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Nowadays, several alternatives to internal combustion engines are being proposed in order to reduce CO2 emissions in freight transportation and citizen mobility. According to many experts, the use of electric vehicles constitutes one of the most promising alternatives for achieving the desirable reductions in emissions. However, popularization of these vehicles is being slowed by long recharging times and the low availability of recharging stations. One possible solution to this issue is to employ the concept of battery sharing or battery swapping. This concept is supported by important industrial partners, such as Eni in Italy, Ample in the US, and Shell in the UK. This paper supports the introduction of battery swapping practices by analyzing their effects. A discrete-event simulation model is employed for this study. The obtained results show that battery sharing practices are not just a more environmentally and socially friendly solution, but also one that can be highly beneficial for reducing traffic congestion.

Machine learning algorithms and the increasing availability of data have radically changed the way how decisions are made in today’s Industry. A wide range of algorithms are being used to monitor industrial processes and predict process variables that are difficult to be measured. Maintenance operations are mandatory to tackle in all industrial equipment. It is well known that a huge amount of money is invested in operational and maintenance actions in industrial gas turbines (IGTs). In this paper, two variations of autoencoders were used to analyse the performance of an IGT after major maintenance. The data used to analyse IGT conditions were ambient factors, and measurements were performed using several sensors located along the compressor. The condition assessment of the industrial gas turbine compressor revealed significant changes in its operation point after major maintenance; thus, this indicates the need to update the internal operating models to suit the new operational mode as well as the effectiveness of autoencoder-based models in feature extraction. Even though the processing performance was not compromised, the results showed how this autoencoder approach can help to define an indicator of the compressor behaviour in long-term performance. This research was funded by Siemens Energy.

The paper presents a set of prototype smart grid technologies and services and validates the economic viability of the proposed solution using cost–benefit analysis (CBA). The study considered the EU-funded project called RESOLVD and implemented the technologies and services in a real-life pilot. the technologies and services on the EU-funded H2020. The paper focuses on the analysis of technological solutions which enhance the operational efficiency and the hosting capacity of low-voltage electricity distribution grids. The solutions provided better integration of a hybrid battery storage system, with the grid interfacing power electronics, smart gateways for the interconnection of assets at the grid edge, and sensors enhancing infrastructure observability and control. The result from the CBA indicates the economic viability of the project, high scalability, and replicability. The economic benefits were realized with the breakeven value of eight secondary substations (SS) and 16 feeders. The scenario test on the DSO’s willingness to pay for the software as a service (SaaS) revealed that the payback period can further be reduced by almost half with a higher internal rate of return (IRR) and net present value (NPV). Both the CBA and scenario tests showed RESOLVD solution can become more economically viable when deployed in largescale. Moreover, the CBA results provide evidence to the energy policy by allowing DSOs to consider both CAPEX and OPEX for better investment decisions. Further, the paper proposes an alternative business approach that shifts from grid reinforcement to service provision. The paper also discusses the research implications on energy policy and business. Peer Reviewed Objectius de Desenvolupament Sostenible::9 - Indústria, Innovació i Infraestructura Objectius de Desenvolupament Sostenible::11 - Ciutats i Comunitats Sostenibles

The increasing penetration of Large-Scale Photovoltaic Power Plants in the power system is raising the concern of potential stability issues due to dynamic interactions of power electronics components. In particular, Power Plant Controllers are starting to provide a fast dynamic response for specific services, such as fast frequency response, which could trigger unexpected unstable interactions with the PV inverters or other grid components. Also, an eventual reduction of synchronous generation in the grid could lead to a power system with high penetration of power electronics, which presents unexplored stability problems. This paper presents an interaction and stability study of a Photovoltaic Power Plant connected to the grid. This study is based on a small-signal analysis employing eigenvalues and participation factors to identify potential unstable modes. A linear model of the Photovoltaic Power Plant is implemented to apply a small-signal analysis. This linear model is validated with the equivalent non-linear model based on time-domain simulations in Matlab Simulink. 2022 The Author(s) The work of Oriol Gomis-Bellmunt is supported by the ICREA Academia program. Marc Cheah-Mane, Eduardo Bullich-Massague and Eduardo Prieto-Araujo are Lecturers of the Serra Hunter programme. This work is also supported under the umbrella of SOLAR-ERA.NET Cofund, which includes the Ministry of Economy and Competitiveness, the CDTI and the Swedish Energy Agency. SOLAR-ERA.NET is supported by the European Commission within the EU Framework Programme for Research and Innovation HORIZON 2020 (Cofund ERA-NET Action, no. 691664 ) This work was supported by the National Priorities Research Program under Grant 11S-1125-170027 from the Qatar National Research Fund (a member of Qatar Foundation ). Scopus 2-s2.0-85124150691

© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works This paper presents an Multi-Input Multi-Output (MIMO) analysis to investigate the mutual interactions and small-signal stability of bipolar-type dc microgrids. Since bipolar dc microgrid is replete with power-electronic converters, its dynamics can not be understood unless the interactions among control systems of converters are properly investigated. To tackle the challenge, each converter in microgrid is modeled via an MIMO transfer matrix. Then, the MIMO models are combined together based on the interactions among the control systems of source and load converters. From this integrative MIMO model, the mutual interactions between various input-output pairs are quantified using Gershgorin Band theorem. Also, Singular Value Decomposition (SVD) analysis is carried out to estimate the frequency of unstable poles. Test results not only successfully validate the effectiveness of the MIMO method but also show that the control system of voltage balancer has a major impact on the overall stability of bipolar dc microgrid, making it a suitable location for applying damping systems.

