Proportional-integral and proportional-resonant based control strategy for PUC inverters

In this paper, a proportional-integral (PI) and proportional-resonant (PR) based control strategy is proposed for packed-U-cell (PUC) inverters. In the conventional PI-PI based control strategy, while the first PI regulates the DC capacitor voltage, the second PI regulates the AC load current. However, it is shown that the second PI cannot guarantee zero tracking error in the load current. The main reason of this comes from the fact that PI controllers are not able to achieve zero tracking error for the AC signals. Also, in an attempt to reduce the tracking error by tuning PI gains distorts the load current. In this study, a PI-PR based control strategy is obtained by replacing the second PI by a PR controller. The performances of both PI-PI and PI-PR control methods have been compared. It is shown that the load current to tracks its reference in all circumstances provided that the inverter current reference is generated accurately. Computer simulations are conducted to show the steady-state and dynamic performances of both control methods

Mitigation of voltage imbalance in power distribution system using MPC-controlled packed-U-cells converter

Delivering high power quality in single-phase distribution has witnessed more challenges especially with the increased penetration of single-phase distributed generation (DG). This paper proposes a smart solid-state-based transformer, which aims to replace traditional ones, for single-phase distribution laterals, and provide load balancing and protection to the three-phase main feeders, that is based on connecting the single-phase lateral to the three-phase main feeder through a power electronics converter. This converter transfers balanced power from and to the three-phase feeder while automatically regulating the lateral single-phase voltage, hence, assuring high power quality without requiring any transformer on-load tap changer. A 7-level packed-U-cells (PUC) single-phase inverter topology was used to deliver single-phase regulated sinusoidal voltage to the AC loads, and at the same time, it is able to deliver DC power to DC loads. The simulation and hardware-in-the-loop (HIL) results have shown that the proposed topology delivers high power quality for both AC and DC loads under different operating scenarios. Moreover, the converter can play the role of a solid-state protection device coordinated with other up- and downstream protective devices. Finally, this system can be integrated within the smart grid allowing more flexibility for automation and efficient control of the grid. - 2019 The Authors. Energy Science & Engineering published by the Society of Chemical Industry and John Wiley & Sons Ltd.This work was made possible by Qatar University Internal Grant no. QUCP?CENG?EE?15/16?4

Predictive Switching Control for Multilevel Inverter using CNN-LSTM for Voltage Regulation

Now-a-days, model predictive control (MPC) is very commonly used for three phase inverters. But conventional MPC suffers computational complexities as well as unstable switching frequency issues. To address these issues related with conventional MPC model, this paper aims to use the benefits of deep learning model for predictive switching control. In this paper, CNN-LSTM network based predictive control is proposed for three phase inverters. Along with predictive control LC filter is cascaded to reduce the harmonics. The model is simulated using SIMULINK under fixed and dynamic load condition. The result shows decreased THD under different load conditions. Finally, the result is validated with existing models and achieves better performance

A Novel Control Approach to Hybrid Multilevel Inverter for High-Power Applications

This paper proposes a hybrid control scheme for a newly devised hybrid multilevel inverter (HMLI) topology. The circuit configuration of HMLI is comprised of a cascaded converter module (CCM), connected in series with an H-bridge converter. Initially, a finite set model predictive control (FS-MPC) is adopted as a control scheme, and theoretical analysis is carried out in MATLAB/Simulink. Later, in the real-time implementation of the HMLI topology, a hybrid control scheme which is a variant of the FS-MPC method has been proposed. The proposed control method is computationally efficient and therefore has been employed to the HMLI topology to mitigate the high-frequency switching limitation of the conventional MPC. Moreover, a comparative analysis is carried to illustrate the advantages of the proposed work that includes low switching losses, higher efficiency, and improved total harmonic distortion (THD) in output current. The inverter topology and stability of the proposed control method have been validated through simulation results in MATLAB/Simulink environment. Experimental results via low-voltage laboratory prototype have been added and compared to realize the study in practice.publishedVersio

