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Open-circuit Fault Diagnosis Strategy For Modular Multilevel Converter Semiconductor Power Switches
Abstract
The modular multilevel converter (MMC) is one of the most commonly used power electronic converters in medium and high-power applications. However, reliability is one of the most critical challenges because of the many power switching devices applied in the MMC. Also, many voltage sensors in the converter topology have increased cost and hardware complexity. In this paper, a method for detecting IGBTs open-circuit fault is proposed. In the proposed method, each converter arm is divided into sets. Each set includes two sub-modules and a voltage sensor. These voltage sensors are responsible for monitoring their set. By comparing the output voltage of each set, in normal operation mode and after the open-circuit fault, the fault is detected with great speed and accuracy. Finally, the performance of the proposed method in various scenarios is examined by the simulation results in MATLAB/Simulink.
... Nevertheless, with the increase in the number of SMs in an MMC system, this approach would be suitable for applications in high voltage fields due to its high cost and increased circuit complexity. In [23], a method for detecting IGBTs in an open-circuit fault is proposed for each grouping detection device, which consists of two submodules and a voltage sensor. This method has a highspeed fault detection advantage, however, it cannot achieve SM fault location fuctionality. ...
... However, the thresholds change with the change in operation conditions of the MMC. Table IV shows that several methods, such as [21], [22], [23], [24], [25], and [31], can handle multiple faults at the same time. The proposed approach is robust to external noise, does not require an empirical threshold and is suitable for multiple faults. ...
With the wide application of a modular multilevel converter in various power conversion fields, submodule open-circuit fault diagnostics have attracted increasing attention, as some of the existing diagnosis methods have a single function and limited localization speed. Therefore, a simplified and innovative multifunctional hybrid machine learning-based fault diagnosis strategy for the submodules is proposed. Starting from the output characteristics of the faulty submodule, the eigenvalues of the bridge arm current and submodule capacitor voltage during faults are extracted, and the eigenvalues are utilized for fault detection and location via the integration of improved supervised learning and unsupervised learning. Finally, the effectiveness of the proposed method is verified by simulated and experimental results in a three-phase modular multilevel converter topology. In addition, it can diagnose multiple fault types and achieve a high fault identification probability.
... [12][13][14][15][16] Gradually, various studies have presented estimation methods for determining the voltage of capacitors in each processing cycle by using the previous cycle's data of switching signals and capacitor voltages, thereby reducing the number of required sensors and the hardware complexity of the system. 17,18 In Yin et al. and Hu et al., 19,20 the current sensors are eliminated, but all voltage sensors are present on the sub-modules (Subs). These methods with many voltage sensors will complicate the system and degrade its reliability in real power grids. ...
... Because all voltage sensors are present in these studies, no estimation method is used, and the fault in each sub can be detected in each sampling time. Gradually, previous studies 14,17,33 apply various methods and Sub configurations to reduce the voltage sensors in half and detect faults in each sub. These studies make use of traditional sorting processes, and the presence of current sensors is required. ...
The modular multilevel converter (MMC) is an innovative structure that has expanded the usage of multilevel converters (MLCs) in the electrical industry. Since the MMC initially required a large number of sensors to manage the capacitor voltages, various studies have been done to reduce their number to improve the converter's reliability and reduce construction costs. In this paper's proposed method, merely two voltage sensors are used to balance the converter's capacitor voltages, and voltages are estimated using the exponentially weighted recursive least square (RLS) method in each sampling time. Also, the estimated voltages are sorted according to the capacitor current sign determined by the voltage sensors, and the current sensors are entirely eliminated. Furthermore, three cases for compensating the capacitor estimated voltages are presented, and the last case proposes the sub‐module force algorithm (SFA) for system protection. The efficacy of the proposed method has been assessed via simulation and experimental implementations.
... Recently, the modular multilevel converter (MMC) has been used frequently for its various advantages [1], [2], [3]. These include fully modular design, easy construction, excellent output waveform quality, and fault tolerance in high and medium power applications [4], [5]. ...