© 2022 Elsevier. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ The use of the electrical energy storage (EES) plays an important role in the transition of energy generation towards renewable energy sources (RESs). An effective sizing of EES systems is very important in order to cope with the volatility of RESs and to ensure a reliable energy supply. The present paper provides a methodology which helps to determine the minimum required EES size for conceiving a fully standalone system. Its approach is based on the evaluation of the energy balance for a given design period, and it can also be applied for sizing the EES system in grid-connected applications. The methodology was validated using measurement data obtained from two different systems corresponding to: a) a near-zero energy building with local generation sources, and b) a large-scale battery energy storage system (BESS) installed in a factory and used for peak-shaving. The obtained results confirmed the effectiveness of the proposed methodology by estimating the required size of the EES system. A good correlation was found between the estimated and the installed BESS size in the considered systems. The deviation between real and estimated BESS capacities was found to be less than 5%. Peer Reviewed Objectius de Desenvolupament Sostenible::13 - Acció per al Clima Objectius de Desenvolupament Sostenible::7 - Energia Assequible i No Contaminant

The automotive sector is rapidly accelerating its transformation towards electric mobility, and electric vehicle (EV) sales have been increasing year after year since the beginning of the decade. Due to their overall performance, lithium-ion batteries currently dominate the electric vehicle market. Each year, car manufacturers launch new models, increasing the average capacity of electric vehicle batteries. This is achieved, in part, through making bigger batteries, which lead to an increase in the vehicle cost, weight and use of more critical raw materials. Although prices are lowering, Li-ion batteries still do not have enough energy density to substantially decrease the weight of vehicles, and EVs are around 50% heavier than common internal combustion engine vehicles (ICEV); thus, using high-energy cells is an intriguing possibility that we are being called on to explore. This Special Issue aims to evaluate several issues concerning high-capacity batteries Peer Reviewed Objectius de Desenvolupament Sostenible::7 - Energia Assequible i No Contaminant

In this paper, a novel two-phase linear hybrid reluctance actuator with the double-sided segmented stator, made of laminated U cores, and an interior mover with permanent magnets is proposed. The permanent magnets are disposed of in a way that increases the thrust force of a double-sided linear switched reluctance actuator of the same size. To achieve this objective, each phase of the actuator is powered by a single H-bridge inverter. To reduce the detent force, the upper and the lower stator were shifted. Finite element analysis was used to demonstrate that the proposed actuator has a high force density with low detent force. In addition, a comparative study between the proposed linear hybrid reluctance actuator, linear switched reluctance, and linear permanent magnet actuators of the same size was performed. Finally, experimental tests carried out in a prototype confirmed the goals of the proposed actuator.

Modern electrical networks are continuously evolving due to the increasing deployment of Information Technologies and Distributed Energy Resources (DERs). This scenario affects the quality of the electricity supply of distribution systems. For this reason, this quality plays a key role on the evolution of electrical networks into Smart Grids. Quality of the electricity supply is defined through three main skills: reliability of the electric power system, power quality and customer relationships, all of them under safety layer. From the network operation point of view, availability in a distribution network is crucial to maintain reliability. Fault location is a priority for electrical network operators in their efforts to ensure high quality for loads, generators and prosumers. The presence of DERs in current electrical distribution networks poses a new scenario where bidirectional current flow complicates fault detection. Implementation of the Smart Grid concept in these networks depends on the automation of procedures such as Fault Location, Isolation and Service Restoration, which enable a rapid response to faults. This paper proposes a fault detection algorithm for grid topologies such as radial, ring, meshed with or without DER penetration.

© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. An accurate electricity price forecasting (EPF) plays a vital role in the deregulated energy markets and has a specific effect on optimal management of the power system. Considering all the potent factors in determining the electricity prices—some of which have stochastic nature—makes this a cumbersome task. In this article, first, Grey correlation analysis is applied to select the effective parameters in EPF problem and eliminate redundant factors based on low correlation grades. Then, a deep neural network with stacked denoising auto-encoders has been utilized to denoise data sets from different sources individually. After that, to detect the main features of the input data and putting aside the unnecessary features, dimension reduction process is implemented. Finally, the rough structure artificial neural network (ANN) has been executed to forecast the day-ahead electricity price. The proposed method is implemented on the data of Ontario, Canada, and the forecasted results are compared with different structures of ANN, support vector machine, long shortterm memory—benchmarking methods in this field—and forecasting data reported by independent electricity system operator (IESO) to evaluate the efficiency of the proposed approach. Furthermore, the results of this article indicate that the proposed method is efficient in terms of reducing error criterion and improves the forecasting error about 5–10 percent in comparison with IESO. This is a remarkable achievement in EPF field.

