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Recently, trans-S-manifolds have been defined as a wide class of metric f-manifolds which includes, for instance, f-Kenmotsu manifolds, S-manifolds and C-manifolds and generalize well-studied trans-Sasakian manifolds. The definition of trans-S-manifolds is formulated using the covariant derivative of the tensor f and although this formulation coincides with the characterization of trans-Sasakian manifolds in such a particular case, this latter type of manifolds were not initially defined in this way but using the Gray-Hervella classification of almost Hermitian manifolds. The aim of this paper is to study how (almost) trans-S-manifolds relate with the Gray-Hervella classification and to establish both similarities and differences with the trans-Sasakian case.

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.

T lymphocytes are key players in adaptive immune responses through the recognition of peptide antigens through the T Cell Receptor (TCR). After TCR engagement, a signaling cascade is activated, leading to T cell activation, proliferation, and differentiation into effector cells. Delicate control of activation signals coupled to the TCR is needed to avoid uncontrolled immune responses involving T cells. It has been previously shown that mice deficient in the expression of the adaptor NTAL (Non-T cell activation linker), a molecule structurally and evolutionarily related to the transmembrane adaptor LAT (Linker for the Activation of T cells), develop an autoimmune syndrome characterized by the presence of autoantibodies and enlarged spleens. In the present work we intended to deepen investigation into the negative regulatory functions of the NTAL adaptor in T cells and its potential relationship with autoimmune disorders. For this purpose, in this work we used Jurkat cells as a T cell model, and we lentivirally transfected them to express the NTAL adaptor in order to analyze the effect on intracellular signals associated with the TCR. In addition, we analyzed the expression of NTAL in primary CD4+ T cells from healthy donors and Rheumatoid Arthritis (RA) patients. Our results showed that NTAL expression in Jurkat cells decreased calcium fluxes and PLC-γ1 activation upon stimulation through the TCR complex. Moreover, we showed that NTAL was also expressed in activated human CD4+ T cells, and that the increase of its expression was reduced in CD4+ T cells from RA patients. Our results, together with previous reports, suggest a relevant role for the NTAL adaptor as a negative regulator of early intracellular TCR signaling, with a potential implication in RA.

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.

Solar energy is one of the main renewable energy sources capable of contributing to global energy demand. However, the solar resource is intermittent, making its integration into the electrical system a difficult task. Here, we present and compare two machine learning techniques, deep learning (DL) and support vector regression (SVR), to verify their behavior for solar forecasting. Our testing from Spain showed that the mean absolute percentage error for predictions using DL and SVR is 7.9% and 8.52%, respectively. The DL achieved the best results for solar energy forecast, but it is worth mentioning that the SVR also obtained satisfactory results.

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%).

Finding and tracking maximum power point are two important dynamics in the control of variable-speed wind turbines since they determine the efficiency of wind turbines. The conventional hill climbing possesses the problems of wrong directionality and low performance since it does not take the inertial effect into account. In this paper, a novel hill climbing method is proposed by considering the inertial effect to solve these problems. Besides, employing the exact model knowledge of the generator in the maximum power tracking control deteriorates the efficiency considerably; therefore, it is required to design a parameter independent and robust control system if possible. Thus, the third-order super-twisting sliding mode and continuous integral sliding mode controllers are designed for the control of generator and grid-side converters to track the maximum power trajectory accurately, and they are compared to each other for the chattering in experimental results. A comparison is also performed between the conventional and proposed hill climbing methods based on the captured energy from the wind. Experimental results, with a wind turbine emulator, demonstrate that the proposed hill climbing method relaxes the wrong directionality and sluggish performance of the conventional one.

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.

