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Summary: Hybrid energy storage systems (HESSs) help mitigating the fluctuations and variable availability of certain renewable sources, such as wind power, as they can provide support in different time scales. Therefore, regulating their state‐of‐charge (SOC) becomes crucial to ensure that the hybrid system complies with generation commitments agreed in time‐ahead markets despite subsequent unexpected wind speed variations. So far, research has been mainly targeted at avoiding extreme SOC situations in the storage devices, whereas the regulation of this parameter to specific values has often been disregarded. A novel approach is proposed in this work, where model predictive control (MPC) is used to regulate the SOC of a HESS under variable wind and grid demand scenarios. The MPC‐based supervisory controller developed for the hybrid system has been implemented and simulated under different situations. This controller monitors the future variation of the SOC with the aim of having the HESS available to develop its assigned functions successfully. The results show that a proper regulation of the SOC in the HESS increases the capacity to manage the active power supplied to the grid by the hybrid system based on wind power, as well as the level of compliance with generation commitments established time ahead. [ABSTRACT FROM AUTHOR]

• Study of PV power plant with quasi-Z-source cascaded H-bridge multilevel inverter under failure. • Control system to provide a suitable DC voltage at the input of the VSI and ensure the grid power delivery. • Control tested from simulation results under different operating conditions and HIL experimental results. • Correct response of the developed control strategy with failure in qZSI module. To ensure the reliability of microgrids (MGs), this paper presents a multi-fault tolerant control for a three-phase energy storage quasi-impedance multilevel-cascaded H-bridge inverter (ES-qZS-CHBMLI) with a photovoltaic (PV) power generation-based MG. In this paper, a battery energy storage system (BESS) is implemented to smooth out the PV generation fluctuations. In the event of a fault, most studies propose the injection of a fundamental zero sequence (FZS) to balance the system after a fault. However, the FZS based-method increases the modulation and it is limited by the converter operation range. The state-of-charge (SOC) unbalanced problem has traditionally been solved by balancing the BESSs as a single unit. This paper introduces an energy management system (EMS) based on the SOC proportional power distribution to balance the power injected into the grid. When one bridge faults, it is bypassed, and the remaining bridges in that phase change their operating conditions according to the references set by the EMS. Individual phase control allows multi-fault issues to be addressed. The simulation results of a three-phase grid-connected ES-qZS-CHBMLI PV-based MG implemented in MATLAB/Simulink validate the proposed multi-fault control and EMS. In addition, an experimental validation (based on OPAL RT4520 and dSPACE MicroLabBox units) confirm these results. [ABSTRACT FROM AUTHOR]

• Study of microgrid with energy-stored quasi-Z-source cascaded H-bridge multilevel inverter and PV system. • Development of energy management system based on model predictive control (MPC-EMS). • Results compared with proportional sharing algorithm based on SOC level (SOC-EMS). • Best results obtained from MPC-EMS. This paper presents a new energy management system (EMS) based on model predictive control (MPC) for a microgrid with solar photovoltaic (PV) power plants and a quasi-Z-source cascaded H-bridge multilevel inverter that integrates an energy storage system (ES-qZS-CHBMLI). The system comprises three modules, each with a PV power plant, quasi-impedance network, battery energy storage system (BESS), and voltage source inverter (VSI). Traditional EMS methods focus on distributing the power among the BESSs to balance their state of charge (SOC), operating in charging or discharging mode. The proposed MPC-EMS carries out a multi-objective control for an ES-qZS-CHBMLI topology, which allows an optimized BESS power distribution while meeting the system operator requirements. It prioritizes the charge of the BESS with the lowest SOC and the discharge of the BESS with the highest SOC. Thus, both modes can coexist simultaneously, while ensuring decoupled power control. The MPC-EMS proposed herein is compared with a proportional sharing algorithm based on SOC (SOC-EMS) that pursues the same objectives. The simulation results show an improvement in the control of the power delivered to the grid. The Integral Time Absolute Error, ITAE, achieved with the MPC-EMS for the active and reactive power is 20 % and 4 %, respectively, lower than that obtained with the SOC-EMS. A 1,3 % higher charge for the BESS with the lowest SOC is also registered. Furthermore, an experimental setup based on an OPAL RT-4510 unit and a dSPACE MicroLabBox prototyping unit is implemented to validate the simulation results. [ABSTRACT FROM AUTHOR]

• Study of MVDC microgrid with PV, hydrogen system and electric vehicles. • Configuration based on Z-source converters that reduces the number of power converters. • Development of optimal energy management system (EMS) using biogeography-based optimization. • EMS achieved a notable improvement in the equivalent hydrogen consumption/generation. Currently, the technology associated with charging stations for electric vehicles (EV) needs to be studied and improved to further encourage its implementation. This paper presents a new energy management system (EMS) based on a Biogeography-Based Optimization (BBO) algorithm for a hybrid EV charging station with a configuration that integrates Z-source converters (ZSC) into medium voltage direct current (MVDC) grids. The EMS uses the evolutionary BBO algorithm to optimize a fitness function defining the equivalent hydrogen consumption/generation. The charging station consists of a photovoltaic (PV) system, a local grid connection, two fast charging units and two energy storage systems (ESS), a battery energy storage (BES) and a complete hydrogen system with fuel cell (FC), electrolyzer (LZ) and hydrogen tank. Through the use of the BBO algorithm, the EMS manages the energy flow among the components to keep the power balance in the system, reducing the equivalent hydrogen consumption and optimizing the equivalent hydrogen generation. The EMS and the configuration of the charging station based on ZSCs are the main contributions of the paper. The behaviour of the EMS is demonstrated with three EV connected to the charging station under different conditions of sun irradiance. In addition, the proposed EMS is compared with a simpler EMS for the optimal management of ESS in hybrid configurations. The simulation results show that the proposed EMS achieves a notable improvement in the equivalent hydrogen consumption/generation with respect to the simpler EMS. Thanks to the proposed configuration, the output voltage of the components can be upgraded to MVDC, while reducing the number of power converters compared with other configurations without ZSC. [ABSTRACT FROM AUTHOR]