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Typically, permanent magnet synchronous generator (PMSG)-driven wind turbines (WTs) present a two-stage power converter topology based on a DC/DC boost converter and voltage source inverter. In this study, this configuration is substituted by a quasi-Z-source inverter (qZSI), which is an attractive solution for boosting and converting the voltage from DC to AC in a single stage. A 2 MW PMSG WT with qZSI was studied herein. A switched dynamic model (SDM) of the qZSI (including the modeling of all switches and firing pulses) is not recommended for steady-state stability studies, long-term simulations, or large electric power systems. For such studies, two averaged dynamic models are proposed in this work. Both models present the same control system as the SDM, except for the generation of firing pulses, which is not necessary in the averaged models. The two proposed models were evaluated and compared with the SDM in the large-scale WT under different operating conditions, such as wind speed fluctuations, variable power references, and grid disturbances (voltage sag and 3rd and 5th order harmonics injection), in order to demonstrate their adequacy to represent the system response with a high reduction in the simulation time and computational efforts.

This work presents a new configuration for a hybrid charging station of electric vehicles (EV) based on Z-source converters (ZSC) in a medium voltage direct current (MVDC) grid. A photovoltaic (PV) system, a battery (BAT), a hydrogen system with fuel cell (FC), electrolyzer (LZ) and hydrogen tank as energy storage system (ESS), a local grid connection and two units of fast charging for EV are the main components of this system. Thanks to the proposed configuration the output voltages of the components can be adapted to MVDC to control their output power and reduce the number of power converters compared with the common configuration without ZSC. In addition, a new supervisory control system (SCS) is designed to keep the power balance in the hybrid charging station and control the level of energy in the ESS. The behavior of the charging station and SCS are proven under variable sun irradiance and considering the connection of three EV to the charging station. The simulation results show that the proposed system (ZSC-based configuration and SCS) is perfectly valid for charging stations.

Renewable energy systems based on photovoltaic (PV) power plants are usually connected to the grid through a DC-DC boost converter and a voltage source inverter. In this paper, this topology is modified by replacing this conversion system consisting of two stages for one of single stage, employing a quasi-Z-source inverter (qZSI), which allows to achieve a medium voltage direct current (MVDC) at the output of the Z source. In addition, a battery is integrated directly into the qZSI, without any additional DC/DC converter, which is used to support the intermittence of the PV generation and improve the operability of the system. The PV power plant operates at maximum power point tracking (MPPT) and the active and reactive power delivered by the PV power plant through the qZSI are controlled by a Z-Space Vector Modulation (ZSVM) technique. An energy management system (EMS) based on a fuzzy logic controller is implemented for the supervisory control of the PV plant and battery. The EMS decides to charge or discharge the battery depending on the power generated by PV power plant, the battery state-of-charge (SoC), and the grid energy price. The main advantages of the proposed system are: (i) the use of a single stage conversion; (ii) the battery connection directly to the Z source, which allows not to use an additional DC/DC converter; (iii) the application of fuzzy logic control for the EMS, while maintaining the battery within secure SoC limits and with a smooth response. The results illustrate the proper behavior of the PV power plant under different operating conditions.

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.

This study presents a new energy management system (EMS) for the optimised operation of power sources of a hybrid charging station for electric vehicles and fuel cell vehicles. It is composed of a photovoltaic (PV) system, a battery and a hydrogen system as energy storage systems (ESSs), a grid connection, six fast charging units and a hydrogen supplier. The proposed EMS is designed to reduce the utilisation costs of the ESS and make them work, as much as possible, around their maximum efficiency points. The optimisation function depends on a cost prediction system that calculates the net present cost of the components from their previous performance and a fuzzy logic system designed for improving their efficiency. Finally, a particle swarm optimisation algorithm is used to solve the optimisation function and obtain the required power for each ESS. The proposed EMS is checked under Simulink environment for long-term simulations (25 years). By comparing the EMS with a simpler one that optimises only the costs, it is proved that the proposed EMS achieves better efficiency of the charging station (+7.35%) and a notable reduction in the loss of power supply probability (-57.32%) without compromising excessively its average utilisation cost (+1.81%).

