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Group measurement of capacitor voltage and capacitance online monitoring for modular multilevel converter
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Modular multilevel cascade converters (MMCCs) are considered a promising power electronics topology in industry. Their scalability allows to reach (ultra/very) high voltage levels with low harmonic content and high efficiency and makes MMCCs an ideal solution for high-power applications; such as electrical drives, solid-state transformers, and high-voltage direct-current (HVdc) transmission systems. However, the high levels of thermal, electrical, and mechanical stress on the power electronics devices and the large number of components (e.g., capacitors or semiconductors) make MMCCs prone to faults. Fault detection and diagnosis (FDD) in combination with fault isolation and system reconfiguration techniques, based on cell redundancy, can increase the reliability, availability, and safety of MMCCs, which is crucial for their utilization in critical energy applications. This second part of the article comprehensively surveys: 1) fault tolerance and FDD; e.g., expert system, model-, or hardware and data-based FDD methods, and 2) system reconfiguration strategies (e.g., cold- or hot-redundant) for MMCCs. Finally, the state of the art, challenges, and future research trends and opportunities toward reliable MMCC-based systems are revealed.
Modular Multilevel Cascade Converters (MMCCs) are considered a promising power electronics topology in industry. Their scalability allows to reach (ultra/very) high voltage levels with low harmonic content and high efficiency and makes MMCCs an ideal solution for high-power applications; such as electrical drives, solid-state transformers and high-voltage direct-current (HVDC) transmission systems. However, the high levels of thermal, electrical and mechanical stress on the power electronics devices and the large number of components (e.g. capacitors or semiconductors) make MMCCs prone to faults reducing its reliability. In this first part of the paper, a comprehensive overview of reliability on MMCCs, failure mechanisms and fault impact analysis in MMCCs, including failure rates and fault modes is presented. Also a set of tables which collect all information to easily detect and identify faults in MMCCs is presented.
This paper presents an online health monitoring scheme for dc capacitors in modular multilevel converters(MMCs). The health monitoring algorithm is based on detecting changes in the dc capacitance value over time. The proposed algorithm only utilizes measurements that are typically available in flexible alternating current transmission systems (FACTS) and high-voltage direct current (HVDC) applications. Hence, in the proposed estimation method, no additional sensors are used. The estimation scheme considers the presence of noise in voltage and current measurements, and utilizes a recursive least square (RLS) estimator in conjunction with a special low-pass filter to minimize the estimation errors. Simulation results of a hardware replica, as well as experimental results on a low-power MMC prototype show that the proposed scheme can identify the dc-link capacitance value with a maximum error of 1%.
Capacitors are critical components of power converter systems as they influence the cost, size, performance, and scale of such systems. However, capacitors exhibit the highest degeneration and breakdown rates among all power converter components due to their wear-out failures and short lifespans. Therefore, condition monitoring is a vital process to estimate the health status of capacitors and to provide predictive maintenance for ensuring stability in the operation of power converter systems. The equivalent series resistance (ESR) and the capacitance of the capacitor are two widely used parameters for evaluating the health status of capacitors. Unlike the ESR, the capacitance of a capacitor is suitable for the health monitoring of various types of capacitors; therefore, it is more preferable for large-scale systems. This paper presents an overview of previous research addressing this aspect of capacitors and provides a better understanding of the capacitance monitoring of capacitors utilized in power converter systems.
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 paper proposes a novel capacitor condition monitoring method for modular multilevel converters (MMCs) based on reference sub-modules (SMs). It significantly enhances the capacitor monitoring accuracy by making full use of the SM voltage sensor measurement range. An accuracy comparison between the existing method and the proposed method is conducted to quantify the improvement of accuracy. Moreover, its operation principle and practical implementation considerations are presented. Finally, a three-phase MMC platform is conducted experimentally to verify the effectiveness of the proposed method.
Modular Multilevel Converters (MMCs) have established their position as the choice of next-generation high voltage converters. These converters, however, require a bulk number of sensors in each phase for Sub-Modules (SMs) voltage balancing. A limited number of studies are found in the literature where the number of sensors is reduced by incorporating observers to estimate the SM voltages. Nonetheless, most of these methods require accurate measurements of the arm voltage. Thus, the dependency on sensors is not completely eliminated. In this paper, a Kalman-filter-based estimation of SM voltages is presented, which does not require any voltage sensor to measure the arm voltage. Therefore, this method considerably simplifies the implementation of MMCs. Extensive simulations and experimental test cases are conducted to validate the performance of the proposed SM voltage estimation method. The performance assessments verify the accuracy and robustness of the proposed method for various test scenarios performed over a wide range of sampling frequencies.