The modular multilevel converter (MMC) is a favored topology in the industry, but its reliability is at risk with an increase in the number of sub-modules (SMs) due to a rise in switching components. The essential need for maintaining capacitor voltage balance in each arm leads to increased complexity and cost, as numerous voltage sensors are required. This study introduces an innovative approach to minimize the number of voltage sensors by employing an enhanced algorithm for open-circuit fault detection in switches. The proposed scheme organizes each arm into groups, each containing two SMs and one voltage sensor, aiming to reduce the overall sensor count. A novel fault detection mechanism is presented, identifying open-circuit faults by comparing group output voltages in healthy and defective conditions. The capacitor voltage estimation algorithm in the sensor reduction scheme is noted for its simplicity compared to other methods. The effectiveness of these methods is validated through simulations and experimental implementations across diverse scenarios, affirming their reliability.
... Despite the success in decreasing the switching frequency and thus the losses in these topologies, they were plagued by problems such as complex structural design, control methods with a high computational burden, and insufficient reliability [8]. Therefore, MCs with modular topologies have been introduced as superior alternatives for high-voltage and power applications compared to the previous choices [9]. ...
The alternate arm multilevel converter (AAMC) is a new type of voltage source converter topology introduced as an attractive option for medium voltage and high-power applications. In AAMC, many series full-bridge sub-modules (FB-SM) are used to achieve high-voltage applications. Despite this, a large number of voltage and current sensors are needed in this converter to balance the capacitor voltage of the SMs. This paper proposes a new method to estimate the SM capacitor voltage that needs only one voltage sensor in each arm and a current sensor in the converter’s output to balance capacitor voltages. By using a proposed method based on a Kirchhoff voltage law and circuit relations govern on AAMC, the capacitor voltages can be determined. Contrary to voltage balancing control schemes based on individual sensors, the number of voltage sensors in the proposed method has been substantially reduced, and arm current sensors are eliminated. In addition, there is low estimation error since the capacitor voltages are calculated with high accuracy and updated depending on the arm voltage sensor and switching signals. Analysis of the proposed method in MATLAB Simulink for different scenarios indicates its validity.
... However, the reliability of the NNPC converter has received less attention from researchers. Semiconductor switches are one of the most fragile elements in the NNPC converter architecture; hence the converter's reliability is a major concern [13]. Semiconductor switches are generally exposed to short-circuit and open-circuit faults [14]. ...
The nested neutral point clamp (NNPC) converter is one of the most promising solutions for medium voltage motor drive applications. However, reliability due to the presence of semiconductor switches in the structure of this converter is one of the most critical concerns. The semiconductor switches are always one of the main components prone to failure. Switch failure can result in adverse effects, including system shutdown, poor system performance, and a reduction in overall system stability. Therefore, fault-tolerant converters are required to raise system availability in industrial applications. This research investigates and proposes the configuration of a fault-tolerant NNPC converter that uses a redundant phase to create a fault-tolerant converter. The redundant phase is in the bypass mode under normal operating conditions. After detecting the fault, the redundant phase will replace the faulty phase by utilizing a simple control scheme. Also, the proposed fault tolerance method is based on the cold reservation method, which will not increase the switching losses in the converter. The proposed fault-tolerant method’s feasibility and effectiveness are confirmed by simulating the NNPC converter under various scenarios in the MATLAB/Simulink environment.
The fault signals of power electronic devices are often accompanied by significant electromagnetic noise, making it difficult for single-feature extraction algorithms to capture periodic impact signals, while single-feature enhancement algorithms are easily disturbed by noise. To address this issue, this paper proposes an AdaESGMD-SPGL fusion method for fault diagnosis of power electronic switching devices based on the integration of feature extraction and enhancement concepts. The method first employs an improved Symplectic Geometry Mode Decomposition (SGMD) to perform an initial decomposition of the switching fault signal, then selects the mode with the highest energy as the feature signal, and finally applies Sparse Periodic Group Lasso (SPGL) to learn the periodic patterns of the feature signal’s characteristic frequency and perform envelope spectrum analysis. Experimental simulation results indicate that the improved SGMD significantly enhances the robustness of the SPGL algorithm against noise.