Renewable energies are reaching the maturity of their technological development, but before they are ready to become the main or even the only power sources in the energy mix, they must become profitably manageable. Currently there are many research topics regarding the integration of renewable energies in power systems, such as the combination of two or more sources into hybrid systems, the addition of energy storage systems, etc. The present paper studies the economic feasibility of converting an existing pumped-storage hydro power plant into a hybrid hydro-wind power plant through the integration of a wind farm in its surroundings. For this purpose, the estimated economic benefits of the existing pumped-storage hydropower plant are compared with the potential benefits of the proposed hybrid hydro-wind configuration. Furthermore, two energy management systems are conceived in order to estimate the energy generated and consumed by the hybrid hydro-wind plant, as well as the income and expenses resulting from the energy purchase-sale. The results point out the economic feasibility of the project, as well as an increased participation of the hybrid plant in the power system.

This paper describes and evaluates a hybrid propulsion system based on diesel generator and supercapacitors (SCs) as energy storage system (ESS) for a rubber tyre gantry (RTG) container crane, which currently operates within the yard of the Algeciras port terminal (Spain) powered by diesel electric generator for supplying the electric drives and motors (hoist and trolley). The SCs, which are connected to the DC bus through a bidirectional DC/DC converter, are controlled by a control strategy based on the DC-bus voltage. The SCs reference current is limited depending on their state-of-charge (SOC). All main components and control strategy of the RTG crane are modelled and simulated in SimPowerSystems. The current and hybrid configuration are simulated and compared under the real working cycle of the RTG crane. The results show the technical viability, the validity of the proposed control strategy, the improvements in the energy efficiency and diesel fuel consumption, and the economic viability of the hybrid propulsion system for the RTG crane.

Grid connection of permanent magnet synchronous generator -based wind turbines can be performed through a three-stage power conversion system: 1) uncontrolled rectifier, 2) DC boost converter, and 3) voltage source inverter. In this paper, this topology is modified by replacing the two intermediate stages by a quasi-Z-source inverter (qZSI). Additionally, a battery is integrated with the qZSI without any additional DC/DC converter. This battery will allow reducing the intermittence of the generation and improving the operability of the wind turbine. The application and control of qZSI for large-scale wind turbine with energy storage systems is illustrated in this work. An energy management system is implemented for the proper operation of the wind turbine and the battery. The qZSI is controlled through a Z-Space Vector Modulation (ZSVM) technique to achieve maximum power point tracking in the wind turbine, reactive power control, and battery charge/discharge depending on the operating conditions and the battery state-of-charge. The simulations show the proper behavior of the system under study.

This paper presents an energy management system (EMS) based on a novel approach using model predictive control (MPC) for the optimized operation of power sources in a hybrid charging station for electric vehicles (EVs). The hybrid charging station is composed of a photovoltaic (PV) system, a battery, a complete hydrogen system based on a fuel cell (FC), electrolyzer (EZ), and tank as an energy storage system (ESS), grid connection, and six fast charging units, all of which are connected to a common MVDC bus through Z-source converters (ZSC). The MPC-based EMS is designed to control the power flow among the energy sources of the hybrid charging station and reduce the utilization costs of the ESS and the dependency on the grid. The viability of the EMS was proved under a long-term simulation of 25 years in Simulink, using real data for the sun irradiance and a European load profile for EVs. Furthermore, this EMS is compared with a simpler alternative that is used as a benchmark, which pursues the same objectives, although using a states-based strategy. The results prove the suitability of the EMS, achieving a lower utilization cost (−25.3%), a notable reduction in grid use (−60% approximately) and an improvement in efficiency.

