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Power converters are the basic elements of any power electronics system in many areas and applications. Among them, the push–pull converter topology is one of the most widespread due to its high efficiency, versatility, galvanic isolation, reduced number of switching devices and the possibility of implementing high conversion ratios with respect to non-isolated topologies. Optimal design and control requires very accurate models that consider all the non-idealities associated with the actual converter. However, this leads to the use of high-order models, which are impractical for the design of model-based controllers in real-time applications. To obtain a trade-off model that combines the criteria of simplicity and accuracy, it is appropriate to assess whether it is necessary to consider all non-idealities to accurately model the dynamic response of the converter. For this purpose, this paper proposes a methodology based on a sensitivity analysis that allows quantifying the impact of each non-ideality on the converter behaviour response as a function of the converter topology, power and frequency. As a result of the study, practical models that combine the trade-off between precision and simplicity are obtained. The behaviour of the simplified models for each topology was evaluated and validated by simulation against the most complete and accurate non-ideal model found in the literature. The results have been excellent, with an error rate of less than 5% in all cases. [ABSTRACT FROM AUTHOR]

The current need to reduce carbon emissions makes hydrogen use essential for self-consumption in microgrids. To make a profitability analysis of a microgrid, the influence of equipment costs and the electricity price must be known. This paper studies the cost-effective electricity price (EUR/kWh) for a microgrid located at ''La Rábida Campus" (University of Huelva, south of Spain), for two different energy-management systems (EMSs): hydrogen-priority strategy and battery-priority strategy. The profitability analysis is based, on one hand, on the hydrogen-systems' cost reduction (%) and, on the other hand, considering renewable energy sources (RESs) and energy storage systems (ESSs), on cost reduction (%). Due to technological advances, microgrid-element costs are expected to decrease over time; therefore, future profitable electricity prices will be even lower. Results show a cost-effective electricity price ranging from 0.61 EUR/kWh to 0.16 EUR/kWh for hydrogen-priority EMSs and from 0.4 EUR/kWh to 0.17 EUR/kWh for battery-priority EMSs (0 and 100% hydrogen-system cost reduction, respectively). These figures still decrease sharply if RES and ESS cost reductions are considered. In the current scenario of uncertainty in electricity prices, the microgrid studied may become economically competitive in the near future. [ABSTRACT FROM AUTHOR]

Power converters are a basic element for the control and design of any power electronic system. Among the many available topologies, the push–pull converter is widely used due to its versatility, safety and efficiency. For its correct analysis, sizing, simulation and control, models that meet the characteristics of generality, accuracy and simplicity are required, especially if its control is to be optimized by means of some analytical technique. This requires models that consider the practical non-idealities intrinsic to the converter, as well as being intuitive and easy to handle analytically in a control loop. In general, the models reviewed in the scientific literature adopt simplifications in their definition that are detrimental to their accuracy. In response to the posed problem, this work presents a generalized, complete, accurate and versatile model of real (non-ideal) push–pull converters, ideal for the analysis, simulation, and control of power systems. Following the premise of general and complete converters, the proposed model includes all the practical non-idealities of the converter elements, and it is accurate because it faithfully reflects its dynamics. Furthermore, the model is versatile, as its state space formulation allows for its easy adaptability to the converter operating conditions (voltage, current and temperature) for each sampling time. Also, the model is excellent for use in model-based control techniques, as well as for making very accurate simulators. The behavior of the developed model has been contrasted with a real push–pull converter, as well as with reference models present in the scientific literature for both dynamic and steady-state response tests. The results show excellent performance in all the studied cases, with behavior faithful to the real converter and with relative errors that are much lower than those obtained for the reference models. It follows that the model behaves like a digital twin of a real push–pull converter. [ABSTRACT FROM AUTHOR]

Current climate crisis makes the need for reducing carbon emissions more than evident. For this reason, renewable energy sources are expected to play a fundamental role. However, these sources are not controllable, but depend on the weather conditions. Therefore, green hydrogen (hydrogen produced from water electrolysis using renewable energies) is emerging as the key energy carrier to solve this problem. Although different properties of hydrogen have been widely studied, some key aspects such as the water and energy footprint, as well as the technological development and the regulatory framework of green hydrogen in different parts of the world have not been analysed in depth. This work performs a data-driven analysis of these three pillars: water and energy footprint, technological maturity, and regulatory framework of green hydrogen technology. Results will allow the evaluation of green hydrogen deployment, both the current situation and expectations. Regarding the water footprint, this is lower than that of other fossil fuels and competitive with other types of hydrogen, while the energy footprint is higher than that of other fuels. Additionally, results show that technological and regulatory framework for hydrogen is not fully developed and there is a great inequality in green hydrogen legislation in different regions of the world. [ABSTRACT FROM AUTHOR]