Photovoltaic (PV) solar generation is gaining an increasing attention due to technological advances such as higher efficiency and life of PV cells and cost reduction. Due to its vast territory, Brazil is composed of regions that can explore renewable energy sources for electricity generation, and the solar resource is found satisfactorily in several areas of the country. This article presents a solar irradiance prediction mechanism developed using data collected in Fortaleza-CE, Brazil. Due to the fact of its characteristic of unpredictability for this resource, many researchers look for several methods to take the generation of this type of energy. The predictions were performed using a Radial Basis Function (RBF) a computational model based on the human nervous system, it is a technical and effective for time series forecasting, which is a relatively complex problem, Artificial Neural Network (ANN) with the advancement of 1 hour. In the ANN performance, a total of 34.4% forecasts underestimated solar energy availability, 7% of the forecasts obtained error 0 and 58.6% of forecasts overestimated the solar resource. A total of 62.33% of forecasts was between -10% and 10% of forecast error. The prediction mean error was 5.93% and the Mean Absolute Percentage Error (MAPE) was 11.43%.

The increasing of photovoltaic plant installations at different scales promotes the development of monitoring systems that facilitate the communication, control and automation of the generating units, allowing to guarantee the predicted energy generation performance. Monitoring systems are composed of different interfaces that involve sensing and capturing data; conversion, treatment, pre-storage and transmission of data; and publishing and final storage through graphic interface. This article focuses on describing the growth of decentralized plants, as well as the increasing demand for monitoring and data acquisition system, commenting the limitations of current commercial models and presenting alternative developed monitoring systems with different platforms.

This work contributes to the research on three-phase photovoltaic systems via a new more robust online adaptive neuro-fuzzy maximum power point tracking (MPPT) control technique considering real partial shading and load conditions. The trapping in local minima and high computational cost in the existing neuro-fuzzy structure are addressed by incorporating B-spline function in the proposed control method. The system parameters are adjusted online via an adaptive neuro-fuzzy inference system rules acquired from the MPPT error. The optimization part of the proposed control law is performed through an online learning gradient-descent back-propagation algorithm. The superiority of the proposed control in terms of energy conversion efficiency, MPPT error, and output power is checked under the same operating conditions with well-known used traditional and intelligent MPPT control algorithms. Finally, the robustness of the proposed control is confirmed through a complete day simulation and comparison indexes.

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.

Introduction: The Sydney system proposal for the study and reporting of lymphadenopathy by fine-needle aspiration (FNA) constitutes one of the first attempts to standardize this procedure. Here, we review its applicability. Materials and Methods: A retrospective study in which all ultrasound-guided FNAs (USFNAs) of superficial lymphadenopathy (palpable or not) performed by interventional pathologists in 2 specialized hospital centers were quantified over 2 years. The procedure was systematized, and the diagnoses were reclassified according to the Sydney system categories. Results: We analyzed 363 USFNAs of lymphadenopathies. The distribution of cases by categories was as follows: insufficient (n = 13; 3.58%), benign (n = 208; 57.30%), atypia of uncertain significance (n = 7; 1.93%), suspicious (n = 21; 5.79), and malignant (n = 114; 31.40%). The risks of malignancy calculated for categories I, II, III, IV, and V were 27%, 3%, 50%, 100%, and 100%, respectively. Conclusion: The implementation of the Sydney system allows the systematization and standardization of the lymph node FNA methodology, with increased efficacy and efficiency. Assimilating the recommendations enables the qualification of the diagnostic procedure.

Maximum Constant Boost Control (MCBC) is one of the most suitable modulation techniques for Z-Source Inverters (ZSI) and quasi-ZSI (qZSI). Nevertheless, it cannot decouple the output voltage control and the fluctuations of the voltage source at the input of the inverter. This work proposes a new method based on this modulation technique that allows decoupling the control of these two variables, input and output voltages of a qZSI. The simulation results show that the Decoupled Maximum Constant Boost Control (DMCBC) has the same features and advantages than the one without decoupling. Voltage gain, stress and harmonic distortion are studied and the results show that the behavior is not modified, except for the reduction of the boost factor.

