This study proposes a model predictive control (MPC) strategy integrated with closed-loop space vector modulation (CL-SVM) for a three-phase, three-level neutral point clamped (3L-NPC) rectifier supplying two alkaline electrolyzers connected in series. Electrolyzers present a nonlinear and dynamically varying load due to their dependence on temperature, pressure, and electrochemical reaction rates, imposing strict requirements on the stability and responsiveness of the power supply. Among, multi-level converter topologies, the 3L-NPC rectifier is a promising candidate for low to medium-voltage, high power applications due to its reduced harmonic distortion, improved high power handling, and balanced trade-off between complexity and performance. However, maintaining DC-link capacitor voltage balance under dynamic loads remains challenging, risking power quality and system reliability. The proposed approach optimizes voltage vector selection to regulate DC output and minimize neutral-point voltage deviation. Simulation results in MATLAB/Simulink confirm the effectiveness of the designed controller in achieving stable DC voltage and a balanced neutral-point voltage, thereby enhancing the overall performance of the power-electronics interface in electrolyzer applications.

This research presents a neural-adaptive control technique for DC microgrids in renewable hydrogen production systems. The proposed approach tackles voltage stability issues arising from variable solar production and fluctuating electrolyzer loads with an adaptive neural network-based proportional-integral (ANN-PI) controller with online system identification. The control architecture utilizes two concurrent multilayer perceptron (MLP) networks: one for real-time system identification to estimate the Jacobian matrix, and another for adaptive proportional-integral (PI) parameter adjustment. The decentralized architecture removes communication dependencies among converters, hence improving reliability and scalability. Simulation results indicate a better dynamic response with a 50% decrease in settling time, increased voltage stability retaining the DC bus voltage within ±2% of the nominal 400 V, and resilient performance under diverse situations, including load transitions and changes in solar irradiation. The neural-adaptive method effectively facilitates intelligent, model-free regulation for electric-hydrogen DC microgrids.

This study investigates the degradation behavior and reliability of silicon carbide (SiC) MOSFETs under power cycling tests to address their vulnerability to thermo-mechanical stresses. Five 650V SiC MOSFETs (IMW65R107M1H) were subjected to controlled thermal cycles, and key parameters such as body diode voltage, thermal resistance, and junction temperature were monitored. The degradation mechanisms, including bond wire fatigue and gate oxide defects, were identified through abrupt and gradual changes in the body diode voltage. A Weibull distribution was used to model the component lifetime, estimating a B-10 lifetime of 7279 cycles for devices with varying ∆Tjbetween 120 °C and 140 °C. Furthermore, the body diode voltage and gate leakage current were highlighted as effective precursors for early failure detection. This research provides insights into improving SiC MOSFET reliability and lays the groundwork for early warning systems in high-power converter applications.

This study addresses a 1.8kV bilateral feeding system for DC railway applications, composed of multi-pulse diode rectifiers at both ends and a storage unit with a DC/DC converter located at an intermediate station. The storage system introduces an additional degree of freedom to control power flows by applying a specific voltage at a strategic point between the passive rectifiers. This paper formulates a voltage compensation problem aimed at reinforcing the network while minimizing conduction losses along the catenary. Due to the nonlinear nature of the power balance equations, a closed-form analytical solution is not directly obtained. To overcome this, the paper proposes an approximation method for the pantograph voltage to enable an analytical formulation of the optimization problem. A comparison between the proposed analytical approach and a numerical iterative optimization method is presented and discussed.

Consensus algorithm-based secondary control, such as virtual impedance, is typically used to achieve power-sharing and ensure stable operation in microgrids. The introduction of communication, however, increases the system's vulnerability. Communication failure, e.g., under cyber attack or disruption, can lead to a huge loss. To solve this, this article proposes a signal reconstruction approach for the miscommunicated signals. The power-sharing convergence, both in normal conditions and under communication failure, is analyzed via the Lyapunov method. The feasibility and effectiveness of the proposed approach are validated on a lab-scale microgrid.

Distributed secondary control achieves voltage restoration and power sharing through communication among adjacent units but exposes the microgrid to potential cyber-attacks. Traditional mitigation strategies modify the secondary controller after the attack, addressing the issue only postoccurrence. Furthermore, in microgrid planning, the structure of the communication network significantly influences the resilience to attacks, but it remains to be explored. This article presents a proactive defense mechanism by designing a resilient communication network. The proposed method quantifies the impact of attacks and develops a multiobjective optimization algorithm to design the network, considering quantified attacks, convergence, time-delay robustness, and communication costs. The method is validated through OPAL-RT simulations of an islanded microgrid with ten converters.

This paper presents an innovative control strategy to enhance the stability of interconnected Microgrids (MGs) with low inertia and high penetration levels of Renewable Energies (REs). The proposed control strategy encompasses a new virtual droop control mechanism that emulates the primary control of synchronous generators for enhanced system stability. Additionally, a weighted Proportional-Integral (PI) controller is used to mitigate the adverse effects of measurement delays caused by Phase-Locked Loop (PLL) dynamics. Furthermore, a feedback integral loop is introduced to improve the efficiency and lifespan of Vanadium Redox Flow Batteries (VRFBs) enabling swift and precise power delivery while reducing steadystate errors. Finally, a new fractional-order virtual inertia control (VIC) is introduced to leverage the fractional derivatives and enhance the system’s frequency response. The presented simulation results demonstrate the effectiveness of the proposed control approach in improving the frequency response and power exchange dynamics across interconnected MGs under various operating scenarios.