This paper presents an economic impact analysis and carbon footprint study of a hydrogen-based microgrid. The economic impact is evaluated with respect to investment costs, operation and maintenance (O&M) costs, as well as savings, taking into account two different energy management strategies (EMSs): a hydrogen-based priority strategy and a battery-based priority strategy. The research was carried out in a real microgrid located at the University of Huelva, in southwestern Spain. The results (which can be extrapolated to microgrids with a similar architecture) show that, although both strategies have the same initial investment costs (EUR 52,339.78), at the end of the microgrid lifespan, the hydrogen-based strategy requires higher replacement costs (EUR 74,177.4 vs. 17,537.88) and operation and maintenance costs (EUR 35,254.03 vs. 34,877.08), however, it provides better annual savings (EUR 36,753.05 vs. 36,282.58) and a lower carbon footprint (98.15% vs. 95.73% CO2 savings) than the battery-based strategy. Furthermore, in a scenario where CO2 emission prices are increasing, the hydrogen-based strategy will bring even higher annual cost savings in the coming years. [ABSTRACT FROM AUTHOR]

Currently, the number of job offers in STEM careers (Science, Technology, Engineering and Mathematics) is growing up, but by contrast, the number of graduates in these fields is decreasing, particularly women graduates. Consequently, if we do not promote the training of women in STEM careers, the gender gap, far from narrowing, will continue to widen. This paper presents the research carried out in the ALAS project (Accompanying girLs towArds STEM careers), which consists of an experimental analysis based on a multi-model study to discover the possible causes of this low participation of women in STEM fields. The models used are the (1) expectancy–value theory of motivation, (2) social role theory, and (3) gender stereotypes theory. Additionally, participatory workshops have been carried out, with the aim of capturing the students' reactions when they are introduced to STEM practices. The surveyed target groups range from primary education groups up to university graduates and enterprise employees, including both students and teachers. The obtained results show that there are still social patterns that make young people differentiate certain types of activities based on gender, especially at secondary school age. Nevertheless, the findings reveal that beyond the three studied models, a key factor in young people's decision to be enrolled in STEM careers is their educational environment. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs), in their pure and hybrid variants, have become the main alternative to ensure the decarbonization of the current vehicle fleet. Due to its excellent performance, EV technology is closely linked to lithium-ion battery (LIB) technology. A LIB is a complex dynamic system with extraordinary nonlinear behavior defined by electrical, thermal and electrochemical dynamics. To ensure the proper management of a LIB in such demanding applications as EVs, it is crucial to have an accurate mathematical model that can adequately predict its dynamic behavior. Furthermore, this model must be able to iteratively adapt its parameters to accommodate system disturbances during its operation as well as performance loss in terms of efficiency and nominal capacity during its life cycle. To this end, a methodology that employs the extended Kalman filter to iteratively improve a fuzzy model applied to a real LIB is presented in this paper. This algorithm allows to improve the classical Takagi–Sugeno fuzzy model (TSFM) with each new set of data obtained, adapting the model to the variations of the battery characteristics throughout its operating cycle. Data for modeling and subsequent validation were collected during experimental tests on a real LIB under EVs driving cycle conditions according to the "worldwide harmonised light vehicle test procedure" (WLTP) standard. The TSFM results allow the creation of an accurate nonlinear dynamic model of the LIB, even under fluctuating operating conditions, demonstrating its suitability for modeling and design of model-based control systems for LIBs used in EVs applications. [ABSTRACT FROM AUTHOR]

This paper aims to analyse two energy storage methods—batteries and hydrogen storage technologies—that in some cases are treated as complementary technologies, but in other ones they are considered opposed technologies. A detailed technical description of each technology will allow to understand the evolution of batteries and hydrogen storage technologies: batteries looking for higher energy capacity and lower maintenance, while hydrogen storage technologies pursuing better volumetric and gravimetric densities. Additionally, as energy storage systems, a mathematical model is required to know the state of charge of the system. For this purpose, a mathematical model is proposed for conventional batteries, for compressed hydrogen tanks, for liquid hydrogen storage and for metal hydride tanks, which makes it possible to integrate energy storage systems into management strategies that aim to solve the energy balance in plants based on hybrid energy storage systems. From the technical point of view, most batteries are easier to operate and do not require special operating conditions, while hydrogen storage methods are currently functioning at the two extremes (high temperatures for metal and complex hydrides and low temperatures for liquid hydrogen or physisorption). Additionally, the technical comparison made in this paper also includes research trends and future possibilities in an attempt to help plan future policies. [ABSTRACT FROM AUTHOR]

