In recent years, the combination of battery energy storage systems and static synchronous compensators in a single device, known as ES-STATCOM, has been studied by both academia and industry. The modular multilevel converter (MMC) is an interesting candidate for ES-STATCOM realization. The integration of batteries based on dc/dc converter presents advantages in terms of design flexibility. However, there is a gap in the literature in terms of design and cost-optimization of ES-STATCOM systems. To fill this void, this paper provides a methodology to support engineers to design and perform cost-optimization of ES-STATCOM systems. Both capital expenditures (CAPEX) and operational expenditures (OPEX) due to energy losses and battery replacement are taken into account. The methodology identifies what is the optimum submodule voltage reference which minimizes the ES-STATCOM total cost for a given target of operating time. A lifetime model is employed to predict if battery replacement is required. This model computes the battery capacity fade caused by the operation mission profile considering both calendar and cycling aging mechanisms. The case study is based on a 25 MVA/75 MWh ES-STATCOM connected to a 34.5 kV grid, which provides ancillary services for a photovoltaic (PV) power plant. Different rated blocking voltages are assumed for the semiconductor devices. Moreover, different maximum and minimum allowed state-of-charge (SOC) are adopted in the converter design. The proposed methodology can also be used to find the optimum combination of the battery and IGBT part-numbers based on a given initial set.

Modular multilevel converter-based battery energy storage systems (MMC-based BESS) can play an important role when applied to power systems, for example, stabilizing and improving power quality. The integration of batteries in an MMC is usually performed in two ways: single-stage (SS) and two-stage (TS) (i.e., with dc/dc converter). Different references discuss the control strategies, sizing methodologies, and the advantages/drawbacks of these approaches. However, a deep comparison of these topologies is still missing in the literature. Thus, benchmarking SS and TS approaches is provided in this work. The battery current spectrum, the battery lifetime, the converter power losses, and the total costs are evaluated for both approaches. In addition, energy oversizing due to rounding is an important figure of merit since batteries account for a large amount of the costs. The case study is evaluated considering commercial battery racks (standard solution) and battery cells (customized solution). For the case studies, different insulated gate bipolar transistor (IGBT) models and states of charge (SOC) ranges are considered. The system under review is a 10.9 MVA/5.76 MWh connected to a 13.8 kV power system. This system aims to perform a time-shift for an industry. In an analysis to optimize the costs of a project that evaluates several variables, the best configuration option is found in the most balanced option. In this sense, when balancing costs in project sizing, power losses, and battery replacement, the optimal design is the SS approach in the customized solution.

In recent years, the integration of battery energy storage systems (BESSs) with multilevel modular converters (MMCs) has received interest in power system applications. In this work, this configuration is called a MMC-based BESS. The batteries are connected directly to the MMCs on submodules (SMs), called the single-stage approach. Several control strategies have been proposed to guarantee the proper operation of a MMC-based BESS. This system is complex due to the control strategy. Another challenge is in obtaining the controller gains for a MMC-based BESS converter. In this sense, there is a gap in the methodology used to calculate the controller gains. Thus, this work aimed to tune the analytical expressions of a MMC-based BESS by considering the single-stage approach. The methodology is validated through detailed simulation models of 10.9 MVA/5.76 MWh connected to a 13.8 kV power system. Finally, to validate the dynamics of the controllers, the simulation results in the PLECS software for the charging and discharging processes are presented.

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