The Dual Active Bridge (DAB) is a popular DC-DC converter for bidirectional power transfer in applications such as the re-emerging technology of flow batteries. For such applications, it is essential to design the DAB for the wide voltage range operation of batteries, specifically focusing on its non-linear characteristics. The existing design methods utilise an optimisation algorithm to minimise the losses of the DAB at various equidistant voltage points in the voltage range. The resulting design is less efficient as it gives too much weight to insignificant operating points. This article proposes a new method that uses the flow battery characteristics to determine the operating points at which minimisation should be performed. The proposed method is validated with simulation results.

This paper proposes a novel sensorless phase-shift modulation-based voltage balancing technique for a 5-level Packed U-Cell (PUC5) inverter. Two phase-shifted triangular carriers are used to modulate the reference signal and generate the appropriate gate pulses. The switching pulse generation is specifically designed to charge and discharge the capacitor at the speed of switching frequency, resulting in a fast voltage balancing of the auxiliary capacitor. Compared with the reported level-shifted modulation method, the proposed technique simplifies comparators and logic gates while keeping the benefit of fast sensorless voltage balancing and, consequently, the capacitor size reduction. In other words, it modifies the reference signal to achieve the fast voltage balancing of the auxiliary capacitor in PUC5. Simulation results are shown to investigate the effectiveness of the proposed technique.

Public electric transport grids tend to be oversized and underutilized. Therefore, they can become sustainable and multi-functional backbones to the city AC grid by integrating smart grid elements into their infrastructures. However, integrating smart grid loads and renewables requires a large array of wirelessly communicating sensors across the traction substations, the smart grid components, and each vehicle of the transport fleet. This can be both costly and technically complex. This paper proposes an analytical state estimator that can predict vehicle traffic count and spare power capacity under a traction substation without the use of any additional sensors. The estimator uses existing, locally available measurements at any power node on the traction section to inform the decision-making of the power management scheme at that node. Validating the results with up to 100000 stochastic test simulations of a verified traction grid model, up to 76% of the monitored conditions were detected, with no false positives, and without the need for additional sensors and wireless communication.

This paper presents a Mix Integer Linear Programming (MILP) optimization approach to reduce peak demand and maximize revenue in a grid-connected building with a PV-equipped charging station for Shared EVs. The study investigates the impact of EV availability on the effectiveness of the system by comparing the results for different connection times of a fleet of Shared EVs, a private EV used for commuting, and a stationary battery. Results from the case study conducted in The Netherlands demonstrate that not only the duration but also the timing of EV connection significantly influence system effectiveness, emphasizing the need for accurate availability estimation. The trade-off between peak reduction and Peak-to-Average Ratio (PAR) reduction is also highlighted, underscoring the importance of considering both factors for optimizing charging station usage. These findings provide valuable insights for optimizing energy management, reducing peak loads, and increasing the utilization of renewable energy sources in the context of Shared EVs and V2G technology.

Power electronics converters (PEC) play a crucial role in interfacing renewable energy systems and electrolyzers to ensure a high production yield of green hydrogen. The design of such PEC is not straightforward due to the safety hazards of using multiple electrolyzer stacks and converter modules at industrial levels. Therefore, real-time simulations should be conducted to ensure the converter design satisfies all the requirements before deploying it on-site. This paper presents a real-time digital twin (RTDT) of a 10 kW dual-active bridge converter interfaced with an electrolyzer. OPAL-RT simulator (eHS toolbox) is used for RTDT. Finally, the voltage across the series inductance and current flowing through it are presented for the open-loop operation of DAB.

Electrolysis requires a high DC current at low voltage to produce hydrogen from water. Designing power converters for such a load requirement could be challenging while fulfilling the galvanic isolation needs. Therefore, prior knowledge of the electrolyzer's impact on the converter operation should be needed. In this context, this paper investigates the behavior of the Dual Active Bridge (DAB) converter when utilized for electrolysis. A MATLAB simulation of DAB with a 10 kW alkaline electrolyzer is developed. Several converter parameters, such as the phase shift angle, series inductance, peak and RMS currents, and voltage gain, are analyzed during electrolysis. Distinct operating behavior is observed from the analysis.

EV fast chargers are essential in addressing the concern of limited driving range for E-mobility applications. However, the load profile of a converter for fast charging involves a high-current pulse that can last for a few minutes to efficiently replenish the EV battery, which is followed by a cooldown period after the charging process is finished. This results in thermal cycles that can lead to thermo-mechanical fatigue and degradation of power electronic components, thereby impacting device lifetime. This paper presents a comparative study on the reliability of power devices in isolated half-bridge and full-bridge DC-DC converters in EV fast chargers. The study focuses on the differences in thermal stresses that Si switches experience in each converter during charging cycles and how it impacts the end-of-life of each device. This study provides valuable insights for selecting reliable power converters for EV fast charging applications.