Mycobacterium kansasii extrapulmonary infections are infrequent in immunocompetent adults. Rifampin (RIF), clarithromycin (CLR), isoniazid (INH) and ethambutol (EMB) are included in all the standard regimens against M.kansasii. We report a case of a healthy 65-year-old male farmer who presented with isolated right supraclavicular lymphadenopathy. The lymph node FNA showed acid-fast-bacilli and granulomatous inflammation. Quantiferon TB Gold test, HIV serology, and functional immunological studies were all negative or normal. He was put on a standard 4 drugs anti-tuberculous regimen that was switched to RIF + CLR+ INH after the Microbiology lab demonstrated an EMB–resistant Mycobacterium kansasii isotype I strain. The patient was cured after 12 months of therapy. This is the 6th reported case of M. kansasii extrapulmonary lymphadenitis in an immunocompetent adult and the 2nd showing EMB resistance in the world literature. Antimycobacterial regimens against M. kansasii, classically resistant to pyrazinamide (PZA) might also exclude EMB due to its increasing resistance in Europe. A 612 months therapy with at least 2 effective antimycobacterial drugs including RIF + CLR might be enough to treat extrapulmonary M. kansasii infections in immunocompetents. Keywords: Mycobacterium kansasii, Cervical lymphadenitis, Immunocompetent, Resistance, Ethambutol, Quantiferon

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.

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.

Rural electrification is one of the most significant issues faced by electricity companies. For this reason, these companies are choosing alternative sources to generate energy in isolated regions. Furthermore, hybrid generation systems are an effective option for supplying protected areas. In this context, this research aims at designing an autonomous hybrid system to meet the annual electricity demand of the inhabitants of a national park. Fluvial and solar energies are the best options to reduce environmental impact and to ensure the conservation of the endemic fauna and flora of the island at a low carbon footprint. The system comprises a series of subsystems modeled using commercial software for sizing and optimization. The main generation subsystem contains a hydrokinetic turbine and photovoltaic panels, the storage subsystem contains a battery bank, and the backup subsystem consists of a diesel generator used in case of lack of energy from the rest of suppliers of the hybrid system. The main results of the simulation show an optimized system that fulfills the energy demand while minimizing the use of the diesel generator to 5668 kWh/year (14.3%) of thorough generation. The hydrokinetic generator supplies 20,330 kWh/year (51.4% of the total generation) and the solar generator supplies 13,580 kWh/year (34.3%).

An ever-increasing penetration of electric vehicles (EVs) on the roads inevitably leads to an ever-stringent need for an adequate charging infrastructure. The emerging ultra-fast charging (UFC) technology has the potential to provide a refueling experience similar to that of gasoline vehicles; hence, it has a key role in enabling the adoption of EVs for medium-long distance travels. From the perspective of the UFC station, the differences existing in the EVs currently on the market make the sizing problem more challenging. A suitably conceived charging strategy can help to address these concerns. In this paper, we present a smart charging station concept that, through a modular DC/DC stage design, allows the split of the output power among the different charging ports. We model the issue of finding the optimal charging station as a single-objective optimization problem, where the goal is to find the number of modular shared DC/DC converters, and where the power rate of each module ensures the minimum charging time and charging cost. Simulation results show that the proposed solution could significantly reduce the required installed power. In particular, they prove that with an installed power of 800 kW it is possible to satisfy the needs of a UFC station composed of 10 charging spots.

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).

We introduce a new general class of metric f-manifolds which we call (nearly) trans-S-manifolds and includes S- manifolds, C-manifolds, s-th Sasakian manifolds and generalized Kenmotsu manifold studied previously. We prove their main properties and we present many examples which justify their study., Comment: 15 pages

We consider generalized ( κ , μ ) {(\kappa,\mu)} -paracontact metric manifolds satisfying certain flatness conditions on the ℳ {\mathcal{M}} -projective curvature tensor. Specifically, we study ξ- ℳ {\mathcal{M}} -projectively flat and ℳ {\mathcal{M}} -projectively flat generalized ( κ , μ ) {(\kappa,\mu)} -paracontact metric manifolds and, further, ϕ- ℳ {\mathcal{M}} -projectively symmetric generalized ( κ ≠ - 1 , μ ) {(\kappa\neq-1,\mu)} -paracontact metric manifolds. We prove that they are characterized by certain structures whose properties are discussed in some detail.

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.