The application of Artificial Intelligence techniques in industry equips companies with new essential tools to improve their principal processes. This is especially true for energy companies, as they have the opportunity, thanks to the modernization of their installations, to exploit a large amount of data with smart algorithms. In this work we explore the possibilities that exist in the implementation of Machine-Learning techniques for the detection of Non-Technical Losses in customers. The analysis is based on the work done in collaboration with an international energy distribution company. We report on how the success in detecting Non-Technical Losses can help the company to better control the energy provided to their customers, avoiding a misuse and hence improving the sustainability of the service that the company provides.

Electric vehicles are becoming more and more popular. One of the most promising possible solutions is one where a hybrid powertrain made up of a FC (Fuel Cell) and a battery is used. This type of vehicle offers great autonomy and high recharging speed, which makes them ideal for many industrial applications. In this work, three ways to build a hybrid power-train are presented and compared. To illustrate this, the case of an industrial robot designed to move loads within a fully automated factory is used. The analysis and comparison are carried out through different objective criteria that indicate the power-train performance in different battery charge levels. The hybrid configurations are tested using real power profiles of the industrial robot. Finally, simulation results show the performance of each hybrid configuration in terms of hydrogen consumption, battery and FC degradation, and dc bus voltage and current regulation., This research was supported by the María de Maeztu Seal of Excellence to IRI (ref. MDM- 2016-0656) and the Spanish Ministry of Economy and Competitiveness under Project DOVELAR (ref. RTI2018-096001-B-C32).

Under voltage sags, grid-tied photovoltaic inverters should remain connected to the grid according to low-voltage ride-through requirements. During such perturbations, it is interesting to exploit completely the distributed power provisions to contribute to the stability and reliability of the grid. In this sense, this paper proposes a low-voltage ride-through control strategy that maximizes the inverter power capability by injecting the maximum-rated current during the sag. To achieve this objective, two possible active power situations have been considered, i.e., high- and low-power production scenarios. In the first case, if the source is unable to deliver the whole generated power to the grid, the controller applies active power curtailment to guarantee that the maximum rated current is not surpassed. In the second case, the maximum allowed current is not reached, thus, the control strategy determined the amount of reactive power that can be injected up to reach it. The control objective can be fulfilled by means of a flexible current injection strategy that combines a proper balance between positive- and negative-current sequences, which limits the inverter output current to the maximum rated value and avoid active power oscillations. Selected experimental and simulation results are reported in order to validate the effectiveness of the proposed control strategy.

This paper presents a novel voltage sag topology that occurs during an unintentional islanding operation (IO) within a distribution network (DN) due to large induction motors (IMs). When a fault occurs, following the circuit breaker (CB) fault clearing, transiently, the IMs act as generators due to their remanent kinetic energy until the CB reclosing takes place. This paper primarily contributes to voltage sag characterization. Therefore, this novel topology is presented, analytically modelled and further validated. It is worth mentioning that this voltage sag has been identified in a real DN in which events have been recorded for two years. The model validation of the proposed voltage sag is done via digital simulations with a model of the real DN implemented in Matlab considering a wide range of scenarios. Both simulations and field measurements confirm the voltage sag analytical expression presented in this paper as well as exhibiting the high accuracy achieved in the three-phase model adopted.

The optimal management of distributed energy resources is one of the existing challenges for the deployment of microgrids. When microgrids operate under feeder flow control mode, trying to maintain a constant self-consumption, generators adapt their output power to compensate load and non-dispatchable generation variations. So, due to the uncertainty, finding the optimal operation point is an important task that can become complex. This paper proposes an optimal power flow problem formulation for feeder flow controlled microgrids. It iated as a mixed integer second order cone program considering the optimal power flow equations in its relaxed form and uncertainty by means of stochastic formulation. In addition, an algorithm is developed in order to find a feasible optimum solution of the original non-relaxed problem. The proposed algorithm can also be used in other optimal power flow problems with the condition that they must use the same relaxation. The algorithm is validated through the IEEE 33-Bus distribution test system.

Modular multilevel converters (MMC) inherent features are gaining more attention for dc voltage transmission systems. One of the main research paths regarding the converter performance deals with its voltage modulation. Specifically, for medium voltage applications with relatively small number of submodules, the voltage modulation techniques impact on the MMC performance needs to be studied. This work provides an extensive review of the carrier-based pulse with modulation (CB-PWM) techniques proposed to be applied on previous multilevel inverter versions. The CB-PWM methods were adapted to be compatible with an additional cell ranking and selection algorithm to ensure equal energy distribution on the arm cells. The state-of-the-art of zero sequence signals (ZSS) applied on three-phase inverters is also reviewed. The alliance between the ZSS with the CB-PWM, as well as the nearest level modulation (NLM), has an important impact on the MMC harmonic content, efficiency and voltage ripple of its cells capacitors. A 15 MW 28-cell-based MMC is used to investigate each particular combination between the modulation method and the common mode ZSS.

This paper presents a novel architecture for rural distribution grids. This architecture is designed to modernize traditional rural networks into new Smart Grid ones. The architecture tackles innovation actions on both the power plane and the management plane of the system. In the power plane, the architecture focuses on exploiting the synergies between telecommunications and innovative technologies based on power electronics managing low scale electrical storage. In the management plane, a decentralized management system is proposed based on the addition of two new agents assisting the typical Supervisory Control And Data Acquisition (SCADA) system of distribution system operators. Altogether, the proposed architecture enables operators to use more effectively—in an automated and decentralized way—weak rural distribution systems, increasing the capability to integrate new distributed energy resources. This architecture is being implemented in a real Pilot Network located in Spain, in the frame of the European Smart Rural Grid project. The paper also includes a study case showing one of the potentialities of one of the principal technologies developed in the project and underpinning the realization of the new architecture: the so-called Intelligent Distribution Power Router.