For electrolyzer applications, traditional solutions using line frequency transformers plus rectifiers are bulky, heavy and have low controllability. The Solid State Transformer (SST) could be a promising solution to solve the mentioned issues. This paper compares the semiconductor ratings and capacitance of five different Modular Multilevel Converter (MMC) based Solid State Transformer (SST) topologies. The results show that the DRU (Diode Rectifier Unit)-MMC based topologies have the lowest semiconductor ratings and capacitance. Because of the unidirectional power flow requirement, the source side MMC of Back-to-Back (BtB) MMC based SST could be replaced by DRU, thus the cost is drastically saved. Another interesting finding is that the DRU-MMC energy ripple is much lower than half of the energy ripple in BtB MMC, which is different from HVDC MMC.

Green hydrogen production uses renewable energies to energise the electrolysers for hydrogen production. The present paper compares possible solutions and configurations of a medium-frequency transformer (MFT) as part of a solid-state transformer (SST) in green hydrogen production applications. The single-phase and three-phase MFTs are compared and it is shown that a Yd three-phase MFT is the optimum choice for applications that require high power delivery and step-down of the voltage. A summary of previous works about MFT is also provided. Three-phase SST based on modular multilevel converters (MMC) is then described and various cases are investigated to obtain the optimum operational frequency. A 25 MVA, 400 Hz, 25.4 kV / 560V oil-immersed MFT design is presented and is shown that the proposed 400 Hz transformer saves 69% of the active parts' weight compared to a conventional line-frequency transformer (LFT).

The reliability of semiconductor power devices can be studied by performing a thermal and power cycling test. In order to create the desired temperature cycles, there are four free variables to select during the power cycling test, namely the heating current, heating time, cooling time, and heatsink temperature. In this paper, the relation between the selected variables and the minimum and maximum junction temperature is extensively tested for the silicon IGBT with serial number IKP06N60T. Furthermore, the thermal model is discussed and verified and a rough estimate of the electrical resistance, thermal time constant, thermal resistance, and thermal capacitance are calculated.

In the context of building electrification the operation of distributed energy resources integrating multiple energy carriers poses a significant challenge. Such an operation calls for an energy management system that decides the set-points of the primary control layer in the best way possible. This is done by fulfilling user requirements, minimizing costs, and balancing local generation with energy storage. This last component is what enables building flexibility. This paper presents a novel aging-aware strategy for operating grid-connected buildings that combine multiple energy carriers (heat and electricity), storage devices (electric vehicles, batteries, and thermal storage), and power sources (solar photovoltaics, solar collectors). The novel energy management algorithm presented considers the aging of the batteries to enhance the operational differences between storage technologies, thus making explicit the trade-off between the services provided by the hybrid energy storage system and its degradation. This unlocks grid cost reductions between 20–45 % depending on the season when compared to state-of-the-art solutions.

It is ideal for the wireless power transfer (WPT) systems to operate at the resonance state for better transmission performance. In practice, however, the parameters of the resonant circuits often deviate because of the capacitance drift and coil misalignment. To this end, this paper proposes a new parameter estimation method for the WPT systems, which is able to facilitate the power flow control and active impedance tuning of the WPT systems under parameter deviations. Distinct from the traditional parameter identification methods, the proposed method is implemented with an short-circuited rectifier, and therefore, the whole estimation process is independent of the load variations. Furthermore, to avoid severe system detuning during the frequency-sweeping process, a dynamic frequency sweeping method is proposed to efficiently and safely extract the data of the primary and secondary coil currents. Based on the extracted data, a mathematical model is established, and the JAYA algorithm is utilized to identify the unknown parameters. Experimental results are presented to verify the estimation accuracy of the proposed method.

Electric vehicle (EV) charging infrastructure will play a critical role in decarbonization during the next decades, energizing a large share of the transportation sector. This will further increase the enabling role of power electronics converters as an energy transition technology in the widespread adoption of clean energy sources and their efficient use. However, this deep transformation comes with challenges, some of which are already unfolding, such as the slow deployment of charging infrastructure and competing charging standards, and others that will have a long-term impact if not addressed timely, such as the reliability of power converters and power system stability due to loss of system inertia, just to name a few. Nevertheless, the inherent transition toward power systems with higher penetration of power electronics and batteries, together with a layer of communications and information technologies, will also bring opportunities for more flexible and intelligent grid integration and services, which could increase the share of renewable energy in the power grid. This work provides an overview of the existing charging infrastructure ecosystem, covering the different charging technologies for different EV classes, their structure, and configurations, including how they can impact the grid in the future.

This paper presents the study of a 100kW electric vehicle (EV) fast charger based on a 12-pulse rectifier cascaded with two buck-type DC-DC converters. The proposed circuit operates with a triangular current shaping method which considerably improves the current harmonics performance of the system. The studied circuit is particularly suited for high power battery charging, being relatively simple to operate, requiring a low active semiconductor count (only two active switches), and because it employs circuit technologies well-established in the high power market. Above all, this EV fast charger meets the requirements of isolation, high efficiency, high output voltage and good power quality (low THD and unity power factor). This paper describes in detail the analytical modeling of the studied circuit, including the current harmonic input filter design which meets the grid standard requirement, and the loss modeling of the semiconductors and passive elements. The modeling and simulation results of the proposed 100 kW system are presented and analyzed.

