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In this paper, passive reinforcement learning (RL) solved by particle swarm optimization policy (PSO–P) is used to handle an adaptive neuro-fuzzy inference system (ANFIS) type-2 structure with unsupervised clustering for controlling the pitch angle of a real wind turbine (WT). The proposed control scheme is based on gain-scheduled reinforcement learning recurrent ANFIS type 2 (GS-RL-RANFIST2) pitch angle controller to maintain the rotor speed at its rated value while smoothing the output power and the performance of the pitch angle system. The practical application of the proposed controller is evaluated by using FAST tool for a real 600 kW WT equipped with a synchronous generator with a full-size power converter (CART3, located at the National Renewable Energy Laboratory, NREL), whose results are compared with those obtained by a gain corrected proportional integral (GC-PI) controller. The results demonstrate that the GS-RL-RANFIST2, which sets the nonlinear characteristics of the system automatically and waves more uncertainties in the windy conditions, allows to increase the energy capture and smooth the output power fluctuation, and therefore, to improve the control and response of the WT.

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.

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.

In a developing world where the demand for energy increases every day, the use of hybrid systems is a viable and important solution. The rivers present a significant potential for the electrical generation from the hydrokinetic use of the river currents, as well as the use of the solar radiation by means of the generation of photovoltaic solar energy for the electrical supply in rural areas. This paper presents a combination of both forms of electricity generation, photovoltaic generators and river turbine, to configure a hybrid system together with a subsystem of support based on hydrogen and batteries to guarantee the electrical supply of a set of isolated loads. The complete design of a hybrid system satisfies the energy requirements of a load. The methodology includes the optimal location of the turbine in a cross section of the river to maximize the performance of the hydroelectric generator, and the techno-economic study of all components of the hybrid system for an efficient use of renewable energy resources. The results show that the hybrid system provides the power demanded by the loads, hydroelectric and solar photovoltaic generation are optimized, and the battery storage subsystem loading status is kept avoiding deep discharges.

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).

Electric vehicles are the most promising sustainable transport technology for solving problems linked to the internal combustion engine vehicles. Wireless charging reduce the main problems associated with electric vehicles, driving range, charging time and size and cost of the battery. Inductive power transfer is the most promising technology for dynamic wireless charging of electric vehicles, which can be used to supply the motors and charge the battery while moving. This paper presents a comparative study of a dynamic wireless power transfer system for charging electric vehicles driving on three stretches of traffic road (motorway, highway and urban stretch) in Cadiz (Spain). The study analyses the electricity consumption demanded by the dynamic wireless power transfer system and the battery state-of-charge of the electric vehicles that travel the stretch to evaluate the increase of autonomy, the length of the stretch or speed of the vehicle for achieving a specific increase of state-of-charge. The results show a great dependence on stretch of road, with large fluctuations in the urban stretch and more stability in the highway and motorway. This study could help to design stretches of roads with dynamic wireless power transfer and to quantify the power and energy demanded by the system.

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.

In this paper, the idea of solving algebraic equations (AEs) through the fixed-point iterative method (FPIM) is generalized for the differential algebraic equations (DAEs) of power systems in order to analyze transient stability problems, which are particularly relevant when the number of DAEs in high-order models increase. In the loop form, reducing the number of variables by explicitly solving AEs is no longer required. It also allows for adding or removing the equations in order to easily analyze the effect of equations in the system's response. Furthermore, through the loop solving (LS) mechanism, the simplification assumption about power consumption in the PQ buses to fixed impedances is not necessary and the loads can be assumed with each arbitrary model. The LS mechanism is the first innovation provided hereby which facilitates the programming of high-order models and increases the accuracy of the system's response. On the other hand, because consistent and redundant variables are in place, solving DAEs in the loop form requires an iterative method with strong a convergence property that provides a convergent solution to the load flow (LF) AEs, and then a convergence solution for the DEs of the machines. This can be developed by extending the FPIM to the traditional Gauss-Siedel (GS) method, called modified GS (MGS), which is the second innovation herein. It can converge the solution of LF equations to the equilibrium point despite the numerical anomalies. Moreover, in order for the same performance as that of the MGS to be achieved, the Newton-Raphson (NR) method is first developed by a new formulation to full complex form, called complex based NR (CNR), which is the third innovation addressed hereby, and then applied with the same technique as that of the MGS to modified NR (MNR). The CNR increases the speed and simplicity of the LF computations and does not require decomposition of AE for both real and imaginary components; therefore, it simplifies the simulation training problems and reduces the computational time for large system dimensions. The proposed method is implemented in Simulink/MATLAB, tested and validated for the Western System Coordinated Council (WSCC) IEEE 9-bus system and compared with the results obtained by power system simulators, such as PowerWorld (PW) and SymPowerSystems (SPSs), and previous works published in the literature. Then, the experience gained from the first test is also applied to the IEEE 57-bus test system as a large scale system. The simulation results show the ability of the proposed method to represent the system's response for severe transient conditions, with better results than those achieved by previous methods. The new results are obtained from the effect of the network's transient on mechanical response of some synchronous machines. Also, the importance of removing damping coils in the system's transient response and the transition of response divergence during the severe fault with the method proposed hereby can be observed.