Currently, Li-ion cells are the preferred candidates as energy sources for existing portable applications and for those being developed. Thus, a proper characterization of Li-ion cells is required to optimize their use and their manufacturing process. In this study, the transport phenomena and electrochemical processes taking place in LiCoO2-Li(NiMnCo)O2/graphite (LCO-NMC/graphite) cells are identified from half-cell measurements by means of impedance spectroscopy. The results are calculated from current densities, instead of absolute values, for the future comparison of this data with other cells. In particular, impedance spectra are fitted to simple electrical models composed of an inductive part, serial resistance, and various RQ networks—the parallel combination of a resistor and a constant phase element—depending on the cell. Thus, the evolution of resistances, capacitances, and the characteristic frequencies of the various effects are tracked with the state-of-charge (SoC) at two aging levels. Concretely, two effects are identified at the impedance spectrum, one is clearly caused by the charge transfer at the positive electrode, whereas the other one is presumably caused by the transport of lithium ions across the solid electrolyte interphase (SEI) layer. Moreover, as the cells age, the characteristic frequency of the charge transfer is drastically reduced by a factor of around 70%.

Local secondary control has been successfully used to regulate the frequency of inverterbased islanded microgrids without using communications. In this scenario, noticeable steady-state deviations have been observed in active power sharing caused by the inherent clock drift of the digital processors that implement each inverter local control. This paper presents a control scheme that performs frequency regulation and improves the active power sharing under high load conditions, thus alleviating the impact of clock drifts in this situation. The study introduces a theoretical analysis that quantifies the steady-state deviations in active power sharing. It also includes a design procedure for the control parameters based on static and dynamic specifications. Experimental tests validate the expected features of the proposed control. The experimental setup is based on a laboratory microgrid equipped with three independent digital signal processors with different clock drifts.

Electric Vehicles (EVs) have seen significant growth in sales recently and it is not clear how power systems will support the charging of a great number of vehicles. This paper proposes a methodology which allows the aggregated EV charging demand to be determined. The methodology applied to obtain the model is based on an agent-based approach to calculate the EV charging demand in a certain area. This model simulates each EV driver to consider its EV model characteristics, mobility needs, and charging processes required to reach its destination. This methodology also permits to consider social and economic variables. Furthermore, the model is stochastic, in order to consider the random pattern of some variables. The model is applied to Barcelona’s (Spain) mobility pattern and uses the 37-node IEEE test feeder adapted to common distribution grid characteristics from Barcelona. The corresponding grid impact is analyzed in terms of voltage drop and four charging strategies are compared. The case study indicates that the variability in scenarios without control is relevant, but not in scenarios with control. Moreover, the voltages do not reach the minimum voltage allowed, but the MV/LV substations could exceed their capacities. Finally, it is determined that all EVs can charge during the valley without any negative effect on the distribution grid. In conclusion, it is determined that the methodology presented allows the EV charging demand to be calculated, considering different variables, to obtain better accuracy in the results.

In this paper, the finite control set model predictive control is combined with the vector operation technique to be applied in the control of a three-phase active power filter. Typically, in the finite control set technique applied to three-phase power converters, eight different vectors are considered in order to obtain the optimum control signal by minimizing a cost function. On the other hand, the vector operation technique is based on dividing the grid voltage period into six different regions. The main advantage of combining both techniques is that for each region the number of possible voltage vectors to be considered can be reduced to a half, thus reducing the computational load employed by the control algorithm. Besides, in each region, only two phase-legs are switching at high frequency while the remaining phase-leg is maintained to a constant dc-voltage value during this interval. Accordingly, a reduction of the switching losses is obtained. Unlike the typical model predictive control methods which make use of the discrete differential equations of the converter, this method considers a Kalman filter in order to improve the behavior of the closed-loop system in noisy environments. Selected experimental results are exposed in order the demonstrate the validity of the control proposal.

Microgrids are a feasible path to deploy smart grids, an intelligent and highly automated power system. Their operation demands a dedicated communication infrastructure to manage, control and monitor the intermittent sources of energy and loads. Therefore, smart devices will be connected to support the growth of grid smartness increasing the dependency on communication networks, which consumes a high amount of power. In an energy-limited scenario, one of the main issues is to enhance the power supply time. Therefore, this paper proposes a hybrid methodology for microgrid energy management, integrated with a communication infrastructure to improve and to optimize islanded microgrid operation at maximum energy efficiency. The hybrid methodology applies some control management rules, such as intentional load shedding, priority load management, and communication energy saving. These energy saving rules establish a trade-off between increasing microgrid energy availability and communication system reliability. To achieve a compromised solution, a continuous time Markov chain model describes the impact of energy saving policies into system reliability. The proposed methodology is simulated and tested with the help of the modified IEEE 34 node test-system.