In emerging fast-charging stations, DC fast chargers (DCFCs) are employed which rely on power electronics and control to achieve the required performance. Harmonic emission induced by the complex system behavior is of great concern in the DCFC system. This paper proposes a harmonic emission model for the typical electric vehicle charger design, i.e., two-level active front end. The technique is based on the Fourier series method and the impedance model which is able to reveal the harmonic current emission of DCFCs under different grid conditions. Time-domain simulations are presented subsequently to validate the proposed model.

The range anxiety and relatively long charging time issues of electric vehicles (EVs) have boosted the development of fast charging technology. With charging light EVs being the main focus in the past decade, a trend of promoting the charging infrastructures dedicated to heavy-duty EVs (HDEVs) such as E-trucks, and Ebuses has emerged to further the electrification of global transportation. Accordingly, the market is calling for advantageous standards, architectures, and power electronic circuits specialized in the fast charging of HDEVs. For the charging of HDEVs, the power rating of chargers can reach an ultra-high-power level (>1 MW) to ensure a charging time comparable to the refueling time of internal combustion engine (ICE) vehicles. At this power rating, the classic full power processing (FPP) two-stage AC-DC plus DC-DC architecture has limited space for improvement in terms of the efficiency and effective cost of the charger circuits. This thesis proposes a solution to the HDEV fast charger topologies. Firstly, the state-of-the-art EV fast charging technology, concepts of the hybrid rectifier, and partial power processing (PPP), which could be beneficial in advancing the charging architecture are reviewed. Based on the results of the literature review, a new unidirectional Input-Parallel-Output-Series (IPOS) three-phase hybrid rectifer topology is proposed and analyzed. This topology is derived from the Input-Parallel-Output-Parallel (IPOP) hybrid rectifier in [1] by connecting the DC-links in series instead of in parallel. The IPOS topology is beneficial at ultrahigh power rating to interface heavy-duty EV batteries which require a high and wide output voltage range, enabling the system to deliver an output voltage range of 800∼1500 V to interface the next-generation of EV batteries with available 600/1200V commercial semiconductors. Besides, the proposed topology is efficient, cost-effective, and scalable with the grid input current harmonic components in compliance with the IEEE-519 standard. The benefits of the IPOS topology are supported by circuit derivation, control strategy, analytical modelling, simulation, and experimental verification of the current modulation technique. Index terms— fast charging, hybrid rectifier, partial power processing, power factor correction, AC–DC converter

Balancing converters are an integral part of a bipolar dc grid. Resonant converter topologies are interesting for power electronics engineers due to their soft switching capabilities. A series resonant converter topology is promising as a balancing converter in a bipolar dc grid. The series resonant converter is usually a non-inverting topology. However, in the balancing converter application, the converter is used as an inverting type, like a buck-boost converter topology. In this paper, the soft switching capabilities of this converter are shown and analyzed for four distinct converter modulation schemes.

This paper offers a complete and verified model of DC trolleybus grids and examines the effect of the common modelling assumptions made in literature by using simulations, as well as bus and substation measurements from the grid of Arnhem, the Netherlands. An equivalent model for the overhead line impedance is offered taking into account the single line impedance, the supply and return lines, and the parallel connections between them. A case study shows that the feeder cables from the substations to the sections can be ignored, but only for certain substation power and feeder-line length ranges. On the other hand, the often-neglected regenerative braking, bus auxiliaries load, bilateral connections, and the exact nominal substation voltage are found to be crucial for the correct modelling of a trolleybus grid.

In inductive power transfer applications, it is possible to ensure high efficiency of the main coils by operating at the optimum load. Since the optimum load depends on the coupling between the main coils, the operation needs to be adapted to match this case at different alignment conditions. This paper proposes a method to keep the optimum load constant by varying the natural resonant frequency of both the primary and secondary circuits of a S-S compensation network. This is possible by changing the value of the compensation capacitors at different alignments. This strategy differs from the ones found in the literature, where the input and the output voltage are changed to always match the optimum load. The proposed concept is proven through circuit simulations of an 11 kW EV battery charging system, and several strategies for the implementation of the variable capacitance are discussed.

Industrial wireless charging systems use standardized coils to guarantee interoperability between different manufacturers. In combination with these coils, the compensation network can still be designed and optimized. This paper explains the step-by-step design of the compensation network for a 7.7 kW wireless charging system (power class WPT2), which is composed of standardized coils. The compensation network must satisfy the output power and voltage requirements, the soft-switching of the inverter, and the limit of voltage and current stress on the components. The S-S compensation network is found to be unfeasible for those coils, and an optimized double-sided LCC compensation network is designed. The 3-phase grid connection is selected despite the 1-phase one because it gives the lowest total conduction losses. Finally, two parallel SiC MOSFETs C3M0075120K are chosen as inverter's switch because of their low conduction losses. This solution can achieve a payback time within a year with respect to the cheapest one.