Typically, grid-connected wind turbines equipped with permanent magnet synchronous generator (PMSG) present a back-to-back power converter based on voltage-source converters. In this paper, this structure is modified using an uncontrolled rectifier for the AC/DC conversion in the generator, and a quasi-Z-source inverter (qZSI) at the grid side. The qZSI is an attractive solution to boost and convert DC voltage to AC in a single stage. The main objective of the paper is the application of a qZSI for large grid-connected wind energy systems. In this configuration, active and reactive powers can be controlled through a Space Vector Modulation technique adapted for Z-source converter. Simulations were performed using MATLAB/Simulink® with wind and load variations to confirm the proper functioning of the proposed controllers. The results showed satisfactory responses of the proposed 5 MW PMSG-driven grid-connected wind turbine.

The application of quasi-Z source inverters (qZSI) for renewable energy sources has been presented as an attractive solution. This kind of inverters perform power conversion in a single stage with buck/boost capability and improved reliability compared to the conventional voltage source inverter. This paper focuses on the application of qZSI to a large-scale grid-connected photovoltaic (PV) system. The active and reactive powers are controlled using a version of the space vector modulation technique adapted to qZSI that allows a high modulation index. Furthermore, the sizing of the impedance components and the filter are described considering commercial values. Simulations are performed under a voltage sag and load variation on the grid, in order to verify the right design and performance of system and control methods. The results confirm the effectiveness of the proposed model and the control techniques applied to the large-scale grid-connected qZSI-based PV power plant.

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.

As already happens with the electric vehicles (EVs) expansion, technology associated with their charge also must be improved. This paper presents a novel decentralized control method (DCM) for charging stations (CSs) based on a medium-voltage direct current (MVDC) bus. This kind of CSs is integrated in a microgrid with a photovoltaic system, a battery energy storage system (ESS), a local grid connection, and two units of fast charge. The main contribution of this paper resides in the cited DCM based on fuzzy logic that includes the state of charge (SOC) of the battery ESS as a control variable. This control contains two independent fuzzy logic systems (one for the battery ESS and other for the grid), whose function is to maintain the MVDC voltage and the battery ESS SOC within proper thresholds and to keep the power balance stable among the units of fast charge and the rest of the CS components. The new control method was tested in a considerable number of operating situations (two hundred cases studied) under different conditions of sun irradiance, initial SOC of battery ESS, and number of EVs connected to the CS with the objective of showing its correct performance in all the considered scenarios.

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., This work was partially supported by Spain's Ministerio de Ciencia, Innovaci ' on y Universidades (MCIU), Agencia Estatal de Investigaci ' on (AEI) and Fondo Europeo de Desarrollo Regional (FEDER) Uni ' on Europea (UE) (grant number RTI2018-095720-B-C32), by the Federal Center for Technological Education of Minas Gerais, Brazil (process number 23062-010087/2017-51) and by the National Council of Technological and Scientific Development (CNPq-Brazil).

Featured Application This work is useful for researchers interested in the study of energy management systems for hybrid electric vehicles. In addition, it is interesting for institutions related to the market of this type of vehicle. The hybridization of vehicles is a viable step toward overcoming the challenge of the reduction of emissions related to road transport all over the world. To take advantage of the emission reduction potential of hybrid electric vehicles (HEVs), the appropriate design of their energy management systems (EMSs) to control the power flow between the engine and the battery is essential. This work presents a systematic literature review (SLR) of the more recent works that developed EMSs for HEVs. The review is carried out subject to the following idea: although the development of novel EMSs that seek the optimum performance of HEVs is booming, in the real world, HEVs continue to rely on well-known rule-based (RB) strategies. The contribution of this work is to present a quantitative comparison of the works selected. Since several studies do not provide results of their models against commercial RB strategies, it is proposed, as another contribution, to complete their results using simulations. From these results, it is concluded that the improvement of the analyzed EMSs ranges roughly between 5% and 10% with regard to commercial RB EMSs; in comparison to the optimum, the analyzed EMSs are nearer to the optimum than commercial RB EMSs.

