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The increasing penetration of renewable energy sources in power grids has resulted in the need for a comprehensive evaluation of their impact on the dynamic behavior of the power system, including its inertia. This study aimed to evaluate the inertia of the current Jordanian power system at different penetration levels of renewable energy sources using DIgSILENT PowerFactory simulation software. In this study, the value of the constant inertia was calculated to be 8.755 s. The results were analyzed to determine the effect of renewable energy penetration on the inertia of the power system. The findings provide valuable information for the development of control strategies for integrating renewable energy sources into the Jordanian power system, ensuring stability and reliability in the power system operation. This study contributes to the understanding of the impact of renewable energy sources on power system inertia and supports the development of renewable energy integration strategies. [ABSTRACT FROM AUTHOR]

• Study of a grid-connected PV power plant through an energy-stored quasi-impedance source inverter. • Development of an online biogeography-based optimization (BBO) algorithm for the battery current control. • Results compared with online PSO-based PI controller and offline tuned PI controller. • Best results obtained from BBO-based PI controller. This study presents an optimal online control that implements a biogeography-based optimization (BBO) algorithm on a battery energy system (BES) integrated into an energy-stored quasi-impedance source inverter (qZSI) that connects a photovoltaic (PV) power plant to the grid. The BBO algorithm was used to tune the PI regulator in the BES current control loop by minimizing the integral time absolute error (ITAE). Two different options for the BBO are compared in this application:1) a PI controller with online self-tuning based on BBO, and 2) a PI controller with offline tuning using BBO. Moreover, the BBO-based PI controllers were compared with a third controller tuned online using the particle swarm optimization (PSO) algorithm. To evaluate and compare the controllers, a PV power plant with a battery energy-stored qZSI was simulated under different operating conditions, such as step changes in the BES current reference, different sun irradiance, and a grid voltage sag. The results demonstrate better control of the BES current with the online tuning techniques (BBO and PSO) than with the offline tuning procedure, and similar results between the two online tuning algorithms. Nevertheless, throughout the simulation, the time of use of the BBO algorithm was almost 2.5 times smaller than the PSO algorithm. Therefore, the online BBO-based PI controller is considered the most suitable option. [ABSTRACT FROM AUTHOR]

The continuous progress on the expansion of renewable energies leads to the development of hybrid power systems, where several power sources contribute to provide a clean and reliable alternative to traditional fossil fuels. The hydrogen technology is viewed with particular interest in this regard. Hydrogen is an outstanding energy carrier that can be exploited for various applications, including electricity generation. Hence, production of hydrogen from renewable sources has received the attention of many researchers lately. With this purpose, this paper deals with the coupled operation of electrolyzer (EZ) and wind turbine. Four different EZ models are presented and evaluated in this work. These models are aggregated to a variable speed wind turbine model using MATLAB/Simulink. The four configurations are evaluated, and their responses compared, under variable wind speed and grid demand. [ABSTRACT FROM AUTHOR]

Abstract: Energy storage systems (ESSs) appear as a viable solution to some of the stability and intermittency problems of wind power generation. As a consequence, it is crucial to develop adequate control strategies that allow the coordinate operation of both energy sources. Moreover, in order to minimize the impact of large wind farms on the power system, many countries have set strict grid codes that wind power generators must accomplish. Hence, it is also necessary to pay due attention to the fault ride through capabilities of these hybrid systems. In this paper two different hybrid configurations are modeled in MATLAB/Simulink, consisting on a doubly fed induction generator driven wind turbine and electrochemical batteries as ESS. They are simulated and compared under various operating conditions (i.e. real fluctuating wind speed input with variable active and reactive power grid demand, voltage sags, three-phase and single-phase fault to ground, and overvoltage). A conventional wind turbine without ESS is also considered as a base-case in order to highlight the main benefits of the hybrid schemes. The results show that by implementing one of the presented control strategies, it is possible to enhance the response to faults of the hybrid systems, achieving higher active power injection and helping the recovery to steady-state, thus improving the grid connection capabilities of hybrid wind farms. [Copyright &y& Elsevier]

Abstract: Integrating energy storage systems (ESS) with wind turbines results to be an interesting option for improving the grid integration capability of wind energy. This paper presents and evaluates a wind hybrid system consisting of a 1.5 MW doubly-fed induction generator (DFIG) wind turbine and double battery-ultracapacitor ESS. Commercially available components are used in this wind hybrid system. A novel supervisory control system (SCS) is designed and implemented, which is responsible for setting the active and reactive power references for each component of the hybrid system. A fuzzy logic controller, taking into account the grid demand, power generation prediction, actual DFIG power generation and state-of-charge (SOC) of the ESSs, sets the active power references. The reactive power references are proportionally delivered to each element regarding their current limitations in the SCS. The appropriate control of the power converters allows each power source to achieve the operation defined by the SCS. The wind hybrid system and SCS are assessed by simulation under wind fluctuations, grid demand changes, and grid disturbances. Results show an improved performance in the overall response of the system with the implementation of the SCS. [Copyright &y& Elsevier]

• 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]