In multilevel converters (MCs), system components such as capacitors and semiconductor switches are very susceptible to damage. Furthermore, utilizing voltage sensors to balance capacitor voltages increases the system’s cost and complexity while decreasing reliability. This paper presents methods for voltage balancing of capacitors, capacitance monitoring, and open-circuit fault detection in a nested neutral point-clamped (NNPC) converter with a reduced number of voltage and current sensors. In the proposed method, converter capacitors’ voltage and current sensors are eliminated, and only the output sensors are employed to control the converter. In order to balance the voltage of capacitors, their voltages are estimated in three cases without using individual sensors. Comparing the capacitors’ measured and estimated voltage change ratios is used to assess their health in the monitoring method. Thus, the capacitors’ status can be checked by considering the system’s health indicator during each period. Furthermore, the open-circuit fault detection method can identify defective switches within one processing cycle by comparing the converter’s measured and standard output voltages in all switching states. The proposed methods have been evaluated in an experimental study of the system, and the results confirmed the effectiveness of the methods based on the new system configuration.
As the proportion of clean energy continues to increase, low carbon energy systems will be a significant way to achieve the goal of carbon neutrality. Therefore, the reliability of modular multilevel converters (MMCs) is particularly significant. However, conventional open-circuit fault diagnosis (OCFD) methods usually have a limited localization speed or are difficult to achieve in practical engineering. Therefore, a fast and simpled OCFD approach for MMC SMs based on an optimized deep learning is proposed in this article. In this approach, data on the of submodule capacitance voltages are input into a trained WOA-DKELM model without the manually settings. The problems of randomness in the regularization coefficient C and the kernel parameters K can be solved by DKELM with WOA optimization, which has a strong generalization capability and higher prognostic accuracy. The effectiveness of the proposed approach is verified by experiment results. This approach achieves an average identification probability of 0.96 within 20 ms of the fault.
In the present scenario, modular multilevel converters (MMCs) are considered to be one of the most promising and effective topologies in the family of high-power converters because of their modular design and good scalability; MMCs are extensively used in high-voltage and high-power applications. Based on their unique advantages, MMCs have attracted increasing attention from academic circles over the past years. Several studies have focused on different aspects of MMCs, including submodule topologies, modeling schemes, modulation strategies, control schemes for voltage balancing and circulating currents, fault diagnoses, and fault-tolerant control strategies. To summarize the current research status of MMCs, all the aforementioned research issues with representative research approaches, results and characteristics are systematically overviewed. In the final section, the current research status of MMCs and their future trends are emphasized.
This review article is mainly oriented to the control and applications of modular multilevel converters (MMC). The main topologies of the switching modules are presented, for normal operation and for the elimination of DC faults. Methods to keep the capacitor voltage balanced are included. The voltage and current modulators, that are the most internal loops of control, are detailed. Voltage control and current control schemes are included which regulate DC link voltage and reactive power. The cases of unbalanced and distorted networks are analyzed, and schemes are proposed so that MMC contribute to improve the quality of the grid in these situations. The main applications in high voltage direct current (HVDC) transmission along with other medium voltage (MV) and low voltage (LV) applications are included. Finally, the application to offshore wind farms is specifically analyzed.