This paper presents an application of the multi-port bidirectional three-phase ac-dc converter as interface between a microgrid composed by several power sources and an electric vehicle charging station (EVCS). The main advantage of using this converter is that it can integrate multiple power sources and loads into a single power conversion stage and thus control the power flow between them reducing the number of power conversion stages and / or devices as well as weight and volume of the entire system and the control architecture does not require communication strucure as main current solutions in this field present. The microgrid of this study was composed of a photovoltaic system, a battery energy storage system, two 48 kW fast charging units for electricle vehicles, a connection to the local grid and the multi-port bidirectional converter with minor changes to be able in this type of application with a rated power at 100 kW. Simulation results obtained from a system model are presented and discussed in order to validate that under different power sources conditions the converter operates effectively confirming the feasibility of using this type of application in EVCS microgrid technology.

This paper describes a novel energy management system for the optimized operation of the energy sources of a grid-connected hybrid renewable energy system (wind turbine and photovoltaic) with battery and hydrogen system (fuel cell and electrolyzer). A multi-objective optimization problem based on the weight aggregation approach is formulated by combining three objective functions (operating costs, efficiency and lifetime of the devices) that can conflict with each. The multi-objective function to be optimized by the energy management system is obtained by solving the problem for all the possible cases. Then, the weights that provide the minimum value of the multi-objective function are selected. As the results demonstrate, the multi-objective function becomes a single-objective function that differs according to the net power (power to be generated by/stored in the energy storage devices) and has to be solved in the energy management system of the hybrid system. It simplifies considerably the multi-objective problem implemented in the energy management system, while taking into account the three control objectives that can conflict with each other, which is the main contribution of this paper. This optimal energy management system is solved using the Particle Swarm Optimization (PSO) method, tested by simulations of the hybrid power generation system throughout 25 years (the expected lifetime of the system), and compared with the results obtained by the energy management systems based on optimizing each single-objective function separately, and by that based on optimizing the multi-objective function combining the three single-objective functions equally weighted. The results demonstrate that this energy management system achieves reasonable operating costs, efficiency and degradation of the devices.

Although electric vehicles (EVs) are experiencing a considerable upsurge, the technology associated with them is still under development. This study focused on the control and operation of a medium-voltage direct-current (MVDC) microgrid with an innovative decentralized control system, which was used as a fast charging station (FCS) for EVs. The FCS was composed of a photovoltaic (PV) system, a Li-ion battery energy storage system (BESS), two 48 kW fast charging units for EVs, and a connection to the local grid. With this configuration and thanks to its decentralized control, the FCS was able to work as a stand-alone system most of the time though with occasional grid support. This paper presents a new decentralized energy management system (EMS) with two options to control the power sources of the FCS. The choice of the power source depends on the MVDC bus voltage, the state-of-charge (SOC) of the BESS, and the control option of the EMS. This control was tested by simulating the FCS, when connected to several EVs and under different sun irradiance conditions. Simulation results showed that the FCS operated smoothly and effectively, which confirms the feasibility of using this technology in EVs.

Control focused on optimizing the lifecycle costs of a stand-alone hybrid system.Combination of renewable sources, battery and hydrogen systems.The modeling includes the electric models of the components.The system assures reliable electricity support for stand-alone applications. This paper presents an Energy Management System (EMS) for hybrid systems (HS) composed by a combination of renewable sources with the support of different storage devices (battery and hydrogen system) that allow its operation without the necessity of grid connection (i.e. a stand-alone system).The importance of the proposed EMS lies in taking into account economic issues that affect to the decision of which device of the HS must operate in each moment. Linear programming was used to meet the objective of minimizing the net present value of the operation cost of the HS for its whole lifespan. The total operation costs depend largely on the reposition costs of its components. Instead of considering predefined reposition years for each component and calculate their net present cost from them (as is commonly considered in other works), in this work it was proposed to use lifetime degradation models - based on the well-known statement that the lifetime depends on the hours of operation and the power profiles that the components are subjected to- from which the repositions are made to check how they affect to the cost calculation and, consequently, to the EMS performance.The behavior of the proposed control is checked under a long term simulation, in MATLAB-Simulink environment, whose duration is the expected lifespan of the HS (25 years). A conventional state-machine EMS is used as a case study to validate and compare the results obtained. The results demonstrate that the proposed HS and EMS combination assures reliable electricity support for stand-alone applications subject to different techno-economic criteria (generation cost and sustenance of battery SOC and hydrogen levels), achieving to minimize the operation cost of the system and extend their lifespan.