Mycobacterium kansasii extrapulmonary infections are infrequent in immunocompetent adults. Rifampin (RIF), clarithromycin (CLR), isoniazid (INH) and ethambutol (EMB) are included in all the standard regimens against M.kansasii. We report a case of a healthy 65-year-old male farmer who presented with isolated right supraclavicular lymphadenopathy. The lymph node FNA showed acid-fast-bacilli and granulomatous inflammation. Quantiferon TB Gold test, HIV serology, and functional immunological studies were all negative or normal. He was put on a standard 4 drugs anti-tuberculous regimen that was switched to RIF + CLR+ INH after the Microbiology lab demonstrated an EMB–resistant Mycobacterium kansasii isotype I strain. The patient was cured after 12 months of therapy. This is the 6th reported case of M. kansasii extrapulmonary lymphadenitis in an immunocompetent adult and the 2nd showing EMB resistance in the world literature. Antimycobacterial regimens against M. kansasii, classically resistant to pyrazinamide (PZA) might also exclude EMB due to its increasing resistance in Europe. A 612 months therapy with at least 2 effective antimycobacterial drugs including RIF + CLR might be enough to treat extrapulmonary M. kansasii infections in immunocompetents.

In this paper, energy management and control of a microgrid is developed through supervisor and adaptive neuro?fuzzy wavelet?based control controllers considering real weather patterns and load variations. The supervisory control is applied to the entire microgrid using lower–top level arrangements. The top?level generates the control signals considering the weather data patterns and load conditions, while the lower level controls the energy sources and power converters. The adaptive neuro?fuzzy wavelet?based controller is applied to the inverter. The new proposed wavelet?based controller improves the operation of the proposed microgrid as a result of the excellent localized characteristics of the wavelets. Simulations and comparison with other existing intelligent controllers, such as neuro?fuzzy controllers and fuzzy logic controllers, and classical PID controllers are used to present the improvements of the microgrid in terms of the power transfer, inverter output efficiency, load voltage frequency, and dynamic response. © 2020 by the authors. Licensee MDPI, Basel, Switzerland. Ministerio de Ciencia, Innovación y Universidades, MCIU: RTI2018?095720?B?C32; Deutsche Forschungsgemeinschaft, DFG: 350746631; Türkiye Bilimsel ve Teknolojik Araştirma Kurumu, TÜBITAK: 5190011 Funding: The work of Murat Karabacak and Tariq Kamal is sponsored by the Scientific and Technological Research Council of Turkey under project number 5190011. The work of Vedran S. Peri? is supported by the Bavarian Government and Deutsche Forschungsgemeinschaft (DFG) under project number 350746631. The work of Luis M. Fernández?Ramírez and Tariq Kamal is sponsored by the Spanish Ministry of Science, Innovation, and Universities under project number RTI2018?095720?B?C32.

This paper proposes an efficient bridgeless power factor corrected (PFC) modified single ended primary inductor converter (SEPIC) for arc welding power supplies (AWPS). The overall configuration is composed of two converters: (1) a modified bridgeless SEPIC PFC converter, which is controlled by a PI controller to achieve a high power factor and fast response; and (2) a full bridge buck converter with high-frequency transformer for high-frequency isolation to ensure arc welding stability. The proposed system is simulated under different operating conditions of an AWPS. It is also tested in real time by a hardware-in-the-loop system based on a dSPACE DS1103 control board. The system performances are evaluated based on power quality indices such as power factor, total harmonic distortions of the AC grid current, and voltage regulation. The obtained results show that the proposed controller enhances the weld bead quality by keeping a constant current at the output and a stable arc, meet the international power quality standards and robustness for voltage regulation.

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 work provides the dynamic operation and supervisory control of a hybrid renewable energy system which supplies power in stand-alone as well as in grid-connected mode. It contains a photovoltaic as a primary source controlled via fuzzy and a Proton Exchange Membrane Fuel Cell (PEMFC) as a secondary source controlled via Proportional Integral Differential (PID) controller. The high intermittency nature of photovoltaic is addressed through the integration of super-capacitor and battery bank in the proposed architecture. The overall strategy of the proposed system is achieved using dynamic power switches of the power converters. The strategy maximizes the use of available photovoltaic /fuel cell/ super-capacitor/battery power and reduces stress on the public grid under all conditions for 24 hours. The proposed test-bed is simulated under real weather pattern and load variations. Simulations conclude the effectiveness of the proposed architecture.

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.