Flexibility and reliability of AC microgrids are enhanced by reducing the dependence on communications in multi-layer hierarchical control. In this sense, this paper presents a secondary control with no communications for islanded microgrids. It is based on a control scheme that switches between two configurations according to a time-dependent protocol. With this proposal, an excellent performance in terms of transient response and frequency restoration in steady-state is achieved. The paper also presents design considerations for the control parameters. In addition, the theoretical predictions are validated by experimental results from a laboratory microgrid.

In this work the effect of the dielectrophoretic force (DEP) in the self-assembly process of nanoparticles electrosprayed onto a substrate, is examined. DEP force is originated by the electric field created by the electrospray gun and by the distortion of the field created by the effective dipole of each nanoparticle. It is also shown that the modulus of this force is large when the distance between particles is few times its diameter, provided the medium is wet and the electric field is not switched off. The directional nature of DEP In this wet phase, is shown to chain nanoparticles aligned with the main electric field direction. Although there is a repulsive force between chains in the orthogonal direction to the field, it is minimum when the beads align with the voids in the nearby chains. DEP is a dominant force in the close distances of nanoparticles compared to double layer, van der Waals, electrophoretic retardation, weight and buoyancy.

La publicación final está disponible en Springer a través de 10.1007/s00202-014-0316-z This work analyzes the behavior of surface-mounted permanent magnet synchronous motors (SPMSMs) operating under stator faults. The studied faults are resistive unbalance and winding inter-turn short circuits, which may lead to unbalanced conditions of the motor. Both faults may reduce motor efficiency and performance and produce premature ageing. This work develops an analytical model of the motor when operating under stator faults. By this way, the theoretical basis to understand the effects of resistive unbalance and stator winding inter-turn faults in SPMSMs is settied. This work also compares two methods for detecting and discriminating both faults. For this purpose, a method based on the analysis of the zero-sequence voltage component is presented, which is compared to the traditional method, i.e. the analysis of the stator currents harmonics. Both simulation and experimental results presented in this work show the potential of the zero-sequence voltage component method to provide helpful and reliable data to carry out a simultaneous diagnosis of resistive unbalance and stator winding inter-turn faults.

This paper presents the analysis and design of a sliding-mode control of a boost converter operating in continuous conduction mode that minimizes the inrush current and provides output voltage regulation in front of input voltage perturbations and load changes. The analytical expression of the inrush current is obtained, and the conditions to minimize the current peak are derived. The resulting controller is implemented analogically and employs two switching surfaces. Namely, one surface is combined with the conventional auxiliary diode branch for the start-up, while another one is used for the voltage regulation in steady state. Experimental results are in perfect agreement with the theoretical predictions.

10.1049/iet-epa.2012.0391 This study deals with modelling and simulation of a linear switched reluctance force actuator with an original, simple and low-cost linear encoder. A fast and accurate way of determining linear switched reluctance motors-characteristics based on two-dimensional finite element analyses taking into account end-effects is presented and validated. The linear switched reluctance force actuator is simulated using 'Matlab-Simulink'. The proposed actuator has been built and tested. Experimental measurements have confirmed the simulation results according to the proposed method.

Magnetic ballast discharge lamp modeling has been extensively studied because these lamps can be an important source of harmonics. Discharge lamp models usually represent the arc voltage by a square waveform. However, this waveform can be far from actual arc voltages, which affects the accuracy of the lamp models. This paper investigates the actual arc voltage behavior of discharge lamps from laboratory measurements and proposes a novel characterization of these voltages to reformulate the conventional models. The accuracy of the new model is validated with experimental measurements.

This study presents the analysis and design of a sliding-mode control of a buck converter operating in continuous conduction mode that minimises the energy during start-up and provides output voltage regulation in front of input voltage perturbations and load disturbances. A linear combination of inductor current and capacitor voltage errors with respect to their corresponding equilibrium values is analysed as a switching surface. A linear matrix inequalities (LMI)-based analysis to obtain optimum coefficients of the linear combination reveals that the best compromise between inrush current and output response rapidity is the current control given by the switching surface S(x) = iL − IE, where IE is the current coordinate of the equilibrium point. This surface is proposed for start-up and for rejecting input voltage perturbations, because it is demonstrated that the current control is inherently insensitive to input voltage variations. Output voltage regulation in front of load perturbations or input voltage variations is achieved once the converter is in a steady state by modifying S(x) with the insertion of a PI-correcting network. The resulting controller is implemented analogically and employs two switching surfaces, that is, one surface for start-up and another one for output voltage regulation. The theoretical predictions are verified by means of simulation and experimental results.

© 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works Several pulsewidth modulation (PWM) strategies have been proposed for three-phase multilevel converters. Typically, these PWM methods can be either space-vector or carrier-based implemented, where the carrier-based implementation usually presents a lower computation complexity. In this paper, a novel approach for the carrier-based implementation of different existing PWM methods is proposed for three- (3L) and four-level (4L) dc-ac converters, which can be easily extended to any number of levels. The main features of the proposed approach are its reduced computation complexity and computation time. On the other hand, the proposed approach suggests the derivation of novel PWM strategies which can potentially present improved performance features. As an example, two new discontinuous PWM (DPWM) strategies are proposed for the 4L converter. One of these DPWM strategies presents lower weighted total harmonic distortion than other previously proposed strategies. Simulation and experimental results verify the effectiveness of the proposed approach and novel DPWM strategies.