Solar energy has been consolidated as one of the main renewable energy sources capable of contributing to supply global energy demand. However, the solar resource has intermittent feature in electricity production, making it difficult to manage the electrical system. Hence, we propose the application of Deep Learning (DL), one of the emerging themes in the field of Artificial Intelligence (AI), as a solar predictor. To attest its capacity, the technique is compared with other consolidated solar forecasting strategies such as Multilayer Perceptron, Radial Base Function and Support Vector Regression. Additionally, integration of AI methods in a new adaptive topology based on the Portfolio Theory (PT) is proposed hereby to improve solar forecasts. PT takes advantage of diversified forecast assets: when one of the assets shows prediction errors, these are offset by another asset. After testing with data from Spain and Brazil, results show that the Mean Absolute Percentage Error (MAPE) for predictions using DL is 6.89% and for the proposed integration (called PrevPT) is 5.36% concerning data from Spain. For the data from Brazil, MAPE for predictions using DL is 6.08% and 4.52% for PrevPT. In both cases, DL and PrevPT results are better than the other techniques being used.

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.

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.

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 a novel energy dispatching based on Model Predictive Control (MPC) for off-grid photovoltaic (PV)/wind turbine/hydrogen/battery hybrid systems. The renewable energy sources supply energy to the hybrid system and the battery and hydrogen system are used as energy storage devices. The denominated “hydrogen system” is composed of fuel cell, electrolyzer and hydrogen storage tank. The MPC generates the reference powers of the fuel cell and electrolyzer to satisfy different objectives: to track the load power demand and to keep the charge levels of the energy storage devices between their target margins. The modeling of the hybrid system was developed in MATLAB-Simulink, taking into account datasheets of commercially available components. To show the proper operation of the proposed energy dispatching, a simpler strategy based on state control was presented in order to compare and validate the results for long-term simulations of 25 years (expected lifetime of the system) with a sample time of one hour.

This paper presents a comparative study of four sizing methods for a stand-alone hybrid generation system integrating renewable energies (photovoltaic panels and wind turbine) and backup and storage system based on battery and hydrogen (fuel cell, electrolyzer and hydrogen storage tank). Two of them perform a technical sizing. In one case, the sizing is based on basic equations, and in the other case, an optimal technical sizing is achieved by using Simulink Design Optimization. The other two methods perform an optimal techno-economical sizing by using the hybrid system optimization software HOMER and HOGA, respectively. These methods have been applied to design a stand-alone hybrid system which supplies the load energy demand during a year. A MATLAB-Simulink model of the hybrid system has been used to simulate the performance of hybrid system designed by each method for the stand-alone application under study in this work. The results are reported and discussed in the paper.

This paper presents two novel hourly energy supervisory controls (ESC) for improving long-term operation of off-grid hybrid systems (HS) integrating renewable energy sources (wind turbine and photovoltaic solar panels), hydrogen system (fuel cell, hydrogen tank and electrolyzer) and battery. The first ESC tries to improve the power supplied by the HS and the power stored in the battery and/or in the hydrogen tank, whereas the second one tries to minimize the number of needed elements (batteries, fuel cells and electrolyzers) throughout the expected life of the HS (25 years). Moreover, in both ESC, the battery state-of-charge (SOC) and the hydrogen tank level are controlled and maintained between optimum operating margins. Finally, a comparative study between the controls is carried out by models of the commercially available components used in the HS under study in this work. These ESC are also compared with a third ESC, already published by the authors, and based on reducing the utilization costs of the energy storage devices. The comparative study proves the right performance of the ESC and their differences.