This paper aims to investigate the radiated magnetic field by 11 kW inductive power transfer (IPT) systems used for the charging of electric vehicles. Two reference designs suggested by SAE J2954 are studied. Both designs are analysed to obtain the coils winding currents, and 3D FEM models are built in COMSOL without considering the car chassis, which constitutes a conservative approach. The magnetic field intensity at specific distances from the IPT coupler are calculated. Finally, the simulation results are compared with the respective magnetic field limits defined in the international standards SAE J2954, IEC 61980-1 and ICNIRP. The results show that the magnetic field radiations at 10 meters points are significantly lower than the limits established in the SAE J2954, while the emissions at 0.9 meters points are only slightly below the limits defined by ICNIRP.

A novel controller design procedure is proposed for a 5-degree-of-freedom (DOF) active magnetic bearing (AMB) system, based on sliding mode control (SMC) and neural network (NN). The SMC is used to achieve high robustness and fast response while the NN can compensate unmodeled uncertainty and external disturbance by on-line tuning algorithm. The proposed controller is compared with the well-tuned PID controller by simulations. The simulation results show the superior performance of the proposed controller.

In this paper, the output impedance of a three-phase inverter based on a dual current control (also called double synchronous reference frame current control) is modelled, which includes: the current loop gain, the control delay, and the Phase-Locked Loop (PLL). The impact of these parameters on the impedance is then analysed by a sensitivity study. The model is derived using transfer matrices and complex transfer functions, and it results in a compact impedance formulation that can be used in harmonic small-signal stability studies and system-wide steady-state harmonic calculations.

As the number of High Voltage Direct Current (HVDC) installations is increasing, there is a growing need for interconnection to create more efficient grids. To tackle the main challenges in HVDC grids, a multiport DC-DC converter, often referred to as DC hub, is considered a solution. This paper provides a thorough review of different DC hub topologies for the interconnection of multiple HVDC lines operating at different voltage levels. A design based on Modular Multilevel Converters (MMC) is chosen due to their inherent advantages and its control operation is described. A DC hub was modelled in Matlab/Simulink and was tested in a case study including the interconnection of three DC lines in symmetric monopolar configuration, operating at different voltage levels. Three DC hub topologies are proposed for the interconnection of the HVDC lines depending on their voltage levels and the operational and protection requirements of the multiterminal HVDC grid.

This paper aims to identify the difference between foreign object (FO) and misalignment in terms of their influence on inductive power transfer (IPT) systems. This is performed through magnetic and equivalent circuit analysis of the mutual inductance, primary input impedance, charging pad terminal impedance and current harmonics. Experiment measurements on an IPT prototype are carried out to verify the analysis. It is found that: the charging pad terminal impedance under FO condition has a more pronounced decrement than that of misalignment; the mutual inductance under FO condition shows negative correlation with frequency, while positive for misalignment; the absolute value of the input impedance is decreased by FO and increased by misalignment; the influence of FO and misalignment on the THD of the input current is minimal. Finally, it is possible to detect FO and distinguish it from misalignment, through the variation of the primary pad terminal inductance, as well as the frequency dependence of the primary input impedance and the mutual inductance.

This work presents a unidirectional three-phase PFC rectifier well-suited for application targeting high efficiency and/or high power density, such as DC-type electric vehicle chargers. Herein, a quasi-single stage AC-DC converter is proposed where a conventional three-phase DELTA-switch voltage source rectifier is cascaded to a PWM interleaved buck-type DC-DC converter by means of a low energy storage DC-link. The characteristics of the presented power electronics, including the principles of operation, modulation strategy, suitable PWM control scheme, and dimensioning equations are described in this paper. The presented circuit is benchmarked against other solutions for a 50 kW power capability battery charger. The results show a superior power efficiency of the proposed system.

In recent years, electrical vehicle (EV) starts showing its unique advantages that the conventional combustion vehicles do not have. Together with the increasing interests on EV, the motor drive with higher efficiency and lighter weight also becomes more attractive. A promising solution is to apply the wide band gap (WBG) components including gallium nitride (GaN) and silicon carbide (SiC) in the motor drive. Thus, the performance of the GaN, SiC and Si based motor drive in this application are compared. Besides, as the current maximum current rating of the GaN and SiC MOSFET is limited and insufficient to satisfy the large phase current in the acceleration and braking process, the inverter topology that adds the parallel MOSFETs in one position is considered. To reduce the time and cost for the development, this paper proposes the modelling of the motor drive, with which the voltage and current stress, power loss, thermal and electromagnetic performance can all be evaluated. The modelling to be introduced consists of the 1-D power loss, simplified thermal modelling of the motor drive and the 3-D modelling of the electromagnetic performance, detailed thermal performance of the motor drive. In the 3-D modelling, to make the heat transfer simulation closer to the realistic, computational fluid dynamic (CFD) is used to evaluated the heat transfer coefficient on the surface with forced air-cooling.