Modularity and high reliability from redundancy are the two attractive advantages of Modular Multilevel Converters (MMCs). This paper elaborates a switch open-circuit fault diagnosis and a fault tolerant operation scheme for MMCs with distributed control. The proposed fault diagnosis and fault-tolerant control method can significantly improve the reliability of the MMC while maintaining the modularity of its software implementation. By distributing fault diagnosis into submodules, its local controller is capable of identifying the switching devices in open-circuit fault without extra hardware circuitry. Based on the real-time measurements of submodule terminal voltage and arm current, single or multiple faulty switches can be identified within 3.5 ms without triggering faulty alarms. Furthermore, a new fault-tolerant operation is proposed to maintain the output current, internal dynamics and switching harmonics unchanged after the faulty submodule is bypassed. This is achieved by resetting the period and phase registers in the local controller according to the information of bypassed submodules. The control loops of the MMC are not influenced by the proposed fault diagnosis and fault tolerant operation, making bthe operation transition seamless and reliable. Experimental results show that fault identification and system reconfiguration can be completed within 5 ms, and the MMC can seamlessly and smooth ride through the switch open-circuit faults without severe malfunction and catastrophic damages.
The modular multilevel converter (MMC) is attractive for medium- or high-power applications because of the advantages of its high modularity, availability, and high power quality. However, reliability is one of the most important issues for MMCs those are made of large number of power electronic submodules (SMs). This paper proposed an effective fault detection and localization method for MMCs. An MMC fault can be detected by comparing the measured state variables and the estimated state variables with a Kalman Filter. The fault localization is based on the failure characteristics of the SM in the MMC. The proposed method can be implemented with less computational intensity and complexity, even in case that multiple SMs faults occur in a short time interval. The proposed method is not only implemented in simulations with professional tool PSCAD/EMTDC, but also verified with a down-scale MMC prototype controlled by a real-time digital signal controller in the laboratory. The results confirm the effectiveness of the proposed method.
This paper presents a new multilevel converter topology suitable for very high voltage applications, especially network interties in power generation and transmission. The fundamental concept and the applied control scheme is introduced. Simulation results of a 36 MW-network intertie illustrate the efficient operating characteristics. A suitable structure of the converter-control is proposed.
Modular multilevel converters (MMCs) play an essential role in power conversion for medium and high voltage industrial applications. These types of converters use many sensors for the process of measuring and sorting the voltage of their capacitors, but this increases cost and hardware complexity, as well as decreases reliability. One of the most widely used methods for voltage sorting of capacitors in MMCs is based on current measuring and detecting the current sign of each arm. This paper uses the capacitor voltages estimation scheme by the Kalman filter (KF) algorithm at each sampling time. Moreover, with the difference between the total voltage of the capacitors in each arm during two consecutive processes, their sorting is done without the current sensor. Therefore, by the proposed scheme, current sensors are entirely removed from the arms, and the MMC control process is implemented by only two voltage sensors in a phase branch. The simulation results in the MATLAB Simulink environment confirm the accuracy of the proposed method.
Fault tolerant operation can significantly improve the reliability of a Modular Multilevel Converter (MMC), but the precondition is that a fast and accurate fault detection and localization method has been embedded into the MMC control system. This paper proposes a fault diagnosis method used in a distributed control architecture, which makes the local controllers capable of identifying the switching devices in open-circuit fault. Instead of using capacitor voltage, sub-module terminal voltage is measured for capacitor voltage control and fault diagnosis according to different sampling instances. The proposed fault diagnosis based on real-time measurements rather than a complicated algorithm can identify the faulty switches in a few sampling intervals, which is suitable for MMC systems with a large number of sub-modules and distributed control. The multiple switching device faults in different sub-modules can be identified by local controllers independently. Experimental results show that the proposed fault diagnosis method is able to locate faulty switches within 3ms and also immune from false alarms.
This paper presents a fault-tolerant configuration for the modular multilevel converter (MMC). The procedure is able to detect faults in voltage sensors and semiconductor switching devices, and it can reconfigure the system so that it can keep on operating. Both switch and sensor faults can be detected by comparing the output voltage of a set of submodules (SMs), which is measured by a so-called supervisory sensor, with two calculated reference voltages. Faults in the supervisory sensors are also considered. Sensor faults are overcome by using a measuring technique based on estimates that are periodically updated with the voltage measurements of the supervisory sensors. Additional SMs are included in the arms so that the MMC can bypass a faulty SM and continue operating without affecting the output voltage of the phase-leg. Experimental results obtained from a low-power MMC prototype are presented in order to demonstrate the effectiveness of the proposed techniques.