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.

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.

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.

Fuel cell (FC) is an efficient energy conversion technology that is growing rapidly and will have a significant role to play in a number of energy end-use sectors, from small-scale applications to large-scale power plants. In this paper, two new methods for voltage harmonic compensation of a stand-alone single phase inverted-based FC are presented and evaluated. The stand-alone power system under study consists of: 1) Proton-Exchange-Membrane (PEM) FC with unidirectional DC/DC converter, which converts the DC voltage delivered by the FC to the DC bus voltage; 2) single-phase pulse width modulated (PWM) inverter; 3) transformer; 4) passive filter; and 5) linear and non-linear loads. The dynamic model of this system and the non-sinusoidal output-based controls applied to the PWM inverter for voltage regulation and harmonic compensation are detailed in this paper, and evaluated by simulation under different linear and non-linear loads. Simulation results show the effectiveness of the two purposed methods for voltage harmonic compensation to acceptable levels defined in grid codes.

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.

This paper presents a novel hourly energy management system (EMS) for a stand-alone hybrid renewable energy system (HRES). The HRES is composed of a wind turbine (WT) and photovoltaic (PV) solar panels as primary energy sources, and two energy storage systems (ESS), which are a hydrogen subsystem and a battery. The WT and PV panels are made to work at maximum power point, whereas the battery and the hydrogen subsystem, which is composed of fuel cell (FC), electrolyzer and hydrogen storage tank, act as support and storage system. The EMS uses a fuzzy logic control to satisfy the energy demanded by the load and maintain the state-of-charge (SOC) of the battery and the hydrogen tank level between certain target margins, while trying to optimize the utilization cost and lifetime of the ESS. Commercial available components and an expected life of the HRES of 25 years were considered in this study. Simulation results show that the proposed control meets the objectives established for the EMS of the HRES, and achieves a total cost saving of 13% over other simpler EMS based on control states presented in this paper.

This paper focuses on describing a control strategy for a real tramway, in Zaragoza (Spain), whose current propulsion system is to be replaced by a hybrid system based on fuel cell (FC) as primary energy source and batteries and ultracapacitors (UCs) as secondary energy sources. Due to its slow dynamic response, the FC needs other energy sources support during the starts and accelerations, which are used as energy storage devices in order to harness the regenerative energy generated during brakings and decelerations. The proposed energy management system is based on an operation mode control, which generates the FC reference power, and cascade controls, which define the battery and UC reference powers in order to achieve a proper control of the DC bus voltage and states of charge (SOC) of battery and UC. The simulations, performed by using the real drive cycle of the tramway, show that the proposed hybrid system and energy management system are suitable for its application in this tramway.

Problems relating to oil supply, pollution, and green house effects justify the need for developing of new technologies for transportation as a replacement for the actual technology based on internal combustion engines (ICE). Fuel cells (FCs) are seen as the best future replacement for ICE in transportation applications because they operate more efficiently and with lower emissions. This paper presents a comparative study performed in order to select the most suitable control strategy for high-power electric vehicles powered by FC, battery and supercapacitor (SC), in which each energy source uses a DC/DC converter to control the source power and adapt the output voltage to the common DC bus voltage, from where the vehicle loads are supplied. Five different controls are described for this kind of hybrid vehicles: a basic control based on three operation modes of the hybrid vehicle depending on the state of charge (SOC) of the battery (operation mode control); a control strategy based on control loops connected in cascade, whose aim is to control the battery and SC SOC (cascade control); a control based on the technique of equivalent fuel consumption, called equivalent consumption minimization strategy (ECMS); and two based on control techniques very used nowadays, the first one of them is a fuzzy logic control and the second one is a predictive control. These control strategies are tested and compared by applying them to a real urban street railway. The simulation results reflect the optimal performance of the presented control strategies and allow selecting the best option for being used in this type of high-power electric vehicles.