Back-To-Back (B2B) Voltage Source Converter (VSC) with AC-side LCL filters can be adopted for parallel AC-DC distribution links. In this paper, Grid-side Current Control (GCC) for the inner/fast control loops of the front- and backend power electronics are implemented in order to enhance the system performance against grid disturbances. Herein, a notch filter-based GCC scheme with a harmonic rejection control is proposed which is able to deliver attenuation to the LCL filter resonances while suppressing the harmonics in the grid-side currents originated when the AC voltages are distorted. The results obtained in MATLAB/SIMULINK and an experimental prototype show that the studied GCC method can successfully mitigate the influence of grid voltage harmonics, while providing a stable power control for the hybrid AC-DC distribution links.

We present a fine-grained load migration protocol intended for parallel discrete event simulation (PDES) of spatially extended models. Typical models have domains that are fine-grained discretizations of some volume, e.g., a cell, using an irregular three-dimensional mesh, where most events span several voxels. Phenomena of interest in, e.g., cellular biology, are often non-homogeneous and migrate over the simulated domain, making load balancing a crucial part of a successful PDES. Our load migration protocol is local in the sense that it involves only those processors that exchange workload, and does not affect the running parallel simulation. We present a detailed description of the protocol and a thorough proof for its correctness. We combine our protocol with a strategy for deciding when and what load to migrate, which optimizes both for load balancing and inter-processor communication using tunable parameters. Our evaluation shows that the overhead of the load migration protocol is negligible, and that it significantly reduces the number of rollbacks caused by load imbalance. On the other hand, the implementation mechanisms that we added to support fine-grained load balancing incur a significant cost.

This paper presents the design of an energy management system (EMS) capable of forecasting photovoltaic (PV) power production and optimizing power flows between PV system, grid, and battery electric vehicles (BEVs) at the workplace. The aim is to minimize charging cost while reducing energy demand from the grid by increasing PV self-consumption and consequently increasing sustainability of the BEV fleet. The developed EMS consists of two components: An autoregressive integrated moving average model to predict PV power production and a mixed-integer linear programming framework that optimally allocates power to minimize charging cost. The results show that the developed EMS is able to reduce charging cost significantly, while increasing PV self-consumption and reducing energy consumption from the grid. Furthermore, during a case study analogous to one repeatedly considered in the literature, i.e., dynamic purchase tariff and dynamic feed-in tariff, the EMS reduces charging cost by 118.44$\%$and 427.45$\%$in case of one and two charging points, respectively, when compared to an uncontrolled charging policy.

Corrections were made to author information for the paper, “Energy management system with PV power forecast to optimally charge EVs at the workplace,” (van Der Meer, D., et al), IEEE Trans. Ind. Informat., vol. 14, no. 1, pp. 311–320, Jan. 2018.

Increased proliferation of the renewable energy sources (RES) brings more power electronic devices to the power distribution. Modularity on the converter level is one of the key concepts enabling flexibility, scalability and high availability of the new solutions for the distribution networks(e.g. for low voltage DC). To understand the trends and performance tradeoffs it is important to describe and classify different aspects of the modularity concept. This paper presents a comprehensive literature review, classification of modular power electronics and outlook on future research. Different aspects of modularity are identified and described from the perspective of a converter designer, manufacturer and a user. It is illustrated that depending on a combination of different aspects, different modules are selected resulting in different technical challenges. These aspect can be considered as a mapping tool for the functional description and physical realization of the power converter.

Modular design of wind turbine generators is a promising means to increase the generator availability by reducing downtimes, especially for offshore turbines. With such physically modular designs, the structural support for the generator is an important consideration as it needs to overcome the loss of rigidity in the generator yoke. This makes the structural support design of the generator an important criterion when comparing modular topologies. This paper presents a comparison of modular generator topologies, both from an electrical and a structural performance perspective. It concludes that the 6/4 (6 slots in each stator module corresponding to 4 rotor poles) module is promising solution from the standpoint of maintenance, electrical performance, and structural performance.

We present a new efficient approach to the parallelization of discrete event simulators for multicore computers, which is based on exposing and disseminating essential information between processors. We aim specifically at simulation models with a spatial structure, where time intervals between successive events are highly variable and without lower bounds. In Parallel Discrete Event Simulation (PDES), the model is distributed onto parallel processes. A key challenge in PDES is that each process must continuously decide when to pause its local simulation in order to reduce the risk of expensive rollbacks caused by future "delayed"' incoming events from other processes. A process could make such decisions optimally if it would know the timestamps of future incoming events. Unfortunately, this information is often not available in PDES algorithms. We present an approach to designing efficient PDES algorithms, in which an existing natural parallelization of PDES is restructured in order to expose and disseminate more precise information about future incoming events to each LP. We have implemented our approach in a parallel simulator for spatially extended Markovian processes, intended for simulating, e.g., chemical reactions, biological and epidemiological processes. On 32 cores, our implementation exhibits speedup that significantly outweighs the overhead incurred by the refinement. We also show that our resulting simulator is superior in performance to existing simulators for comparable models, achieving for 32 cores an average speedup of 20 relative to an efficient sequential implementation.