This paper presents an overview of the state-of-the-art of research on control strategies or energy management systems for DC networks and microgrids. For this purpose, a systematic literature review was performed, which classified the research on the topic and identified the interconnections between the different approaches described in the publications selected. The work reviewed was initially classified into two main categories, based on a set of distinguishing characteristics identified in the control strategies. These categories were the following: (1) active load sharing (which includes the subcategories of centralized control and of master–slave control; (2) droop control methods. A third ad hoc category was also established for the approaches that did not fit in the other two categories. Additionally, secondary topics affecting the control strategies were also analyzed, such as the configuration of DC networks, commonly used control methods and factors, communication system relevance, and finally, the simulation and experimental techniques used for validation. Moreover, this systematic review permitted the identification of current research gaps as well as the proposal of new research lines. The results obtained not only are useful as a guide for researchers, who are starting out in the field, but they also highlight interesting research questions that more experienced researchers can actively pursue.

Inverters are critical for injecting power from renewable energy sources into the grid or grid-integrated load. This paper provides a novel improved adaptive neuro-fuzzy control of inverter for grid-coupled photovoltaic systems. The improvement is performed by the integration of Jacobi wavelet in the existing neuro-fuzzy controller. Unlike existing neuro-fuzzy controller, the new proposed controller is capable to locate the exact local minima, which sequentially improves the performance of the proposed controller. Simulations are performed to show that the proposed controller is better than the existing state-of-the- art in terms of power transfer, inverter output efficiency, and load voltage frequency.

Forecasting the power production from renewable energy sources (RESs) has become fundamental in microgrid applications to optimize scheduling and dispatching of the available assets. In this article, a methodology to provide the 24 h ahead Photovoltaic (PV) power forecast based on a Physical Hybrid Artificial Neural Network (PHANN) for microgrids is presented. The goal of this paper is to provide a robust methodology to forecast 24 h in advance the PV power production in a microgrid, addressing the specific criticalities of this environment. The proposed approach has to validate measured data properly, through an effective algorithm and further refine the power forecast when newer data are available. The procedure is fully implemented in a facility of the Multi-Good Microgrid Laboratory (MG L a b 2 ) of the Politecnico di Milano, Milan, Italy, where new Energy Management Systems (EMSs) are studied. Reported results validate the proposed approach as a robust and accurate procedure for microgrid applications.

Due to its high-efficiency characteristics, the three-level boost DC-DC converter is widely used as a PV fed converter to connect PV panels to the DC bus. In our previous work [13], a decentralized energy management system for EV fast charging station was proposed where a conventional two-level boost DC-DC converter was used as a PV fed converter. In this paper, this converter is replaced by a three-level one. MPPT, output voltage and capacitors voltage balance are carried out, which facilitate the converter implementation on the charging station.

The use of distributed charging stations based on renewable energy sources for electric vehicles has increased in recent years. Combining photovoltaic solar energy and batteries as energy storage system, directly tied into a medium voltage direct current bus, and with the grid support, results to be an interesting option for improving the operation and efficiency of electric vehicle charging stations. In this paper, an electric vehicle charging station supplied by photovoltaic solar panels, batteries and with grid connection is analysed and evaluated. A decentralized energy management system is developed for regulating the energy flow among the photovoltaic system, the battery and the grid in order to achieve the efficient charging of electric vehicles. The medium voltage direct current bus voltage is the key parameter for controlling the system. The battery is controlled by a model predictive controller in order to keep the bus voltage at its reference value. Depending on the state-of-charge of the battery and the bus voltage, the photovoltaic system can work at maximum power point tracking mode or at bus voltage sustaining mode, or even the grid support can be needed. The results demonstrate the proper operation and energy management of the electric vehicle charging station under study.