This paper presents a sizing method and different control strategies for the suitable energy management of a stand-alone hybrid system based on photovoltaic (PV) solar panels, hydrogen subsystem and battery. The battery and hydrogen subsystem, which is composed of fuel cell (FC), electrolyzer and hydrogen storage tank, act as energy storage and support system. In order to efficiently utilize the energy sources integrated in the hybrid system, an appropriate sizing is necessary. In this paper, a new sizing method based on Simulink Design Optimization (SDO) of MATLAB was used to perform a technical optimization of the hybrid system components. An analysis cost has been also performed, in that the configuration under study has been compared with those integrating only batteries and only hydrogen system. The dynamic model of the designed hybrid system is detailed in this paper. The models, implemented in MATLAB-Simulink environment, have been designed from commercially available components. Three control strategies based on operating modes and combining technical-economic aspects are considered for the energy management of the hybrid system. They have been designed, primarily, to satisfy the load power demand and, secondarily, to maintain a certain level at the hydrogen tank (hydrogen energy reserve), and at the state of charge (SOC) of the battery bank to extend its life, taking into account also technical-economic analysis. Dynamic simulations were performed to evaluate the configuration, sizing and control strategies for the energy management of the hybrid system under study in this work. Simulation results show that the proposed hybrid system with the presented controls is able to provide the energy demanded by the loads, while maintaining a certain energy reserve in the storage sources.

We define a new association between graphs and orthonormal bases of even-dimensional Euclidean vector spaces endowed with an special isomorphism motivated by the recently introduced theory of submanifolds associated with graphs. We provide several interesting examples and we analyze the shape of such graphs by proving some general results.

This paper evaluates the option of using a new powertrain based on fuel cell (FC), battery and supercapacitor (SC) for the Urbos 3 tramway in Zaragoza, Spain. In the proposed powertrain configuration, a hydrogen Proton-Exchange-Membrane (PEM) FC acts as main energy source, and a Li-ion battery and a SC as energy support and storage systems. The battery supports the FC during the starting and accelerations, and furthermore, it absorbs the power generated during the regenerative braking. Otherwise, the SC, which presents the fastest dynamic response, acts mainly during power peaks, which are beyond the operating range of the FC and battery. The FC, battery and SC use a DC/DC converter to connect each energy source to the DC bus and to control the energy exchange. This configuration would allow the tramway to operate in an autonomous way without grid connection. The components of the hybrid tramway, selected from commercially available devices have been modeled in MATLAB-Simulink. The energy management system used for controlling the components of the new hybrid system allows optimizing the fuel consumption (hydrogen) by applying an equivalent consumption minimization strategy. This control system is evaluated by simulations for the real driving cycle of the tramway. The results show that the proposed control system is valid for its application to this hybrid system.

This paper deals with the modeling and control of a hybrid system integrating a doubly-fed induction generator (DFIG) wind turbine and batteries as energy storage system (ESS). The modeling of the mechanical and electrical main components of a 1.5 MW wind turbine is described. Specific focus is to be taken on the power converter of the DFIG, since it allows the interconnection of the ESS to the generator and a proper energy management. A lead-acid battery is used as energy storage device, which is connected through a bidirectional DC/DC converter to the DC bus of the DFIG power converter. A new supervisory control system, responsible for the coordinate operation of power sources (DFIG wind turbine and ESS), is described and evaluated by simulation under wind speed fluctuations and grid demand changes. It is based on using the wind turbine as primary power source and the ESS as auxiliary power source, providing or storing the power mismatching between the actual wind power and grid demand, whenever the battery state-of-charge (SOC) remains within the recommended limits. This configuration increases the generation capability and smooths the output power fluctuations caused by the wind speed variability, and therefore, improves the grid integration of wind turbines.

This paper focuses on describing a control strategy for a real surface tramway powered by a hybrid system based on fuel cell and battery. This tramway, called Metro Centro , serves the centre of Seville, a city in Spain. Currently, it operates as catenary-powered tramway. The configuration and modeling of all principal components of the hybrid system are briefly described. The models, implemented in MATLAB-Simulink environment, have been designed from commercially available components. The implemented control is based on an equivalent consumption minimization strategy. It allows a suitable energy management of the hybrid system, minimizing the hydrogen consumption.