This paper illustrates the construction of a new class of iterative solvers for power flow calculations based on the method of Alternating Search Directions. This method is fit to the particular algebraic structure of the power flow problem resulting from the combination of a globally linear set of equations and nonlinear local relations imposed by power conversion devices, such as loads and generators. The choice of the search directions is shown to be crucial for improving the overall robustness of the solver. A noteworthy advantage is that constant search directions yield stationary methods that, in contrast with Newton or Quasi-Newton methods, do not require the evaluation of the Jacobian matrix. Such directions can be elected to enforce the convergence to the high voltage operative solution. The method is explained through an intuitive example illustrating how the proposed generalized formulation is able to include other nonlinear solvers that are classically used for power flow analysis, thus offering a unified view on the topic. Numerical experiments are performed on publicly available benchmarks for large distribution and transmission systems.

© 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The extension and size of the power grid is expected to increase in the near future. Managing such a system presents challenging control problems that, so far, have been approached with classical control techniques. However, large scale systems of interconnected nodes fall within the framework of the emerging field of complex networks. This paper models multi-terminal VSC-HVDC systems as a complex dynamical network, and derives conditions ensuring bounded synchronization of its trajectories for a family of controllers. The obtained results are validated via numerical simulations.

© 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. A large class of three-phase electrical power systems possess symmetry conditions that make it possible to describe their behavior using single-input single-output transfer functions with complex coefficients. In such cases, an extended root locus method can be used to design control laws, even though the actual systems are multi-input multi-output. In this paper, the symmetric conditions for a large class of power systems are analyzed. Then, the root locus method is revisited for systems with complex coeffcients and used for the analysis and control design of power systems. To demonstrate the benefits of the approach, this paper includes two examples: 1) a doubly fed induction machine and 2) a three-phase LCL inverter.

Power devices intended for high-voltage systems must be tested according to international standards, which includes the short-time withstand current test and peak withstand current test. However, these tests require very special facilities which consume huge amounts of electrical power. Therefore, mathematical tools to simulate such tests are highly appealing since they allow reproducing the electromagnetic and thermal behavior of the test object in a fast and economical manner. In this paper, a three-dimensional finite element method (3D-FEM) approach to simulate the transient thermal behavior of substation connectors is presented and validated against experimental data. To this end, a multiphysics 3D-FEM method is proposed, which considers both the connector and the reference power conductors. The transient and steady-state temperature profiles of both the conductors and connector provided by the 3D-FEM method prove its suitability and accuracy as compared to experimental data provided by short-circuit tests conducted in two high-current laboratories. The proposed simulation tool, which was proven to be accurate and realistic, may be particularly useful during the design and optimization phases of substation connectors since it allows anticipating the results of mandatory laboratory tests.

In the last few years, restrictive grid codes have arisen to ensure the performance and stability of electrical networks, which experience a massive integration of renewable energy sources and distributed generation systems that are normally connected to the grid through electronic power converters. In these codes, the injection of positive- and negative-sequence current components becomes necessary for fulfilling, among others, the low-voltage ride-through requirements during balanced and unbalanced grid faults. However, the performance of classical dq current controllers, applied to power converters, under unbalanced grid-voltage conditions is highly deficient, due to the unavoidable appearance of current oscillations. This paper analyzes the performance of the double synchronous reference frame controller and improves its structure by adding a decoupling network for estimating and compensating the undesirable current oscillations. Experimental results will demonstrate the validity of the proposed decoupled DSRF controller.

This paper describes a grid impact analysis of charging electric vehicles (EV) using charging curves with detailed battery modelling. A probabilistic method using Monte Carlo was applied to a typical Spanish distribution grid, also using mobility patterns of Barcelona. To carry out this analysis, firstly, an IEEE test system was adapted to a typical distribution grid configuration; secondly, the EV and its battery types were modeled taking into account the current vehicle market and the battery characteristics; and, finally, the recharge control strategies were taken into account. Once these main features were established, a statistical probabilistic model for the household electrical demand and for the EV charging parameters was determined. Finally, with these probabilistic models, the Monte Carlo analysis was performed within the established scenario in order to study the lines’ and the transformers’ loading levels. The results show that an accurate model for the battery gives a more precise estimation about the impact on the grid. Additionally, mobility patterns have been proved to be some of the most important key aspects for these type of studies.

This paper proposes a simple semi-analytical method for designing coil-systems for homogeneous magnetostatic field generation. The homogeneity of the magnetic field and the average magnitude of the magnetic flux density inside of the volume of interest are the objective functions chosen for the selection of the coil-system geometry (size and location), number of coils and the number of turns of each winding. The spatial distribution of the magnetostatic field is estimated superposing the magnetic induction numerically computed from the analytical expression of the magnetic field generated by each coil, obtained using the Biot-Savart's law and the current filament method. The homogeneous magnetic field is synthesized using an iterative algorithm based on TABU search with geometric constraints, which varies the design parameters of the windings to meet the requirements. The number of turns of each coil and gauge of wire used for the windings is adjusted automatically in order to achieve the target average magnitude of the magnetic induction under the constraints imposed by power consumption. This method was used to design a coil arrangement that can generate up to 10 mT within a volume (0.5 × 0.5 × 1) m with 99% of spatial homogeneity, with square loops of length less than or equal to 1.5 m, and with a power dissipated by Joule effect less than or equal to 1 W per coil. The synthesized magnetic field distribution was validated using Finite Element Method simulation, showing a good correspondence between the objective values and the simulated fields. This method is an alternative to design magnetic field exposure systems over large volumes such as those used in bioelectromagnetics applications.