This paper addresses one of the main challenges on the way to an offshore transnational multi-terminal dc (MTdc) network: its control and operation. The main objective is to demonstrate the feasibility of using reinforcement learning (RL) techniques to control, in real time, a multi-terminal dc network aimed at integrating offshore wind farms (OWFs). This method of controlling MTdc networks using RL techniques is called Online Distributed Voltage Control (ODVC). The ODVC strategy uses Continuous Action Reinforcement Learning Automata (CARLA) to optimize power flows in real time. To validate the effectiveness of the proposed control method, dynamic simulations are carried out using a MTdc grid model composed of six nodes, interconnecting three offshore wind farms to three European countries. The results obtained demonstrate the advantages of implementing an online distributed voltage control strategy to obtain feasible controlled power flows with low transmission losses. The results obtained demonstrate the feasibility of the proposed method to control, in real time, MTdc networks and that the RL techniques are well-suited for this problem due to their inherent advantages of coping with stochastic environments.

Optimal power flow control remains one of the main challenges to be solved before large multi-terminal dc (MTdc) networks can be successfully developed. This article employs a novel strategy to achieve optimal power flow (OPF) control in MTdc networks for large offshore wind power plants (OWPP). The strategy, called Distributed Voltage Control (DVC), is validated on an experimental low-voltage laboratory setup. The low-voltage dc network is designed to reproduce the behaviour of a high-voltage one. The experimental setup consists of three voltage-source converters connected in a parallel-radial topology with a symmetric monopolar configuration, which is a suitable choice for the initial development of MTdc networks. A large OWPP is emulated using an OPAL-RT real-time simulator. The results obtained showed that the complete system has a very good dynamic response with fast transients lasting less than 100 ms. Furthermore, the DVC strategy controlled the power flow inside the MTdc network with very high precision, as the median deviation was only 0.03 pu. In conclusion, the DVC strategy is well suited to optimally control MTdc networks.

We present a new technique for controlling optimism in Parallel Discrete Event Simulation on multicores. It is designed to be suitable for simulating models, in which the time intervals between successive events between different processes are highly variable, and have no lower bounds. In our technique, called Dynamic Local Time Window Estimates (DLTWE), each processor communicates time estimates of its next inter-processor event to (some of) its neighbors, which use the estimates as bounds for advancement of their local simulation time. We have implemented our technique in a parallel simulator for simulation of spatially extended Markovian processes of interacting entities, which can model chemical reactions, processes from biology, epidemics, and many other applications. Intervals between successive events are exponentially distributed, thus having a significant variance and no lower bound. We show that the DLTWE technique can be tuned to drastically reduce the frequency of rollbacks and enable speedups which is superior to that obtained by other works. We also show that the DLTWE technique significantly improves performance over other existing techniques for optimism control that attempt to predict arrival of inter-process events by statistical techniques.

The Covariance Matrix Adaptation Evolutionary Strategy (CMA-ES) is a well-known, state-of-the-art optimization algorithm for single-objective real-valued problems, especially in black-box settings. Although several extensions of CMA-ES to multi-objective (MO) optimization exist, no extension incorporates a key component of the most robust and general CMA-ES variant: the association of a population with each Gaussian distribution that drives optimization. To achieve this, we use a recently introduced framework for extending population-based algorithms from single- to multi-objective optimization. We compare, using six well-known benchmark problems, the performance of the newly constructed MO-CMA-ES with existing variants and with the estimation of distribution algorithm (EDA) known as iMAMaLGaM, that is also an instance of the framework, extending the single-objective EDA iAMaLGaM to MO. Results underline the advantages of being able to use populations. Because many real-world problems have constraints, we also study the use of four constraint-handling techniques. We find that CMA-ES is typically less robust to these techniques than iAMaLGaM. Moreover, whereas we could verify that a penalty method that was previously used in literature leads to fast convergence, we also find that it has a high risk of finding only nearly, but not entirely, feasible solutions. We therefore propose that other constraint-handling techniques should be preferred in general.

This paper presents an educational experiment designed for enabling students to interact with a domain of great interest - leakage detection and monitoring. Students will create LabVIEW/MATLAB programs and will use already existing applications in order to get familiar with signal processing concepts like Cross Correlation, Time Delay Estimation and Signal Whitening. Their activity is supported by a real experimental installation which simulates a water transportation system with liquid loss. In addition to the educational component, a professional leak detection device (the Correlux P200) is used for experimental results validation. Consequently, the students benefit from understanding how such an instrument works.

Fault protection aspects are very crucial for the realization of multi-terminal dc (MTdc) networks. This paper investigates the impact of power flow control strategies on the response of MTdc networks to a dc fault. The successful ride-through of a dc fault is defined by two factors: first, a fast fault isolation and second, a fast post-fault system recovery. According to these criteria, two control methods are compared: the common Single converter Voltage Control (SVC) method and the Distributed Voltage Control (DVC) strategy. The main difference between the two methods is the number of the converter stations used for the control of the dc voltage in the MTdc network. A five-step methodology is proposed to determine the dc lines critical loading and to assess the system current and voltage response to a pole-to-ground dc fault. The simulated network consists of four voltage-source converters (VSC) radially connected using a bipolar topology with metallic return. The study shows that both control strategies have the same effect on the system's faulty pole operation, provided that the protection design ensures the system post-fault direct voltage controllability. When the DVC strategy is used, the MTdc network has more redundancy, which enables it to resume operation in most dc fault cases, despite having a higher effect on the post-fault operation of the remaining `healthy' pole converters.

