkai, Deng Fujin, Cai Xu, et al.Submodule open-circuit fault detection for modular multilevel converters under light load condition with rearranged bleeding resistor circuit[J]. IEEE Transactions on Power Electronics, 2022, 37(4): 4600-4613. [21] Bi Kaitao, An Quntao, Duan Jiandong, et al.Fast diagnostic method of open circuit fault for modular multilevel DC/DC converter applied in energy storage system[J]. IEEE Transactions on Power Electronics, 2017, 32(5): 3292-3296. [22] Zhang Jianzhong, Hu Xing, Xu Shuai, et al.Fault diagnosis and monitoring of modular multilevel converter with fast response of voltage sensors[J]. IEEE Transactions on Industrial Electronics, 2020, 67(6): 5071-5080. [23] Wang Jun, Ma Hao, Bai Zhihong.A submodule fault ride-through strategy for modular multilevel con- verters with nearest level modulation[J]. IEEE Transactions on Power Electronics, 2018, 33(2): 1597-1608. [24] Liu Zehao, Xiao Lan, Wang Qin, et al.Open-circuit fault diagnosis for MMC based on event-triggered and capacitor current state observation[J]. IEEE Transa- ctions on Circuits and Systems II: Express Briefs, 2022, 69(2): 534-538. [25] Deng Fujin, Chen Zhe, Khan M R, et al.Fault detection and localization method for modular multilevel converters[J]. IEEE Transactions on Power Electronics, 2015, 30(5): 2721-2732. [26] Pang Yuqi, Ma Gang, Xu Xiaotian, et al.RNN-based fault detection method for MMC photovoltaic grid- connected system[J]. Recent Advances in Electrical & Electronic Engineering, 2021, 14(7): 755-766. [27] Kiranyaz S, Gastli A, Ben-Brahim L, et al.Real-time fault detection and identification for MMC using 1-D convolutional neural networks[J]. IEEE Transactions on Industrial Electronics, 2019, 66(11): 8760-8771. [28] Deng Fujin, Jin Ming, Liu Chengkai, et al.Switch open-circuit fault localization strategy for MMCs using sliding-time window based features extraction algorithm[J]. IEEE Transactions on Industrial Elec- tronics, 2021, 68(10): 10193-10206. [29] An Yang, Sun Xiangdong, Yuan Qing.IGBT open circuit fault diagnosis method for a modular multi- level converter based on PNN-MD[C]//2020 4th International Conference on HVDC (HVDC), Xi'an, China, 2020: 911-916. [30] Jiang Siyu, Wang Bin, Xu Wanwan.Fault diagnosis of modular multilevel converter based on principal component analysis and support vector machine[J]. Journal of Physics: Conference Series 2021, 2030(1): 012086. [31] Qu Xiaoyu, Dong Kun, Zhao Jianfeng, et al.An identification and location method for power quality disturbance sources in MMC converter based on KNN algorithm[C]//2021 4th International Conference on Energy, Electrical and Power Engineering (CEEPE), Chongqing, China, 2021: 170-177. [32] Yang Qichen, Qin Jiangchao, Saeedifard M.Analysis, detection, and location of open-switch submodule failures in a modular multilevel converter[J]. IEEE Transactions on Power Delivery, 2016, 31(1): 155-164. [33] Li Cui, Liu Zhenxing, Zhang Yong, et al.Diagnosis and location of the open-circuit fault in modular multilevel converters: an improved machine learning method[J]. Neurocomputing, 2019, 331: 58-66. [34] 李翠, 刘振兴, 柴利, 等. 模块化多电平换流器的子模块开路故障检测方法[J]. 中国电机工程学报, 2017, 37(23): 6995-7003, 7091. Li Cui, Liu Zhenxing, Chai Li, et al.An open circuit fault detection method for sub-modules in modular multi-level converters[J]. Proceedings of the CSEE, 2017, 37(23): 6995-7003, 7091.
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