The use of a battery energy-stored quasi-Z-source inverter (BES-qZSI) for large-scale PV power plants exhibits promising features due to the combination of qZSI and battery as energy storage system, such as single-stage power conversion (without additional DC/DC boost converter), improvements in the output waveform quality (due to the elimination of switching dead time), and continuous and smooth delivery of energy to the grid (through the battery energy storage system). This paper presents a new simplified model of a BES-qZSI to represent the converter dynamics with sufficient accuracy while using a less complex model than the detailed model (including the modelling of all switches and switching pulses). It is based on averaged values of the variables, voltage/current sources, and the same control circuit than the detailed model, except for the switching pulses generation. The simplified model enables faster time-domain simulation and is useful for control design and dynamic analysis purposes. Additionally, an energy management system has been developed to govern the power supply to grid under two possible scenarios: 1) System operator command following; or 2) economic dispatch of the stored energy. The results obtained from simulations and experimental hardware-in-the-loop (HIL) setup for different operating conditions of the grid-connected large-scale PV power plant with battery energy storage under study demonstrate the validity of the proposed simplified model to represent the dynamics of the converter and PV power plant for steady-state stability studies, long-term simulations, or large electric power systems. • Study of battery energy-stored quasi-Z-source inverter (BES-qZSI) based PV power plant. • Development of new simplified model of BES-qZSI. • Averaged model based on controlled voltage/current sources. • Model is easy to implement and achieves important reduction in computational effort. • Suitable for long simulations, large power systems, control design and dynamic analysis. [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. At the present time, quasi-Z-source cascaded H-bridge multilevel inverters (qZS-CHBMLI) have gained attention in photovoltaic (PV) applications, due to their advantages over traditional multilevel inverters. They allow single-stage power conversion of a PV power plant by independently adjusting the DC voltage in each module; thus, each PV array operates at the maximum power. This advantage permits dispensing with a DC/DC boost converter and reduces the number of modules required. This paper develops a novel control strategy for a qZS-CHBMLI connected to a single-phase system that guarantees proper operation when a fault occurs in a quasi-impedance source inverter (qZSI). The control strategy is employed in a grid-connected qZS-CHBMLI with three modules, each one with a quasi-impedance network, a 4.8 kW PV array and a voltage source inverter (VSI), with H-bridge topology. The purpose of the control system is to deliver a suitable DC voltage at the input of the VSI and ensure the grid power requirements after a fault in a module. The proposed control system is evaluated through a 40 s simulation in MATLAB/Simulink® in two cases: A) analysis of the system behaviour when there is a variation in the operation limit equation; and B) evaluation of the control strategy under dissimilar operating conditions. In addition, an experimental setup based on an OPAL RT-4510 unit and a dSPACE MicroLabBox prototyping unit is employed to validate the results. The results confirmed the correct response of the applied strategy with the failure of a single module. [ABSTRACT FROM AUTHOR]

A novel optimal energy management system (EMS) using a nonlinear constrained multivariable function to optimize the operation of battery energy storages (BESs) used in a hybrid power plant with wind turbine (WT) and photovoltaic (PV) power plants is proposed in this work. The hybrid power plant uses a configuration based on a battery-stored impedance-based cascaded multilevel inverter to integrate renewable energy sources (PV power plants and WT) and BESs into the grid. The new optimal EMS seeks for satisfying the demanded power while dispatching power between BESs to optimize their efficiency. A grid-connected configuration is implemented to assess the efficiency of the suggested supervisory control under changes in renewable energy (changes in wind speed and irradiation), and in a varying active and reactive powers' request. The BES efficiency obtained from the suggested EMS is set side by side to the BES efficiency got from a conventional EMS and a model predictive control (MPC), both working based on the state-of-charge (SOC) of the BES and balancing power EMS. The results from MATLAB simulation and the experimental results with the real-time OPAL-RT simulator (OP4510, OPAL-RT) and dSPACE MicroLabBox show the effectiveness of the suggested approach and the improvement in long-term BES efficiency. • Hybrid power plant with wind turbine, PV and battery integrated into multilevel configuration. • Design of optimal energy management system to optimize the battery efficiency. • Control tested from simulation results under different operating conditions and HIL experimental results. • Improved response when compared to other energy management systems. [ABSTRACT FROM AUTHOR]

A considerable growth of large-scale offshore wind farms (OWF) is noticeable in Europe mainly due to advances in wind turbines and foundation structures, which have improved their economic conditions and contributed to the implementation of offshore plants. It is expected that the installed capacity will continue to increase, since the European Union aims at reaching about 100 GW of offshore wind capacity by 2030. OWF have many challenges in terms of cost reduction and technology. Due to these issues, it is important to have a comprehensive understanding of the current situation and the future trends of OWF. This paper analyses the current status and the trends of large-scale OWF with an installed capacity above 150 MW in Europe. The results show the trends on wind turbine size and capacity, turbine model, distance to shore, water depth, investment cost, type of foundation, transmission technology, and voltage array systems among others. This paper gathers the latest information about the topic, deducing future trends from the evaluation of OWF fully commissioned, authorized or under construction. • Analysis of large-scale offshore wind farms in operation or projected in Europe. • New offshore wind farms are being placed away from the coast into deeper waters. • Increasing power and voltage of wind turbines and internal collection systems. • Offshore wind energy costs are decreasing and becoming more competitive. • Direct current is the preferred transmission for long distances to the shore. [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]