This paper presents a modulation strategy for wide voltage output in a bidirectional modular multilevel dc-dc power electronic converter for wave energy extraction using Electro Active Polymer Wave Energy Converters (EAPWECs). The chosen electrical power converter uses a 10 kV, low current bidirectional dc-dc modular multilevel topology with Dual Active Bridges (DABs) as a basis for each module. This paper proposes a modulation method consisting of several variable frequency DAB modulation modes and explains their operating areas and limitations. Through a simulation model it is shown how the control for the multilevel converter is implemented. Finally, loss estimation is performed using the developed loss model, which was previously validated on an experimental setup.

This paper studies grid code compliance of offshore wind farms (OWFs) when connected to a multi-terminal dc network (MTDC) using VSC-HVDC technology. As the wind farms become decoupled from the ac grids via the dc network, the onshore VSC-HVDC terminals are responsible for complying with the grid codes. However, the onshore VSCs are an active part of the MTDC network control. Voltage-source converters can independently control active and reactive power, but only within their rated capability. If reactive power requirements are too strict, it detriments the converter active power capability, influencing the MTDC network operation. The work is divided as follows: at first, the most common grid codes requirements are introduced. Secondly, the capability chart of a VSC-HVDC terminal is analyzed. Afterwards, the operation of VSC-HVDC terminals inside MTDC networks is explained. Lastly, dynamic simulations verify whether VSC-HVDC terminals fulfill the grid codes requirements when inside MTDC networks.

Offshore wind farms with high installed capacities and located further from the shore are starting to be built by northern European countries. Furthermore, it is expected that by 2020, several dozens of large offshore wind farms (LOWFs) will be built in the Baltic, Irish and North seas. These LOWFs will be constituted of a considerable amount of wind turbines (WTs) packed together. Due to shadowing effects between turbines, the power production is reduced, resulting in a decreased wind farm efficiency. Hence, when LOWFs are considered, wake losses reduction is an important optimization goal that needs to be considered. This work presents a clustering approach to optimize the energy production of LOWFs through a genetic algorithm (GA). The method consists of a turbine clustering strategy where the optimal wind farm layout is obtained in different steps. The number of turbines used in each step is increased until all turbine locations have been optimized. The results demonstrate the method effectiveness. A computational time decrease and a reduction of the problem search space are observed when compared to the standard optimization strategy, without jeopardizing the quality of the optimal layouts achieved.

Design of a contactless power transfer system with supercapacitor based primary energy storage for electric vehicle application is described in this paper. The contactless power transfer system which uses inductively coupled coils to transfer power over a large air gap has been developed. Compensation topologies and the operational frequency of power transfer system have been studied in order to obtain maximum efficiency and high power transfer capability. An experimental setup is built using the design considerations so derived and design parameters for such a system is laid out. Finally, a microcontroller charge control mechanism is implemented to operate the system in a safe region and avoid over charging of supercapacitors.

In this paper the Electric Vehicle (EV) charging demand on quick charge replenishment (QCR), by Fast Charging and Battery Switching, based on Dutch travel pattern is modeled and compared. A comparison between the QCR methods based on number of visits to these facilities and the time of service is obtained. The extra number of batteries to be introduced into the battery switching network is calculated. Using queuing theory the required number of charging points/ switching lanes per quick charge replenishment station is estimated. Based on this the potential peak power requirements of the two methods are obtained.

A new generation of mobile electrical power sources is based on the use of Variable Speed - Constant Frequency technology (VSCF). These optimally controlled variable speed technologies and permanent magnet generators can achieve higher efficiency. The constant frequency and voltage must be controlled by power electronics. This paper presents a short review of some problems in the efficiency investigation of power electronics and presents a comparison of EGS concepts versus power electronics to improve power system efficiency. We consider here measurements made and experimental verification of 7 kW EGS. The investigation and experimental verification of efficiency reveal future trends in this area of power sources to achieve the maximum efficiency.

This paper looks at the performance of model of photovoltaic modules. This paper presents the photovoltaic panel model obtained by the identification method on the basis of measured data. The obtained model is applied in an analog-digital simulator that provides an simulations as a functional circuit model with numerical algorithms. The constructed model results from the nonlinear form of Norton model and is further used for the model performance optimization. This approach can be has its advantages, which are discussed in paper. The final model regards the solar radiation and is valid for a particular panel and temperature changes. The final constructed model is experimentally tested both on the level of simulation and the real measurements. The article also contains the analysis of implemented PV panel model errors. These results can be useful in designing of photovoltaic systems with maximum power point tracking.

This work focuses on a design methodology that aids in design and development of complex engineering systems. This design methodology consists of simulation, optimization and decision making. Within this work a framework is presented in which modelling, multi-objective optimization and multi criteria decision making techniques are used to design an engineering system. Due to the complexity of the designed system a three-step design process is suggested. In the first step multi-objective optimization using genetic algorithm is used. In the second step a multi attribute decision making process based on linguistic variables is suggested in order to facilitate the designer to express the preferences. In the last step the fine tuning of selected few variants are performed. This methodology is named as progressive design methodology. The method is applied as a case study to design a permanent magnet brushless DC motor drive and the results are compared with experimental values.