This paper presents a comparative study of Proton Exchange Membrane (PEM) Fuel Cell (FC) models for integration in hybrid propulsion systems, based on a commercial FC from Nuvera, which is especially manufactured for this application. An existing model is used as a reference in order to build dynamical mathematical models which describe its dynamical behavior in the time domain. These mathematical models are obtained by applying system identification techniques to the reference model. The proposed FC models have been tested through simulations for the real drive cycle of the existing Metro Centro tramway in Seville.

This paper presents a hybrid electric power system for a real surface tramway. The hybrid system consists of two electrical energy sources integrating a single dc/dc converter to provide the power demanded by the tramway loads (four electric traction motors and auxiliary services): (1) a Polymer Electrolyte Membrane (PEM) fuel cell (FC) as the primary and (2) a rechargeable Ni–MH battery as electrical energy storage to supplement the FC over the driving cycle. According to the requirements of the real driving cycle of the tramway, it was considered a 200 kW PEM FC system with two FCs connected in parallel and a 34 Ah Ni–MH battery. The PEM FC and Ni–MH battery models were designed from commercially available components. The power conditioning system provides the appropriate power for the tramway. It is composed of: (1) a unique dc/dc boot converter which adapts the FC output voltage to the 750 V traction standard dc bus; (2) three phase inverters to drive properly each electric motors; and (3) a braking chopper to dissipate excess of regenerative braking energy. Suitable state machine control architecture is presented for the hybrid system, its objective being to provide demanded power by the driving cycle, optimizing the energy generated. Following this objective, a new state machine control strategy based on eight states decides the operating point of each component of the system and a cascade control structure allows achieving the operating points determined by the strategy. Simulation results of the real driving cycle of the tramway check the adequacy of the hybrid electric power system.

This paper presents a model for a fuel cell (FC)-battery powered hybrid system for the Metro-Centro tramway (400kW) from Seville, Spain. Modeling of each component, implemented in MATLAB/SIMULINK environment, is briefly presented. Polymer Electrolyte Membrane (PEM) FC and Ni-MH battery models are designed from commercial available components. Two control strategies are presented and tested for the energy management of the hybrid system: cascade and fuzzy logic. The objective of both strategies is to manage the primary (PEM FC) and secondary (battery) energy source to supply the power requirements of the tramway forcing the FC to work around its maximum efficiency point and maintaining the battery state of charge (SOC) in a desired level.

This paper describes a comparative study of two control schemes for the energy management system of a hybrid tramway powered by a Polymer Electrolyte Membrane (PEM) Fuel Cell (FC) and an Ni-MH battery. The hybrid system was designed for a real surface tramway of 400 kW. It is composed of a PEM FC system with a unidirectional dc/dc boost converter (FC converter) and a rechargeable Ni-MH battery with a bidirectional dc/dc converter (battery converter), both of which are coupled to a traction dc bus. The PEM FC and Ni-MH battery models were designed from commercially available components. The function of the two control architectures was to effectively distribute the power of the electrical sources. One of these control architectures was a state machine control strategy, based on eight states. The other was a cascade control strategy which was used to validate the results obtained. The simulation results for the real driving cycle of the tramway reflected the optimal performance of the control systems compared in this study.

This paper describes the modelling and control system of a direct-drive PMSG wind turbine for effective active and reactive power generation control and voltage control at the grid connection point. This study focuses on the maximum power capability of the wind turbine, which is limited by its generator and power converter. The ability of this model and control strategy are assessed by means of simulations and discussed at length. The results of our study show that a PMSG wind turbine is able to actively participate in grid operation because it can independently control active and reactive power production (operating as a PQ node) or the active power and voltage at the connection node (operating as a PV node).

As a result of the increasing wind farms penetration on power systems, the wind farms begin to influence power system, and therefore the modeling of wind farms has become an interesting research topic. In this paper, new equivalent models of wind farms equipped with wind turbines based on squirrel-cage induction generators and doubly-fed induction generators are proposed to represent the collective behavior on large power systems simulations, instead of using a complete model of wind farms where all the wind turbines are modeled. The models proposed here are based on aggregating wind turbines into an equivalent wind turbine which receives an equivalent wind of the ones incident on the aggregated wind turbines. The equivalent wind turbine presents re-scaled power capacity and the same complete model as the individual wind turbines, which supposes the main feature of the present equivalent models. Two equivalent winds are evaluated in this work: (1) the average wind from the ones incident on the aggregated wind turbines with similar winds, and (2) an equivalent incoming wind derived from the power curve and the wind incident on each wind turbine. The effectiveness of the equivalent models to represent the collective response of the wind farm at the point of common coupling to grid is demonstrated by comparison with the wind farm response obtained from the detailed model during power system dynamic simulations, such as wind fluctuations and a grid disturbance. The present models can be used for grid integration studies of large power system with an important reduction of the model order and the computation time.