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. Reliability is one of the most important challenges for the MMC consisting of a large number of submodules (SMs). The capacitor monitoring is one of the important issues in the MMC. This paper proposed a reference submodule (RSM)-based capacitor monitoring strategy for the capacitance estimation in the MMC, where the capacitances in the monitoring SMs can be estimated based on the capacitor voltage relationship between the RSM and the monitoring SMs. The proposed monitoring strategy does not rely on the information of all capacitor voltage and current, which effectively simplifies the algorithm for capacitance estimation. The simulation studies with the time-domain professional tool PSCAD/EMTDC are conducted and a down-scale MMC prototype is also tested in the laboratory with the proposed capacitor monitoring strategy. The study results confirm the effectiveness of the proposed capacitor monitoring strategy.
This paper presents a new voltage estimation method for the submodule (SM) capacitor in a modular multilevel converter (MMC). The proposed method employs a Kalman filter (KF) algorithm to estimate the SM voltages of the converter. Compared with sensor-based methods, this scheme requires only one voltage sensor to achieve the voltage-balancing of the converter. This sensor is connected to the total arm voltage; the proposed algorithm requires also the switching patterns of each upper SM switch which are provided from the processor used without the need for extra sensors. This impressive reduction in the number of voltage sensors improves system reliability and decreases its cost and complexity. Extensive simulation and experimental analyses carried out to validate the proposed estimation scheme under different conditions include steady-state analyses and investigation of the effect of variations in capacitance and inductance and the effect of low carrier and effective switching frequency on the accuracy of the estimation, step changes in load conditions, faults and a range changes in DC voltage. The results obtained are validated based on a single-phase MMC.
The modular multilevel converter (MMC) is expected to be used extensively in high-voltage direct current (HVDC) transmission networks because of its superior characteristics over the line-commutated converter (LCC). A key issue of concern is balancing sub-module capacitor voltages in the MMCs, which is critical for the correct operation of these converters. The majority of voltage balancing techniques proposed thus far require that the measurement of the capacitor voltages use a reliable measuring system. This can increase the capital cost of the converters. This paper presents a voltage balancing strategy based on capacitor voltage estimation using the adaptive linear neuron (ADALINE) algorithm. The proposed estimation unit requires only three voltage sensors per phase for the arm reactors and the output phase voltages. Measurements of sub-module capacitor voltages and associated communication links with the central controller are not needed. The proposed strategy can be applied to MMC systems that contain a large number of sub-modules. The method uses PSCAD/EMTDC, with particular focus on dynamic performance under a variety of operating conditions.
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.
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 capacitor condition monitoring is an important issue for the reliable operation of modular multilevel converters (MMCs) in high-voltage applications. The numerous capacitors make the monitoring for the capacitor condition complex and computation-consuming. This paper proposes a hierarchic capacitor condition monitoring strategy to assure the reliability of high-voltage MMCs. In the strategy, the switching times of the switching signals are counted to detect the condition of the capacitor in each submodule (SM). Then, the subsequent capacitance calculation method is only conducted to the abnormal capacitors indicated by the above condition detection algorithm. Meanwhile, the variations of the measured and reference capacitor voltages are employed to calculate the capacitance in the proposed method. The condition detection algorithm shrinks the scope where the abnormal capacitors locate, which avoids calculating the total capacitances in MMCs. In the proposed capacitance calculation method, the complex operations are further saved. Both the two measures reduce the computation burden effectively. The implementation of the whole monitoring strategy is simple and fit for high-voltage MMCs. Moreover, the strategy has no adverse influence on the normal operation of MMCs. The effectiveness of the proposed strategy is verified by the simulation studies with the professional tool Matlab/Simulink.
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.
