In dual active bridge (DAB) converters, there can be transformer current ringing, especially when the transformer turns ratio is high. It is induced by high dv/dt generated by fast switching as well as the low impedance of the magnetic tank at the high-frequency range. To quantify the influence of the magnetic tank, its impedance model is thoroughly modeled by considering all the parasitic components. It is found that the parasitic capacitors of the magnetics do not equally affect the current ringing, and thereby the critical one is addressed. On top of that, the design guide of the inductor is provided for the mitigation of the current ringing. Additionally, the impact of dv/dt is also studied. The models and analyses are verified on a 2.5-kW DAB prototype.@en

Renewable energy resources are becoming the dominating element in power systems. Along with de-carbonization, they transform power systems into a more distributed, autonomous, bottom-up style one. We speak of Smart Grid and Microgrid when distributed energy resources take over. While being a means to improve technical and financial efficiency, planning, operations, and carbon footprint, it is these new technologies that also introduce new challenges. Reliability is one of them, deserving a new way of describing and assessing system and component reliability. This paper introduces a new reliability framework that covers these new elements in modern power systems. It can be seen that reliability assessment of modern power systems also requires introducing local reliability concepts as well as incorporating different electro-magnetic/mechanical stability issues.@en

This article aims to incorporate the reliability model of power electronic converters into power system reliability analysis. The converter reliability has widely been explored in device- and converter-levels according to physics of failure analysis. However, optimal decision-making for design, planning, operation, and maintenance of power electronic converters require system-level reliability modeling of power electronic-based power systems. Therefore, this article proposes a procedure to evaluate the reliability of power electronic-based power systems from the device-level up to the system-level. Furthermore, the impact of converter failure rates including random chance and wear-out failures on power system performance in different applications such as wind turbine and electronic transmission lines is illustrated. Moreover, because of a high calculation burden raised by the physics of failure analysis for large-scale power electronic systems, this article explores the required accuracy for reliability modeling of converters in different applications. Numerical case studies are provided employing modified versions of the Roy Billinton Test System (RBTS). The analysis shows that the converter failures may affect the overall system performance depending on its application. Therefore, an accurate converter reliability model is, in some cases, required for reliability assessment and management in modern power systems. @en

A Dual Active Bridge (DAB) converter can achieve a wide high-efficiency range when its input and output voltages are equal, assuming a 1:1 turns ratio for its isolation transformer. If its input or output voltage is doubled, efficiency of the DAB will drop significantly, because of the introduction of hard switching and high circulating power. Thus, a new modulation scheme has been proposed, whose main idea is to introduce a voltage offset across the dc blocking capacitor connected in series with the transformer. Operational principle of the proposed modulation has been introduced, before analyzing its soft-switching area and circulating power mathematically. The final modulation scheme is not difficult to implement, but can help the DAB achieve soft switching, low circulating power, and thereby high efficiency, even with its input or output voltage doubled. These features have been verified by experimental results obtained with a 1.2 kW prototype.@en

This paper proposes a new series resonant DC-DC converter with four configurable operation states depending on the input voltage and output voltage levels. It suits well for the DC-DC stage of grid-connected photovoltaic (PV) systems with a wide-input voltage range and different grid voltage levels, i.e., 110/120 V and 220/230/240 V. The proposed converter consists of a dual-bridge structure on the primary side and a configurable half- or full-bridge rectifier on the secondary side. The root-mean-square (RMS) currents are kept low over a fourfold voltage-gain range; The primary-side MOSFETs and secondary-side diodes can achieve zero-voltage switching (ZVS) on and zero-current switching (ZCS) off, respectively. Therefore, the converter can maintain high efficiencies over a wide voltage gain range. A fixed-frequency pulse width modulated (PWM) control scheme is applied to the proposed converter, which makes the gain characteristics independent of the magnetizing inductance and thereby simplifies the design optimization of the resonant tank. The converter topology and operation principle are first described. Then the characteristics, i.e., the dc voltage gain, soft-switching, and RMS currents, are detailed before a performance comparison with conventional resonant topologies is carried out. Furthermore, the design guidelines of the proposed converter are also presented. Finally, the experimental results from a 500-W converter prototype verify feasibility of the proposed converter.@en

