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This article presents a circulating current reference generator based on a constrained model predictive control approach to perform the intercluster capacitor voltage balancing in modular multilevel matrix converters (M3C). The proposed reference generator incorporates nominal current limits as bound constraints into the optimal control problem. This approach enables the reference generator to efficiently provide the necessary circulating current in each cluster, thereby balancing the energies of the converter's clusters. As a result, the M3C can operate even during critical frequency points, significant power steps, and severe imbalance levels while ensuring that every cluster current remains within its feasible limits. Experimental results on a M3C prototype of 36 submodules are provided to validate the effectiveness and high-quality performance of the proposed strategy.

Cascaded H-bridge (CHB) converters are an attractive candidate for numerous applications, including static synchronous compensators and next-generation photovoltaic and battery energy storage inverters. Due to its simplicity, scalability, and excellent harmonic performance, phase-shifted pulsewidth modulation (PS-PWM) is one of the preferred modulation strategies for CHB converters. However, the latter advantage might be drastically affected when an unbalanced operation in the H-bridge cells is required, e.g., setting different dc-voltage levels and/or ac-voltage references among cells. This work proposes a predictive optimal variable angle PS-PWM (OVA-PS-PWM) strategy for CHB converters. The proposed OVA-PS-PWM introduces a bilinear dynamic model that describes the impact of the phase-shift angles (PS-angles) over the CHB output voltage harmonics. This model is then employed to formulate an optimal control problem that minimizes the output voltage harmonic distortion. An analytical optimal solution for a PS-angle update rule that applies to CHB converters of any number of cells is derived. As a result, the proposed OVA-PS-PWM updates each PS-angle at every sampling instant, significantly improving the harmonic content of the CHB output voltage even under severely unbalanced operation scenarios. Experimental results are provided with a CHB converter with nine cells to verify the effectiveness of the proposed optimal modulation strategy.

The modular multilevel matrix converter (M3C) is a direct ac-ac power converter that presents several features such as scalable and flexible structure, high efficiency, fault-tolerant capability, and high power quality. However, this converter requires a complex control strategy to govern the cluster currents and balance the internal floating capacitor voltages among clusters and cells. To fulfill these requirements, this article proposes a long-horizon sequential finite-control-set model predictive control (sFCS-MPC). The resulting predictive strategy is formulated to perform both the local cell balancing control and to regulate cluster currents of the M3C in a unified control algorithm, considering the nonlinear and coupled dynamic model of each cluster. Additionally, the total available combinations and the average cell switching frequency are reduced. The proposed sFCS-MPC is implanted for a prediction horizon from one to four, and compared with some previous FCS-MPC approaches. Experimental results on a 3-kW prototype are provided to demonstrate the effectiveness and high-quality performance of the proposed strategy.

Grid-connected AC/DC power converters play a crucial role in integrating renewable energies, smart grids, and motor drives. Consequently, high-performance control techniques have constantly attracted the interest of researchers. Predictive direct power control (P-DPC) strategies are promising control techniques for these converters, due to their fast transient response. However, standard P-DPC strategies cannot effectively compensate for steady-state errors when the switching frequency is reduced, due to model inaccuracies. This work proposes a new optimal switching sequence direct power control (OSS-DPC) strategy, which enhances the converter discrete-time model by estimating the grid currents and voltages at each commutation instant within a sampling period. As a result, the proposed OSS-DPC provides a fast dynamic response with reduced overshoot and improved steady-state performance, outperforming the standard P-DPC strategies.

Modular multilevel matrix converters stand out for their performance in ac-ac high-power conversion. However, they require multiple control loops to govern the currents from both ac ports, the internal circulating currents, and the capacitor voltages. This article proposes a computationally efficient model predictive control (MPC) strategy based on a new converter modeling to exploit the phase-shifted pulsewidth modulation working principle fully, achieving four improvements: 1) control unification of both ac-ports currents, circulating currents, and capacitor voltages; 2) constrained optimization to safeguard the converter limits; 3) computational burden reduction and high scalability compared to standard MPC strategies; and 4) wide frequency operation with fast closed-loop transient responses, low harmonic distortion, and fixed switching frequency.

This paper presents a versatile and effective model predictive current control strategy based on optimal switching sequences for four–leg two–level grid–connected converters. The proposed control methodology, presents an excellent dynamic performance, good tracking of high-frequency reference signals, fixed switching frequency, and well-formed harmonic spectrum, enabling the proposed controller to govern shunt active filters and distributed generation applications based on four-leg converters. Experimental results demonstrate the effectiveness and high-quality performance obtained with the proposed strategy.

Modular multilevel converters (MMCs) have become one of the most popular power converters for medium/high-power transmission systems and motor drive applications. Standard control schemes for MMCs use a voltage measurement per submodule (SM) to balance the capacitor voltages and govern the MMC. Consequently, the control system requires a significant amount of sensors and the effective communication of sensitive data under relevant electromagnetic interference (EMI), impacting the reliability and cost of the MMC. This work presents a distributed neural network (DNN) observer inspired by a general predictor-corrector structure for estimating the capacitor voltages at each SM. The proposed observer predicts each SM capacitor voltage using a standard average model. Then, each prediction is corrected and denoised by a neural network of reduced computational complexity. As a result, the proposed observer reduces the number of required voltage sensors per arm to only one and filters the high-frequency noise without noticeable delay in the estimated SM capacitor voltages for both transient and steady-state operations. Experiments conducted in a three-phase MMC with 24 SMs confirm the effectiveness of the proposed DNN observer.