Featured Application: The main application was to give a second life to an obsolete and declassified type of RPAS (remotely piloted aircraft system) for use in monitoring key parameters, in the cultivation of the olive tree and in other types of cultivation that occupy large areas of land. Similarly, it can be used to track and monitor endangered animal species. INTA (National Institute for Aerospace Applications) is located on the grounds of the Doñana National Park, where the Iberian lynx lives, one of the most threatened felines in the world, taking advantage of some of the main advantages of this RPA (remotely piloted aircraft) like autonomy, efficiency, low-noise level, and non-polluting. It is well proved that remotely piloted aircraft systems (RPASs) are very useful systems for remote sensing in precision agricultural labors. INTA (National Institute for Aerospace Applications) and the University of Huelva are involved in Tecnolivo Project that proposes the development of a marketable and easy-to-use technological solution that allows integrated, ecological, and optimized management of the olive grove through non-invasive monitoring of key agronomic parameters using RPASs. The information collected by the RPAS in regards to the state of the vegetation, such as hydric stress levels, plague detection, or maturation of the fruit, are very interesting for farmers when it comes to make decisions about their crops. Current RPAS applications for precision agriculture are mainly developed for small- to medium-sized crops using rotary-wing RPASs with small range and endurance operation, leaving aside large-sized crops. This work shows the conversion of a fully declassified and obsolete fixed-wing internal combustion engine (ICE) remotely piloted aircraft (RPA), used as aerial target for military applications and in reconnaissance and surveillance missions at low cost, into an electric lithium polymer (LiPo) battery-driven RPA that will be used for precision agriculture in large-sized crop applications, as well as other applications for tracking and monitoring of endangered animal species in national parks. This RPA, being over twenty years old, has undergone a deep change. The applied methodology consisted of the design of a new propulsion system, based on an electric motor and batteries, maintaining the main airworthiness characteristics of the aircraft. Some other novelties achieved in this study were: (1) Change to a more efficient engine, less heavy and bulky, with a greater ratio of torque vs. size. Modernization of the fly control system and geolocation system. (2) Modification of the type and material of the propeller, reaching a higher performance. (3) Replacement of a polluting fuel, such as gasoline, with electricity from renewable sources. (4) Development of a new control software, etc. Preliminary results indicate that the endurance achieved with the new energy and propulsion systems and the payload weight available in the RPA meet the expectations of the use of this type of RPAS in the study of large areas of crops and surveillance. [ABSTRACT FROM AUTHOR]

This work presents a hardware/software data acquisition system developed for monitoring the temperature in real time of the cells in Air-Cooled Polymer Electrolyte Fuel Cells (AC-PEFC). These fuel cells are of great interest because they can carry out, in a single operation, the processes of oxidation and refrigeration. This allows reduction of weight, volume, cost and complexity of the control system in the AC-PEFC. In this type of PEFC (and in general in any PEFC), the reliable monitoring of temperature along the entire surface of the stack is fundamental, since a suitable temperature and a regular distribution thereof, are key for a better performance of the stack and a longer lifetime under the best operating conditions. The developed data acquisition (DAQ) system can perform non-intrusive temperature measurements of each individual cell of an AC-PEFC stack of any power (from watts to kilowatts). The stack power is related to the temperature gradient; i.e., a higher power corresponds to a higher stack surface, and consequently higher temperature difference between the coldest and the hottest point. The developed DAQ system has been implemented with the low-cost open-source platform Arduino, and it is completed with a modular virtual instrument that has been developed using NI LabVIEW. Temperature vs time evolution of all the cells of an AC-PEFC both together and individually can be registered and supervised. The paper explains comprehensively the developed DAQ system together with experimental results that demonstrate the suitability of the system. [ABSTRACT FROM AUTHOR]

In this work a new, scalable and low cost multi-channel monitoring system for Polymer Electrolyte Fuel Cells (PEFCs) has been designed, constructed and experimentally validated. This developed monitoring system performs non-intrusive voltage measurement of each individual cell of a PEFC stack and it is scalable, in the sense that it is capable to carry out measurements in stacks from 1 to 120 cells (from watts to kilowatts). The developed system comprises two main subsystems: hardware devoted to data acquisition (DAQ) and software devoted to real-time monitoring. The DAQ subsystem is based on the low-cost open-source platform Arduino and the real-time monitoring subsystem has been developed using the high-level graphical language NI LabVIEW. Such integration can be considered a novelty in scientific literature for PEFC monitoring systems. An original amplifying and multiplexing board has been designed to increase the Arduino input port availability. Data storage and real-time monitoring have been performed with an easy-to-use interface. Graphical and numerical visualization allows a continuous tracking of cell voltage. Scalability, flexibility, easy-to-use, versatility and low cost are the main features of the proposed approach. The system is described and experimental results are presented. These results demonstrate its suitability to monitor the voltage in a PEFC at cell level. [ABSTRACT FROM AUTHOR]