In this paper a new voltage measurement technique for modular multilevel converter (MMC) capacitors is proposed. While all the capacitors voltages should be known for closed loop control of MMCs, only the arms voltages are measured employing the proposed method. Therefore, the number of voltage sensors reduced dramatically to one per arm. The capacitors voltage quantities are updated continuously using the arms voltage and the switching signals. Although the proposed method precision is depended on the equality of the capacitors, presented investigations show that the steady state error and even transient error in capacitors voltage estimation is ignorable for the proper operation of the converter.
This study proposes a new fault detection method for modular multilevel converter (MMC) semiconductor power switches. While in common MMCs, the cells capacitor voltages are measured directly for control purposes, in this study voltage measurement point changes to the cell output terminal improving fault diagnosis ability. Based on this measurement reconfiguration, a novel fault detection algorithm is designed for MMCs semiconductor power switches. The open circuit and short circuit faults are detected based on unconformity between modules output voltage and switching signals. Simulation and experimental results confirm accurate and fast operation of the proposed method in faulty cell diagnosis. Implementation simplicity, no need to extra voltage measurements and multi faults detection ability are some other advantages of the proposed method
The modular multilevel converter (MMC) is distinguished by its modularity that is the use of standardized sub-modules (SMs). To enhance reliability and avoid unscheduled maintenance, it is desired that an MMC can remain operational without having to shut down despite some of its SMs are failed. Particularly, in this paper, complete fault diagnosis and tolerant control solution, including the fault detection, fault tolerance, fault localization, and fault reconfiguration, have been proposed to ride through the insulated gate bipolar transistor open-circuit failures. The fault detection method detects the fault by means of state observers and the knowledge of fault behaviors of MMC, without using any additional sensors. Then, the MMC is controlled in a newly proposed tolerant mode until the specific faulty SM is located by the fault localization method; thus, no overcurrent problems will happen during this time interval. After that, the located faulty SM will be bypassed while the remaining SMs are reconfigured to provide continuous operation. Throughout the fault periods, it allows the MMC to operate smoothly without obvious waveform distortion and power interruption. Finally, experimental results using a single-phase scaled-down MMC prototype with six SMs per arm show the validity and feasibility of the proposed methods.
This paper presents a fault detection and isolation (FDI) method for open-circuit faults of power semiconductor devices in a modular multilevel converter (MMC). The proposed FDI method is simple with only one sliding-mode observer (SMO) equation and requires no additional transducers. The method is based on an SMO for the circulating current in an MMC. An open-circuit fault of power semiconductor device is detected when the observed circulating current diverges from the measured one. A fault is located by employing an assumption-verification process. To improve the robustness of the proposed FDI method, a new technique based on the observer injection term is introduced to estimate the value of the uncertainties and disturbances; this estimated value can be used to compensate the uncertainties and disturbances. As a result, the proposed FDI scheme can detect and locate an open-circuit fault in a power semiconductor device while ignoring parameter uncertainties, measurement error, and other bounded disturbances. The FDI scheme has been implemented in a field-programmable gate array using fixed-point arithmetic and tested on a single-phase MMC prototype. Experimental results under different load conditions show that an open-circuit faulty power semiconductor device in an MMC can be detected and located in less than 50 ms.
This paper presents a fault detection and isolation (FDI) method for a Modular Multilevel Converter (MMC). This method can locate an open-circuit faulty device accurately and quickly. Based on a sliding mode observer (SMO) and a switching model of a half bridge, the approach is to assume the location of the fault, modify the observer equation and then compare the measured and observed states to verify, or otherwise, the assumption for possible fault locations. This technique requires no additional measurement elements and can easily be implemented in a microcontroller. The operation and robustness of the proposed method are confirmed using simulation results.
An Innovative Modular Multilevel Converter Topology Suitable for a Wide Power Range
- A Lesnicar
- I Introduction