Recently, the nested neutral point clamped (NNPC) converter has been developed for medium voltage applications. This converter has been considered for its desirable properties, such as application in a wide range of voltages, the low voltage stress on the switches, and excellent output waveform quality. This study presents a fast open-circuit fault detection method in semiconductor switches. The proposed method only requires the measurement of output voltage. The output voltage of the converter is investigated in different switching states. If there is a discrepancy in the converter output in normal mode and after the fault, the defective switch is identifiable. The proposed method has been investigated in the MATLAB Simulink environment under different scenarios. The simulation results confirm the desired performance of the proposed method.
Multilevel converters (MLCs) are pioneers in the field of electrical energy conversion. From the classification of MLCs, modular multilevel converter (MMC) is very popular due to its attractive structure and performance. The modular nature and no need for isolated DC resources are two great advantages in this converter, but the need for many sensors to control its performance is a significant drawback. In addition, the internal circulating current in the MMC causes losses, decreases efficiency, and increases the voltage ripple of capacitors. In this paper, combining a new capacitor voltage sorting method and an open-loop controller based on arms energy estimation is proposed to control the MMC using two voltage sensors in the arms and one current sensor at the output. The proposed method ensures continuous voltage balancing of the capacitors and removes multiple voltage sensors from sub-modules (SMs). The simulation and experimental results verify the accuracy and effectiveness of the proposed method.
Modular multilevel converter (MMC) with reduced number of voltage sensors is conducive to the reduction of equipment cost and hardware complexity, however, usually resulting in the performance degradation. For example, when only one voltage sensor is equipped for the measurement of arm voltage, estimation of capacitor voltages may be not accurate enough, moreover, condition monitoring and fault diagnosis of submodules (SMs) are hard to implement. Thus, capacitor voltage estimation with capacitance self-updating based on grouping measurement (GM) is proposed in this article. By grouping and updating SM capacitance periodically, the accuracy of voltage estimation is greatly increased, meanwhile, severely aging or faulty capacitors can be detected, convenient for prompt replacement. Furthermore, GM-based fault diagnosis and fault disposal are proposed. Utilizing the measured and estimated group voltages, single or multiple SM open-circuit failures can be located in several sampling cycles and the isolating time of faulty SMs can be easily obtained even considering the time delay of bypass switch. Therefore, capacitor overvoltage and current distortion during SM failures are restrained effectively, which enhances the reliability and achieves seamless operation of MMC. Finally, the effectiveness of the proposed scheme is confirmed by simulation and experimental results.
This paper proposes a state observer (SO) based capacitor-voltage-balancing method for modular multilevel converters (MMCs) without arm-current sensors. Without the knowledge of the actual arm-current signals, this method can balance capacitor voltages while reducing the sampling signals, compacting the control system and saving the overall cost. In this paper, the arm-current value estimated by an SO, instead of the measured one, is employed to determine which sub-modules (SMs) should be inserted or bypassed. Furthermore, the design procedure of the proposed SO is presented. In addition, a medium voltage MMC (20 kV, 25 MW) simulation model using Matlab/Simulink is constructed to verify the proposed method. Finally, the proposed method is also validated by experimental results based on a scaled-down MMC prototype.
This letter proposes a new submodule capacitor condition monitoring method for modular multilevel converters (MMCs) based on the dc-side start-up procedure. During this process, the MMC can be simplified into an
RC
charging circuit, and the submodule capacitance can be estimated by investigating its relationship with the phase current and submodule voltage. Several practical issues related to the implementation, advantages, and limitations of the proposed method are presented as well. In order to validate the method, a series of experiments with different submodule capacitances are conducted based on a three-phase MMC platform. Experimental results confirm the effectiveness and feasibility of the proposed method.
Modular multilevel converters (MMCs) are emerging as a promising topology for medium/high-power applications. Aluminum electrolytic capacitors (AECs) are usually employed in MMCs as floating capacitors due to their high volumetric efficiency and low price. AECs gradually deteriorate over time due to electrolyte vaporization and for this reason, they have been recognized as one of the most fragile components in the converter. As they continue to age, the AEC's capacitance decreases and its equivalent series resistance (ESR) increases which can result in an increase of submodule (SM) capacitor voltage ripple, power loss, and could damage the operation of the MMC with prolonged use of the aged capacitors. To prevent such damage, monitoring the health of capacitors is an important step to enhance the reliability of the MMC by predictive maintenance. This paper presents a failure prediction scheme for SM capacitors in the MMC by monitoring the SM capacitor voltage oscillations. Detailed simulation studies are carried out for a five-level MMC in PLECS platform and verified experimentally. The estimated capacitance through simulations and experiments are in close agreement to that value measured using the LCR meter.
