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In the operation of battery energy storage systems based on the cascaded H-bridge converter, it is beneficial to balance the state of charge of batteries in different submodules within the converter phase-arm. This is achieved by distributing the active power among the submodules. Although multiple methods have been proposed for this purpose, they face the challenge of rendering optimal active power distributions that maximize balancing speed while meeting power constraints in the battery energy storage system. To overcome this challenge, a model predictive control scheme is developed in this article. The proposed method is remarkably robust against parametric uncertainties (battery voltage, capacity, etc.), as evidenced by its ability to tolerate a substantial 50% uncertainty in the parameters, resulting in a mere 0.05% steady-state error. Furthermore, because the predictive control can be executed at a low frequency, the computational burden is comparable to other existing methods.

The architecture of solid-state transformers (SSTs) is usually comprised with three-stage cascaded converters. The control of cascaded multistage SSTs is conventionally designed considering decoupled stages. Furthermore, the isolating stage, which is typically implemented with dual active bridge converters, employs a closed-loop control with a much larger bandwidth (BW) than the ac–dc stage. This disparity in the BWs can put a strain on the intermediate dc-link capacitors that connect the ac–dc and isolating stages, resulting in large capacitor voltage excursions when the load changes. In fact, this can result in ac–dc stage overmodulation and even large current overshoots through the isolating stage's high-frequency transformers. This necessitates advanced SST control strategies that can mitigate the aforementioned challenges. This article proposes a control design in which the state variables are selected as the sum of capacitor energies and differences in capacitor energies. Unlike the state-of-the-art SST controllers, the proposed integrated control approach creates a more balanced and safe distribution of energies among the dc-link capacitors during load transients. The control design is simplified as the difference in the control-loop BWs between the stages does not affect this disturbance attenuation ability. The effectiveness of the proposed control is demonstrated by experiments using a 1-kVA SST with two strings.

The cascaded H-bridge (CHB) low-capacitance static compensator (LC-StatCom) has a limited negative-sequence current injection capability compared to a conventional CHB StatCom, due to the comparatively larger oscillations on the capacitor voltages. Placing limits on the ability to provide negative-sequence current to the grid for a given capacitor size is required to prevent overmodulation. This article shows that these limits can be maximized by injecting an optimal third-harmonic circulating current. The effects of injecting the third-harmonic current on the capacitor voltages, both in balanced and unbalanced grid voltage conditions, are analyzed. Specifically, the procedure allows the knowledge of the potential capability of the LC-StatCom when injecting negative-sequence currents. The procedure is based on a linear programming approach. Although the procedure is applicable to any CHB StatCom, regardless of the submodule capacitor size, it is particularly important in LC-StatComs. To corroborate the proposed analysis, simulation and experimental results under balanced and unbalanced grid voltage conditions are presented.

In stand-alone dc microgrids (dcMGs), battery energy storage systems (BESSs) are conventionally used for regulating the dc-link voltage, causing a continuous battery operation. Though operating the photovoltaic (PV) system at its maximum power point (MPP) yields minimum battery discharge current, the opposite is true for battery charging current. Therefore, reducing the battery charging current based on its state-of-charge (SoC) and the amount of available PV surplus power (which can be treated as virtually stored energy) is an opportunity for improving the battery life. The main objective of the control strategy proposed in this article is to prolong the battery lifetime by reducing the charging current and keeping the battery SoC at lower values if the PV power is enough to supply the loads. Additionally, the PV system is used as the primary asset to regulate the microgrid voltage. The dynamic performance of the proposed control strategy is validated with experimental tests under various operating conditions. Furthermore, its effectiveness in prolonging the battery lifetime is evaluated using an aging model of a lithium-ion (Li-ion) battery (without loss of generality) by simulated case studies.

High penetration of renewable energy resources in the power system results in various new challenges for power system operators. One of the promising solutions to sustain the quality and reliability of the power system is the integration of energy storage systems (ESSs). This article investigates the current and emerging trends and technologies for grid-connected ESSs. Different technologies of ESSs categorized as mechanical, electrical, electrochemical, chemical, and thermal are briefly explained. Especially, a detailed review of battery ESSs (BESSs) is provided as they are attracting much attention owing, in part, to the ongoing electrification of transportation. Then, the services that grid-connected ESSs provide to the grid are discussed. Grid connection of the BESSs requires power electronic converters. Therefore, a survey of popular power converter topologies, including transformer-based, transformerless with distributed or common dc-link, and hybrid systems, along with some discussions for implementing advanced grid support functionalities in the BESS control, is presented. Furthermore, the requirements of new standards and grid codes for grid-connected BESSs are reviewed for several countries around the globe. Finally, emerging technologies, including flexible power control of photovoltaic systems, hydrogen, and second-life batteries from electric vehicles, are discussed in this article.