This paper is focused on the study of particle swarm optimization (PSO)-based PI controllers for the power control of a grid-connected inverter supplied from a hybrid renewable energy system. It is composed of two renewable energy sources (wind turbine and photovoltaic – PV – solar panels) and two energy storage systems (battery and hydrogen system, integrated by fuel cell and electrolyzer). Three PSO-based PI controllers are implemented: (1) conventional PI controller with offline tuning by PSO algorithm based on the integral time absolute error (ITAE) index; (2) PI controllers with online self-tuning by PSO algorithm based on the error; and (3) PI controllers with online self-tuning by PSO algorithm based on the ITAE index. To evaluate and compare the three controllers, the hybrid renewable energy system and the grid-connected inverter are simulated under changes in the active and reactive power values, as well as under a grid voltage sag. The results show that the online PSO-based PI controllers that optimize the ITAE index achieves the best response.

This paper presents and evaluates three energy management systems (EMSs) based on Particle Swarm Optimization (PSO) for long-term operation optimization of a grid-connected hybrid system. It is composed of wind turbine (WT) and photovoltaic (PV) panels as primary energy sources, and hydrogen system (fuel cell –FC–, electrolyzer and hydrogen storage tank) and battery as energy storage system (ESS). The EMSs are responsible for making the hybrid system produce the demanded power, deciding on the energy dispatch among the ESS devices. The first PSO-based EMS tries to minimize the ESS utilization costs, the second one to maximize the ESS efficiency, and the third one to optimize the lifetime of the ESS devices. Long-term simulations of 25 years (expected lifetime of the hybrid system) are shown in order to demonstrate the right performance of the three EMSs and their differences. The simulations show that: 1) each EMS outperforms the others in the designed target; and 2) the third EMS is considered the best EMS, because it needs the least ESS devices, and presents the lowest total acquisition cost of hybrid system, whereas the rest of parameters are similar to the best values obtained by the other EMSs.

This paper presents a “full green” version of a rubber tyre gantry (RTG) crane with a fuel cell (FC) unit and supercapacitors (SCs) as energy storage system (ESS), instead of using the conventional RTG powered by a diesel engine. The SCs provide the required high current peaks and power demands when accelerating the load in the hoisting-up movement. Once the power demand reaches a steady level (hoist up constant speed), the FC provides the energy needed for the rest of the movements. The SCs are also charged when the hoist down movement is taking place. In this case, the regenerative energy can be stored in the SCs instead of being burnt in the braking resistors as in the conventional RTG crane. The new hybrid powertrain based on FC and SCs is designed and evaluated from the real driving cycle of the RTG crane. Simulation results, which include a comparative study with the current configuration of the RTG crane (powered only by diesel engine), demonstrate the technical viability of the RTG crane powered by FC and SCs. This hybrid powertrain is more expensive than the diesel powertrain, but more energy-efficient, and a better solution from the environmental point of view.

Currently, electric vehicles (EV) are going through an important emergence, nevertheless, the technology associated to them is still under development. This paper presents a fast charging station (FCS) for EVs supplied by renewable energy with a novel decentralized control of the system. The fast CS is composed of a photovoltaic (PV) system, an energy storage system (ESS), and a connection with the local grid. Thanks to this configuration, the FCS is able to work as a stand-alone system most of the time, with occasional grid support. The proposed control is based on the voltage control of the common medium voltage DC (MVDC) bus, to which all the energy sources are connected. Thus, depending on its voltage, the PV system, the ESS or the grid are used to supply the energy demanded by the EVs. To show the viability of this control, the charging of two EVs is simulated under different operating conditions. Simulation results show the proper operation of the FCS.