This letter proposes a currentless sorting and selection (SAS) based capacitor-voltage-balancing method for modular multilevel converters (MMCs). Without the knowledge of arm-current signals, this method has almost the same performance as the conventional SAS method while reducing the sampling signals, compacting the control system and saving the overall cost. In this letter, the derivative of the total capacitor voltage of an arm, instead of the arm current, is employed to determine which sub-modules (SMs) should be inserted or bypassed. Furthermore, the efficacy of the proposed method is verified by experimental results.
In this paper, an improved post-fault strategy is introduced for Modular Multilevel Converters (MMCs), which utilizes the remaining healthy capacity of the converter more efficiently and increases the line voltage amplitude under these circumstances. Previous works proposed to use the neutral point shift in AC side and DC side of the converter simultaneously. This paper adds a comprehensive and coherent formulation, deep analyzation, and experimental validation. The main improvement of proposed method is maximizing the line voltage amplitude using the optimum DC component and the best neutral point position. Indeed, fewer restrictions in fault numbers, fewer restrictions in load power factor, and fewer non-solution conditions are among other improvements of Combined DC and Neutral Shift (CDCNS) method. Comparative simulation and experimental results verify the effectiveness of the proposed method.
This paper presents a new method to measure the voltage across the submodule (SM) capacitors in a modular multilevel converter (MMC). The proposed technique requires only one voltage sensor per arm. This reduces the number of sensors required compared to conventional sensor-based methods. Therefore, the cost and complexity of the system are reduced, which in turn improves the converter’s overall reliability. The proposed method employs an exponentially weighted recursive least square (ERLS) algorithm to estimate the SM capacitor voltages through the measured total arm voltage and the switching patterns of each SM. There is thus no need for extra sensors to measure these control signals as they are directly provided from the controller. The robustness of the proposed method is confirmed via introducing deviations for the capacitance values, dynamic load changes, DC voltage change and start-up transient condition. Simulation and experimentally validated results based on a single-phase MMC show the effectiveness of the proposed method in both, steady-state and dynamic operations.
This paper employs a Kalman filter (KF) algorithm to estimate the capacitance of submodule (SM) capacitors in modular multilevel converters (MMCs). The proposed method can be used in the health condition monitoring technique of the capacitors. This proposed scheme estimates the capacitance of each individual capacitor from data of arm current and the corresponding voltage across the targeted capacitor. The arm current is used to calculate the capacitor current from the upper state of the SM switch. The proposed method has shown very good performance under normal operating conditions. The effectiveness of the proposed technique is validated via a MATLAB simulation analysis of a single-phase four-level MMC.
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 paper proposes a condition monitoring scheme of submodule (SM) capacitors in the modular multilevel converters (MMC), which is based on the capacitance estimation using the information of the current and voltage ripples of the capacitors. In order to induce the voltage ripple in the capacitor, a controlled AC current is injected into the circulating current loop through the action of the average voltage control of each SM in the converter leg. The capacitor current is calculated from the arm current and its switching state. By processing these AC voltage and current with digital filters, the capacitance is estimated by a recursive least square (RLS) algorithm. The validity of the proposed scheme has been verified by simulation results for the 1-MW 7-level modular multilevel converter. Also, its feasibility has been proved by experimental results for a reduced-scale prototype.
This paper presents a new technique for measuring the capacitor voltages in a modular multilevel converter using a reduced number of voltage sensors. With this technique, the minimum number of voltage sensors per arm is two. Each sensor measures the output voltage of a set of submodules (SMs) connected in series and acquires a new measurement when there is only one SM activated within the set. The acquired value corresponds to the capacitor voltage of the activated SM minus the voltage drops produced in the switches. A simple mathematical model is used to estimate all the SM capacitor voltages, and it is then updated whenever there is a new measurement available. An algorithm that enforces the periodic update of the voltage measurements is also presented. The proposed measuring technique highly reduces the number of voltage sensors; hence reducing the complexity and costs of the signal conditioning and data acquisition stages. Simulation and experimental results are presented to demonstrate the efficiency of the proposed technique.