This paper analyzes the impact of the charge of EVs(Electrical Vehicles) on a power grid. In order to simulate the behavior of the EV charging on the grid a model of its battery has been found (EV’s charging curve). As the way of the EV is charged from the grid affects critically to the voltage levels and to the saturation of the lines two modalities of charge are presented: not-controlled charge and controlled charge. Finally,the simulations have been performed from two points of view:deterministic analysis and probabilistic analysis.

© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works Electric vehicles use 10 to 25 kWh batteries. After their use in cars, these batteries are still in good condition to be used for energy storage in stationary applications and smart grid systems at all stages: generation, transmission, and distribution. However, before their reuse, there are some changes to be made on these batteries, such as those concerning communications. Electric vehicle batteries use a battery management system that controls functionality and safety, transmitting their condition and status, but also containing confidential information. This article studies two strategies to deal with communications difficulties in their second life as storage energy devices.

A new parameters determination method for squirrel-cage induction motors is presented. As a main contribution, the method uses the instantaneous electrical power and the mechanical speed measured in a free acceleration test to estimate the double-cage model parameters. The parameters are estimated from the machine impedance calculated at several points: (1) at speed points where the double-cage effect is significant, i.e., between the zero speed point and the maximum torque point, the machine impedance is evaluated by the instantaneous power method and (2) at speed points where the doublecage effect is not significant, i.e., between the maximum torque point and synchronism, the machine impedance is evaluated by a dynamic model based linear least square method. The proposed method has been applied to obtain the parameters of three motors tested in the laboratory. To check the method accuracy, the steady-state torque- and current-slip curves predicted by the estimated parameters are successfully compared with those measured in the laboratory.

This paper presents a method for squirrel-cage induction motor parameter estimation using a phase-to-phase standstill variable frequency test. The measured resistance and reactance at different frequencies are the data of the minimization error function to be minimized for single- and double-cage model parameters estimation. It is observed that the single-cage model is unable to fit the measured data for frequencies above several tenths of Hertz, whereas the double-cage model fits the measured data accurately in all the frequency ranges (from 0 to 150 Hz). The single- and double-cage estimated parameters are validated by comparison with data from two additional tests: 1) steady-state torque and current measurement test at different speeds; and 2) dynamic free-acceleration test. Again, the agreement between measured and predicted torque (in the first test) and current (in both tests) is satisfactory only for the double-cage model.

This article introduces a hierarchical power control structure for Multi-terminal High Voltage Direct Current (MT-HVDC) systems. The presented hierarchy is similar to the control structure used in classical AC transmission systems and is divided in primary, secondary and tertiary control actions. The voltage control in the MT-HVDC scheme acts in a way similar to the primary control action of generators in AC systems, while the secondary control action is performed by an outer power control loop. The design of the individual controllers and the interaction between these control loops is discussed in detail. Furthermore, the operational characteristics are described and the main operating points are identified. Scenarios including a power reference change and a grid side converter disconnection have been simulated in order to test and verify the proposed method. The main contribution of the paper is the development of a control methodology, providing a separation of the different control actions in different time domains, similar to what is already in use (and therefore known) within traditional power systems. publisher: Elsevier articletitle: Hierarchical power control of multiterminal HVDC grids journaltitle: Electric Power Systems Research articlelink: http://dx.doi.org/10.1016/j.epsr.2014.12.014 content_type: article copyright: Copyright © 2014 Elsevier B.V. All rights reserved. ispartof: Electric Power Systems Research vol:121 pages:207-215 status: published

This article investigates the combined low voltage (LV) and medium voltage (MV) residential grid impact for slow and fast electric vehicle (EV) charging, for an increasing local penetration rate and for different residential slow charging strategies. A realistic case study for a Flemish urban distribution grid is used, for which three residential slow charging strategies are modeled: uncoordinated charging, residential off-peak charging, and EV-based peak shaving. For each slow charging strategy, the EV hosting capacity is determined, with and without the possibility of fast charging, while keeping the grid within its operating limits. The results show that the distribution grid impact is much less sensitive to the presence of fast charging compared to the slow charging strategy. EV-based peak shaving results in the lowest grid impact, allowing for the highest EV hosting capacity. Residential off-peak charging has the highest grid impact, due the load synchronization effect that occurs, resulting in the lowest EV hosting capacity. Therefore, the EV users should be incentivized to charge their EVs in a more grid-friendly manner when the local EV penetration rate becomes significant, as this increases the EV hosting capacity much more than the presence of fast charging decreases it. ispartof: Energies vol:8 issue:3 pages:1760-1783 status: published

AC traction systems are 1x25 or 2x25 kV 50 Hz single-phase, non-linear, time-varying loads that can cause power quality problems. One of the main concerns about these systems is voltage distortion because adjustable speed drives for trains may inject harmonic currents of frequencies below 2 kHz. Since the presence of parallel resonances in the contact feeder section of the traction circuit worsens the scenario, traction system resonance phenomena should be analyzed to prevent problems. Several works address these phenomena but they only draw weak numerical conclusions based on the frequency scan method. This paper studies 1x25 kV traction system resonances at pantograph terminals and provides more effective analytical expressions to locate them and determine the impact of traction system parameters on them. These expressions are validated from several traction systems in the literature.