Model predictive control has emerged as a promising approach to govern modular multilevel converters (MMCs), due to its flexibility to include multiple control objectives and simple design process. However, this control scheme presents relevant issues, such as high computational complexity and variable switching frequency. This work proposes a sequential phase-shifted model predictive control (PS-MPC) for MMCs. The key novelty of this proposal lies in the way the predictive control strategy is formulated to fully exploit a phase-shifted pulsewidth modulation technique through an appropriate choice of synchronized average models for each carrier. In this way, the proposed predictive controller obtains independent optimal modulating signals for each carrier in a sequential manner, by solving an optimization problem with reduced computational effort independent of the number of submodules. This sequential optimization allows one to formulate the optimal control problem to achieve multiple control objectives, similarly to the finite-control-set MPC (FCS-MPC). Nevertheless, the MMC governed with the proposed PS-MPC generates an output voltage with fix-spectrum and operates with an even power loss distribution among semiconductors in steady-state, outperforming the standard FCS-MPC strategy. Experimental results are provided to verify the proposed PS-MPC effectiveness when governing a three-phase MMC with four half-bridges per stack.

Cascaded H-bridge (CHB) converters are attractive candidates for next generation photovoltaic (PV) inverters. CHB converters present a reduced voltage stress per power switch and a high modularity. Therefore, the plant can be divided in several PV strings that can be connected to each H-bridge cell. However, due to variability on solar irradiance conditions, each PV string may present different maximum available power levels, which difficult the overall converter operation. To address this issue, this article presents a model predictive control (MPC) strategy, which works along with a phase-shifted pulsewidth modulation (PS-PWM) stage; hence, its name phase-shifted MPC (PS-MPC). The novelty of this proposal is the way both interbridge and interphase power imbalance are directly considered into the optimal control problem by a suitable system reference design. Thus, the interphase imbalance power is tackled by enforcing the converter to operate with a proper zero-sequence voltage component. Then, by exploiting the PS-PWM working principle, PS-MPC is able to handle each H-bridge cell independently. This allows the predictive controller to also deal with an interbridge power imbalance using the same control structure. Experimental results on a 3-kW prototype are provided to verify the effectiveness of the proposed PS-MPC strategy.

Model predictive control (MPC) has emerged as a promising approach to govern modular multilevel converters (MMCs) due to its flexibility to include multiple control objectives and its simple design process. However, this control scheme presents relevant issues, such as high computational complexity and the proper references design requirement. This work proposes a phase-shifted model predictive control (PS-MPC) for MMCs with an optimal circulating currents reference governor based on a quadratic programming MPC (QP-MPC). The PS-MPC is formulated to fully exploit a phase-shifted pulsewidth modulation technique by obtaining independent optimal modulating signals for each carrier sequentially, with reduced computational effort independent of the number of submodules. Moreover, the proposed QP-MPC reference governor improves the overall dynamic performance of the MMC and brings flexibility for prioritizing the capacitor voltage ripples reduction or the MMC efficiency by changing the weighting factors of its cost function. Simulation results are provided to verify the proposed control scheme's effectiveness when governing a three-phase MMC with four half-bridges per arm.

Cascaded converters have risen as a suitable solution for the connection of Utility-scale Battery Energy Storage Systems (BESS) to the grid. These converters allow to split the battery array into the power modules, reducing the total series-connected battery cells and improving the reliability of the system. Different types of modules have been proposed to integrate the batteries in the converter. The three-port full-bridge module connects the batteries through a second deport decoupled from the harmful low-frequency oscillations and current peaks. However, the multi-variable controller required to manage the power interaction between the battery and the grid presents a challenge in terms of computational burden and scalability. This work proposes the use of the Sequential Phase-Shifted Model Predictive Control (PS-MPC) in a multilevel BESS implementation using three-port full-bridge modules. The proposed controller outperforms a standard FCS-MPC, as it obtains the optimal duty cycles for the operation of the converter with the same fast dynamic response, but also with the fixed spectrum of the PS-PWM and low computational burden, which facilitates its scalability to multilevel BESS with a large number of cells. Simulation results show the ability of the system to exchange different amounts of power with the grid, ensuring the best battery operational conditions.

© 2019 IEEE. Multilevel inverters are widely used in the medium voltage energy market. Among them, the Cascaded H-Bridge (CHB) and Modular Multilevel Inverter (MMC) stand out for their modular hardware, which allows the easy replacement of their modules in the case of failures. Normally, these converters are operated with centralized control schemes, which require a large processing capacity, multiple digital outputs and wires for the switching signals of the transistors. The use of a centralized controller reduces the modularity of the system and generates difficulties as the number of inverters connected in series (cells) increases. In this work, a distributed control strategy for CHB converters is proposed, allowing each cell to have an independent local controller, which increases the modularity of the multilevel converter without deteriorating the performance of the system. Extensive simulations are carried out, showing the advantages and disadvantages of the proposed distributed control strategy offers when compared to a PI current controller on dq axes and Shifted PWM. The proposed control scheme is also tested under fault conditions and is finally applied in a Field Oriented Control (FOC) of a permanent magnet synchronous machine (PMSM), in order to evaluate its performance in electrical drives applications.