This work deals with the prediction of variables for a hydrogen energy storage system integrated into a microgrid. Due to the fact that this kind of system has a nonlinear behaviour, the use of traditional techniques is not accurate enough to generate good models of the system under study. Then, a hybrid intelligent system, based on clustering and regression techniques, has been developed and implemented to predict the power, the hydrogen level and the hydrogen system degradation. In this research, a hybrid intelligent model was created and validated over a dataset from a lab-size migrogrid. The achieved results show a better performance than other well-known classical regression methods, allowing us to predict the hydrogen consumption/generation with a mean absolute error of 0.63% with the test dataset respect to the maximum power of the system. [ABSTRACT FROM AUTHOR]

This paper proposes a multi-objective model predictive control (MPC) designed for the power management of a multi-stack fuel cell (FC) system integrated into a renewable sources-based microgrid. The main advantage of MPC is the fact that it allows the current timeslot to be optimized while taking future timeslots into account. The multi-objective function solves the problem related to the power dispatch at time that includes criteria to reduce the multi-stack FC degradation, operating and maintenance costs, as well as hydrogen consumption. Regarding the scientific literature, the novelty of this paper lies in the proposal of a generalized MPC controller for a multi-stack FC that can be used independently of the number of stacks that make it up. Although all the stacks that make up the modular FC system are identical, their levels of degradation, in general, will not be. Thus, over time, each stack can present a different behavior. Therefore, the power control strategy cannot be based on an equal distribution according to the nominal power of each stack. On the contrary, the control algorithm should take advantage of the characteristics of the multi-stack FC concept, distributing operation across all the stacks regarding their capacity to produce power/energy, and optimizing the overall performance. [ABSTRACT FROM AUTHOR]

This paper proposes a fuzzy logic-based energy management system (EMS) for microgrids with a combined battery and hydrogen energy storage system (ESS), which ensures the power balance according to the load demand at the time that it takes into account the improvement of the microgrid performance from a technical and economic point of view. As is known, renewable energy-based microgrids are receiving increasing interest in the research community, since they play a key role in the challenge of designing the next energy transition model. The integration of ESSs allows the absorption of the energy surplus in the microgrid to ensure power supply if the renewable resource is insufficient and the microgrid is isolated. If the microgrid can be connected to the main power grid, the freedom degrees increase and this allows, among other things, diminishment of the ESS size. Planning the operation of renewable sources-based microgrids requires both an efficient dispatching management between the available and the demanded energy and a reliable forecasting tool. The developed EMS is based on a fuzzy logic controller (FLC), which presents different advantages regarding other controllers: It is not necessary to know the model of the plant, and the linguistic rules that make up its inference engine are easily interpretable. These rules can incorporate expert knowledge, which simplifies the microgrid management, generally complex. The developed EMS has been subjected to a stress test that has demonstrated its excellent behavior. For that, a residential-type profile in an actual microgrid has been used. The developed fuzzy logic-based EMS, in addition to responding to the required load demand, can meet both technical (to prolong the devices' lifespan) and economic (seeking the highest profitability and efficiency) established criteria, which can be introduced by the expert depending on the microgrid characteristic and profile demand to accomplish. [ABSTRACT FROM AUTHOR]

In this work, a new low-cost and high-performance system for cells voltage monitoring and degradation studies in air-cooled polymer electrolyte fuel cells has been designed, built and validated in the laboratory under experimental conditions. This system allows monitoring in real time the cells' voltages, the stack current and temperature in fuel cells made of up to 100 cells. The developed system consists of an acquisition system, which complies with all the recommendations and features necessary to perform degradation tests. It is a scalable configuration with a low number of components and great simplicity. Additionally, the cell voltage monitoring (CVM) system offers high rate of accuracy and high reliability and low cost in comparison with other commercial systems. In the same way, looking for an "All-in-One" solution, the acquisition hardware is accompanied by a software tool based on the "plug and play" philosophy. It allows in a simple way obtaining information from the cells and performing a degradation analysis based on the study of the polarisation curve. The different options and tools included in the CVM system permit, in a very intuitive and graphical way, detecting and quantifying the cell degradation without the need of isolating the stack from the system. Experimental tests carried out on the system validate its performance and show the great applicability of the system in cases where cell faults detection and degradation analysis are required. • Study of commercial solutions for fuel cell degradation analysis. • Study and design of hardware to perform accurate degradation analysis. • Experimental case is presented to demonstrate the proposal solution. • Conclusions and future works derived from experimental case are presented. [ABSTRACT FROM AUTHOR]