CONTROL STRATEGIES OF DC MICROGRID TO ENABLE A MORE WIDE-SCALE ADOPTION

Microgrids are gaining popularity in part for their ability to support increased penetration of distributed renewable energy sources, aiming to meet energy demand and overcome global warming concerns. DC microgrid, though appears promising, introduces many challenges in the design of control systems in order to ensure a reliable, secure and economical operation. To enable a wider adoption of DC microgrid, this dissertation examines to combine the characteristics and advantages of model predictive control (MPC) and distributed droop control into a hierarchy and fully autonomous control of the DC microgrid. In addition, new maximum power point tracking technique (MPPT) for solar power and active power decoupling technique for the inverter are presented to improve the efficiency and reliability of the DC microgrid. With the purpose of eliminating the oscillation around the maximum power point (MPP), an improved MPPT technique was proposed by adding a steady state MPP determination algorithm after the adaptive perturb and observe method. This control method is proved independent with the environmental conditions and has much smaller oscillations around the MPP compared to existing ones. Therefore, it helps increase the energy harvest efficiency of the DC microgrid with less continuous DC power ripple. A novel hierarchy strategy consisting of two control loops is proposed to the DC microgrid in study, which is composed of two PV boost converters, two battery bi-directional converters and one multi-level packed-u-cell inverter with grid connected. The primary loop task is the control of each energy unit in the DC microgrid based on model predictive current control. Compared with traditional PI controllers, MPC speeds up the control loop since it predicts error before the switching signal is applied to the converter. It is also free of tuning through the minimization of a flexible user-defined cost function. Thus, the proposed primary loop enables the system to be expandable by adding additional energy generation units without affecting the existing ones. Moreover, the maximum power point tracking and battery energy management of each energy unit are included in this loop. The proposed MPC also achieves unity power factor, low grid current total harmonics distortion. The secondary loop based on the proposed autonomous droop control identifies the operation modes for each converter: current source converter (CSC) or voltage source converter (VSC). To reduce the dependence on the high bandwidth communication line, the DC bus voltage is utilized as the trigger signal to the change of operation modes. With the sacrifice of small variations of bus voltage, a fully autonomous control can be realized. The proposed distributed droop control of different unit converters also eliminates the potential conflicts when more than two converters compete for the VSC mode. Single-phase inverter systems in the DC microgrid have low frequency power ripple, which adversely affects the system reliability and performance. A power decoupling circuit based on the proposed dual buck converters are proposed to address the challenges. The topology is free of shoot-through and deadtime concern and the control is independent with that of the main power stage circuit, which makes the design simpler and more reliable. Moreover, the design of both PI and MPC controllers are discussed and compared. While, both methods present satisfied decoupling performances on the system, the proposed MPC is simpler to be implemented. In conclusion, the DC microgrid may be more widely adopted in the future with the proposed control strategies to address the current challenges that hinder its further development

Model predictive control applied to a single phase seven-level active rectifier

© 2017 IEEE. This paper presents an improved single phase seven-level active rectifier architecture controlled by finite control set model predictive control (FCS-MPC). The FCS-MPC is designed to enable power conversion with a unity power factor and generate seven level voltage waveform at the input. The proposed active rectifier architecture reduces harmonic contents of the rectifier input current by producing different voltage levels at the rectifier input. Owing to the architecture and multilevel operation, it reduces the EMI filter size, input current harmonic, the voltage rating on devices and switching losses that are lower than those of conventional three-level rectifier topologies. The proposed converter can also be operated as a multilevel inverter. Extensive simulation results are presented to verify the proposed converter when the load changes, the reference active and reactive power changes

Model Predictive Control Technique of Multilevel Inverter for PV Applications

Renewable energy sources, such as solar, wind, hydro, and biofuels, continue to gain popularity as alternatives to the conventional generation system. The main unit in the renewable energy system is the power conditioning system (PCS). It is highly desirable to obtain higher efficiency, lower component cost, and high reliability for the PCS to decrease the levelized cost of energy. This suggests a need for new inverter configurations and controls optimization, which can achieve the aforementioned needs. To achieve these goals, this dissertation presents a modified multilevel inverter topology for grid-tied photovoltaic (PV) system to achieve a lower cost and higher efficiency comparing with the existing system. In addition, this dissertation will also focus on model predictive control (MPC) which controls the modified multilevel topology to regulate the injected power to the grid. A major requirement for the PCS is harvesting the maximum power from the PV. By incorporating MPC, the performance of the maximum power point tracking (MPPT) algorithm to accurately extract the maximum power is improved for multilevel DC-DC converter. Finally, this control technique is developed for the quasi-z-source inverter (qZSI) to accurately control the DC link voltage, input current, and produce a high quality grid injected current waveform compared with the conventional techniques. This dissertation presents a modified symmetrical and asymmetrical multilevel DC-link inverter (MLDCLI) topology with less power switches and gate drivers. In addition, the MPC technique is used to drive the modified and grid connected MLDCLI. The performance of the proposed topology with finite control set model predictive control (FCS-MPC) is verified by simulation and experimentally. Moreover, this dissertation introduces predictive control to achieve maximum power point for grid-tied PV system to quicken the response by predicting the error before the switching signal is applied to the converter. Using the modified technique ensures the iii system operates at maximum power point which is more economical. Thus, the proposed MPPT technique can extract more energy compared to the conventional MPPT techniques from the same amount of installed solar panel. In further detail, this dissertation proposes the FCS-MPC technique for the qZSI in PV system. In order to further improve the performance of the system, FCS-MPC with one step horizon prediction has been implemented and compared with the classical PI controller. The presented work shows the proposed control techniques outperform the ones of the conventional linear controllers for the same application. Finally, a new method of the parallel processing is presented to reduce the time processing for the MPC