This work investigates the activity of copper modified Ce0.50Zr0.50O2 (Cu-CZ) based anodes prepared through subsequent impregnation steps into a porous YSZ matrix. The ceria zirconia oxide was reduced at increasing temperatures and the effect of structural changes on anode performance investigated at 973 K under humidified H-2. Performance of all cells increased after one redox cycle due to a decrease of both the anode polarization and the ohmic resistance of the cell. The redox behaviour of Cu-CZ anode was investigated in a symmetrical cell configuration and it was observed that subsequent redox cycles lead to an activation and stabilization of the electrodes. SEM and EIS characterizations showed that this is mainly attributable to a rearrangement of the morphology and microstructure of the CZ oxide at the electrode/electrolyte interface and to an improvement of copper distribution into the porous electrode matrix. It is inferred that the interplay of copper and CZ favours the promotion of anode activity by increasing the number of active sites; moreover it stabilizes the redox behaviour of the electrode. An optimization of electrical and structural properties of Cu-CZ composites was also discussed. (C) 2014 Elsevier B.V. All rights reserved.

Detailed switching models of power electronics devices often lead to long computing times, limiting the size of the system to be simulated. This drawback is especially important when the goal is to implement the model in a real-time simulation platform. An alternative is to use dynamic average models (DAM) for analyzing the dynamic behavior of power electronic devices. This paper presents the development of a DAM for a bidirectional solid-state transformer and its implementation in a real-time simulation platform. Several case studies have been carried out in order to evaluate the behavior of the model under different operating conditions, check its feasibility for power quality improvements and explore the implementation in a real-time simulation platform. (C) 2014 Elsevier B.V. All rights reserved.

Aeronautical ground lighting (AGL) systems provide visual reference to aircraft during airport operations. In AGL systems, constant current regulators feed a series circuit composed of luminaires supplied through transformers. Component modeling is necessary to simulate AGL systems, and thus characterize and predict their behavior. This paper presents an AGL transformer model including transformer core saturation. Moreover, a procedure to estimate transformer model parameters is proposed. Both the model and the estimation method are validated with extensive measurements on more than 20 AGL transformers of different power ratings and trade names.

In this paper, we present a framework to analyze the propagation of measurement errors through the body composition equations. This is done through the equations for body composition assessment (BCA), for single/multifrequency (SF, MF) body impedance analysis (BIA) approaches. We show that it is possible to estimate a priori the error variance on the BCA parameters from the error measurement in the weight, height, and impedance. The theoretical results are validated through the simulation and experimental data coming from the low-cost AFE4300 impedance spectrometer developed by Texas Instruments. This new spectrometer has been calibrated and characterized by performing measurements on phantoms and foot-to-foot body impedance measurements. The influence of the number of measurement frequencies on the accuracy of BCA is also studied for MF-BIA approach. Ultimately, the measurement error framework can be used to evaluate the suitability of an impedance system for BIA.

© IFAC 2014. This work is posted here by permission of IFAC for your personal use. Not for distribution. The original version was published in ifac-papersonline.net In this work, a fault diagnosis methodology termed VisualBlock-Fuzzy Inductive Reasoning, i.e. VisualBlock-FIR, based on fuzzy and pattern recognition approaches is presented and applied to PEM fuel cell power systems. The innovation of this methodology is based on the hybridization of an artificial intelligence methodology that combines fuzzy approaches with well known pattern recognition techniques. To illustrate the potentiality of VisualBlock-FIR, a non-linear fuel cell simulator that has been proposed in the literature is employed. This simulator includes a set of five fault scenarios with some of the most frequent faults in fuel cell systems. The fault detection and identification results obtained for these scenarios are presented in this paper. It is remarkable that the proposed methodology compares favorably to the model-based methodology based on computing residuals while detecting and identifying all the proposed faults much more rapidly. Moreover, the robustness of the hybrid fault diagnosis methodology is also studied, showing good behavior even with a level of noise of 20 dB.

In this paper a new type of hybrid reluctance actuator is presented. This linear hybrid reluctance actuator is a two phase double sided actuator in which the stator is composed by four normalized U cores, each with a coil wrapped around the yoke connecting the two arms of the core or with two coils wound on each of the arms and a permanent magnet placed near the air gap between and in contact with both arms. The mover is comprised of rectangular poles without connecting iron pieces between them but mechanically joined by non-magnetic mounting parts. The magnets are arranged so that their flux is in parallel to the flux created when the coils are energized, both fluxes are added and the total reinforced flux links the stator and the mover. But when no currents flow through the coils no flux crosses the air gap, and the flux of the magnets is closed through the back iron that supports them. An analysis and simulation of the motor using 2 D finite element and MATLAB Simulink is carried out. Finally, a comparison of this type of actuator with respect a linear reluctance stepper motor of the same size is shown.