Measurement schemes with reduced number of sensors for modular multilevel converter

PhD ThesisDuring the last four decades there has been considerable development in voltage source converters (VSCs), which are widely contributed in multilevel converter topologies. Since then, multilevel VSC topologies have been used for applications with different power rating owing to the improvement of the output waveforms quality and minimising filtering requirements. In comparison with the conventional multilevel converters, modular multilevel converter (MMC) is considered as the most attractive topology for high and medium-power applications mainly due to the series connection of a high number of submodules (SMs). The challenges associated with the implementation of a high number of SMs includes: voltage-balancing of the distributed SM, cost, reliability and the increased complexity in the circuit configuration. Furthermore, achieving efficient and fast closed-loop control of the MMC requires the accurate knowledge of the voltage and current measurements, which means a considerable number of sensors are usually required to operate the MMCs. The main objective of this research is to propose several novel strategies for the converter to achieve voltage-balancing with fewer number of sensors to produce comparable performance to the sensor-based method. Four different sensorless schemes have been investigated, where two are current sensorless-based techniques and two are voltage sensorless-based techniques. The proposed current sensorless schemes are based on developed sorting algorithm, and the proposed voltage sensorless schemes employ two novel different recursive algorithms with the standard sorting algorithm. In regards to the voltage sensorless schemes, the first proposed method uses an exponentially weighted recursive least square (ERLS) algorithm, while the second proposed method employs a Kalman filter (KF) to estimate the SM capacitor voltages. Capacitance uncertainty has been investigated for the proposed voltage sensorless schemes. The proposed methods have been implemented via simulation but also on a scaled-down laboratory prototype. II The thesis also deals with capacitor diagnosis where a new scheme has been proposed which may be used for health monitoring technique, a comparison with an existing technique has been evaluated. Detailed simulations and experimental tests are carried out to investigate the performance of the proposed sensorless schemes, and results are compared with the sensor-based approach. These various schemes have been implemented and tested in real-time using a commercial floating point microcontroller where a 4-level single-phase MMC was employed. The results achieved for these novel schemes show an important improvement in the performance of the MMC under different operation conditions while fewer sensors were used.Libyan Ministry of Higher Education and Scientific Research for sponsoring this research and Zawia University

Submodule Voltage Estimation Scheme in Modular Multilevel Converters with Reduced Voltage Sensors Based on Kalman Filter Approach

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 by the controller used without the need for extra sensors. The substantial reduction in the number of voltage sensors improves the 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, the effect of variations in capacitance and inductance, of the impact of low carrier and effective switching frequency on the accuracy of the estimation, step changes to the load, and a range changes in DC voltage. The results obtained are experimentally verified using a single-phase MMC

Capacitor Voltage Estimation Scheme with Reduced Number of Sensors for Modular Multilevel Converters

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