As a result of the increasing wind power penetration on power systems, the wind farms are today required to participate actively in grid operation by an appropriate generation control. This paper presents a comparative study on the performance of three control strategies for DFIG wind turbines. The study focuses on the regulation of the active and reactive power to a set point ordered by the wind farm control system. Two of them (control systems 1 and 2) are based on existing strategies, whereas the third control system (control system 3) presents a novel control strategy, which is actually a variation of the control system 2. The control strategies are evaluated through simulations of DFIG wind turbines, under normal operating conditions, integrated in a wind farm with centralized control system controlling the wind farm generation at the connection point and computing the power reference for each wind turbine according to a proportional distribution of the available power. The three control systems present similar performance when they operate with power optimization and power limitation strategies. However, the control system 3 with down power regulation presents a better response with respect to the reactive power production, achieving a higher available reactive power as compared with the other two. This is a very important aspect to maintain an appropriate voltage control at the wind farm bus.

As a result of increasing wind farms penetration in power systems, the wind farms begin to influence power system, and thus the modelling of wind farms has become an interesting research topic. Nowadays, doubly fed induction generator based on wind turbine is the most widely used technology for wind farms due to its main advantages such as high-energy efficiency and controllability, and improved power quality. When the impact of a wind farm on power systems is studied, the behavior of the wind farm at the point common coupling to grid can be represented by an equivalent model derived from the aggregation of wind turbines into an equivalent wind turbine, instead of the complete model including the modelling of all the wind turbines. In this paper, a new equivalent model of wind farms with doubly fed induction generator wind turbines is proposed to represent the collective response of the wind farm by one single equivalent wind turbine, even although the aggregated wind turbines operate receiving different incoming winds. The effectiveness of the equivalent model to represent the collective response of the wind farm is demonstrated by comparing the simulation results of equivalent and complete models both during normal operation and grid disturbances.

This paper is about Astrodata, a Supervisory, Control and Data Adquisition system (SCADA). It was designed and implemented employing two important concepts: the effective cost and the sustainable automation. The SCADA is working at the Radio Astronomical Station of Havana. This solution has demonstrated to be more economical than the former solution implemented.

The increasing wind power penetration on power systems requires the development of adequate wind farms models for representing the dynamic behaviour of wind farms on power systems. The behaviour of a wind farm can be represented by a detailed model including the modelling of all wind turbines and the wind farm electrical network. But this detailed model presents a high order model if a wind farm with high number of wind turbines is modelled and therefore the simulation time is long. The development of equivalent wind farm models enables the model order and the computation time to be reduced when the impact of wind farms on power systems is studied. In this paper, equivalent models of wind farms with fixed speed wind turbines are proposed by aggregating wind turbines into an equivalent wind turbine that operates on an equivalent wind farm electrical network. Two equivalent wind turbines have been developed: one for aggregated wind turbines with similar winds, and another for aggregated wind turbines under any incoming wind, even with different incoming winds. The proposed equivalent models provide high accuracy for representing the dynamic response of wind farm on power system simulations with an important reduction of model order and simulation time compare to that of the complete wind farm modelled by the detailed model.

A new class of Lie algebras of finite dimension, those which are associated with a certain combinatorial configuration made up by triangles of weighted and non-directed edges, is introduced and a characterization theorem for them is proved. Moreover, some subclasses of such Lie algebras are classified.

This paper is about Low Cost Automation. In it, a basic background about Havana Radioastronomical Station is described. It is showed a Real Time Supervisory and Control System named Astrodata. The System employs Virtual Instruments and Distributed I/O. Transfer information from sensors to computer it is made by communication network. Astrodata creates a database for off-line data processing. Data's primary processing is made by system on-line.