Power electronic converters will serve as the fundamental components of modern power systems. However, they may suffer from poorer reliability if not properly designed, consequently affecting the overall performance of power systems. Accordingly, the converter reliability should be taken into account in design and planning of Power Electronic-based Power Systems (PEPSs). Optimal decision-making in planning of PEPSs requires precise reliability modeling in converters from component up to system-level. This paper proposes model-based system-level design and maintenance strategies in PEPSs based on the reliability model of converters. This will yield a reliable and economic planning of PEPSs by proper sizing of converters, cost-effective design of converter components, identifying and strengthening the converter weakest links, as well as optimal maintenance scheduling of converters. Numerical case studies demonstrate the effectiveness of the proposed design and planning strategies for modern power systems.@en

Power electronic converters are one of failure sources in energy systems, and hence drivers of downtime costs in power systems. Different approaches can be employed for converter reliability enhancement including design/control for reliability methods, condition monitoring and fault diagnosis, and maintenance strategies. This paper proposes optimal preventive maintenance strategies based on wear-out failure model of converter components. The proposed approaches employ two different performance measures at converter-level and system-level. The converter-level measures take into account planned and unplanned maintenance times or costs in a single unit or small-scale system. Moreover, the system-level measure considers not only maintenance times, but also energy losses and additional maintenance costs induced by aging of the converter components. The outcome is optimal replacement time of converter and its components, which depends on the employed performance measure. Optimal replacement scheduling is of importance for risk management and decision-making during planning of modern power electronic based power systems. The applicability of the proposed approaches is illustrated by numerical analysis in a photovoltaic system.@en

Microgrids (MGs) are becoming active segments of future power systems. Frequency regulation inislanded MGs is of high importance to guarantee stable and reliable operation under different loading conditions. This paper proposes a decentralized frequency regulation of AC MGs, which relies on the local information. Comparing to the conventional approaches, the proposed scheme does not require a communication system for frequency regulation, resulting in higher reliability and lower costs. Simulation results verify the effectiveness of the proposed frequency control strategy.@en

DC microgrids can be considered as cyber-physical systems (CPSs) and they are vulnerable to cyberattacks. Therefore, it is highly recommended to have effective plans to detect and remove cyberattacks in dc microgrids. This article shows how artificial neural networks can help to detect and mitigate coordinated false data injection attacks (FDIAs) on current measurements as a type of cyberattacks in dc microgrids. FDIAs try to inject the false data into the system to disrupt the control application, which can make the dc microgrid shutdown. The proposed method to mitigate FDIAs is a decentralized approach and it has the capability to estimate the value of the false injected data. In addition, the proposed strategy can remove the FDIAs even for unfair attacks with high domains on all units at the same time. The proposed method is tested on a detailed simulated dc microgrid using the MATLAB/Simulink environment. Finally, real-time simulations by OPAL-RT on the simulated dc microgrid are implemented to evaluate the proposed strategy. @en

Distributed model predictive control (DMPC) has become a focus in the energy management of shipboard power systems due to its capabilities for privacy preservation, robustness, and distributing computing burdens to local processors. DMPC determines control actions in a distributed manner based on the predictions of system statuses. However, the performance of DMPC is affected by inaccurate predictions resulting from uncertain parameters in nominal prediction models. Particularly, these inaccuracies in predicting propulsion loads and solar panel generation powers can lead to power imbalances when implementing the control actions determined by DMPC. To address this challenge, this paper proposed a novel reinforcement learning compensated DMPC (RL-C-DMPC) to distributively compensate for the control actions determined by DMPC baseline control, thereby rectifying the power imbalances caused by uncertain parameters in nominal prediction models. A value-decomposition-network-based training and distributed testing mechanism is designed for our proposed RL-C-DMPC. Furthermore, a method for range selection of compensation rate is specifically proposed for the energy management of shipboard power systems. To validate the effectiveness of our proposed RL-C-DMPC, we conduct a comprehensive case study utilizing real-life voyage data and historical solar power generation data in the area of the voyage to build the environment for training and testing. By comparing power imbalances between DMPC and RL-C-DMPC, our results indicate significant reductions in power imbalances so that frequency stability can be better ensured. Furthermore, via the case study, we also evaluate the communication robustness of RL-C-DMPC.@en

Distributed model predictive control (DMPC) has become a focus in the energy management of shipboard power systems due to its capabilities for privacy preservation, robustness, and distributing computing burdens to local processors. DMPC determines control actions in a distributed manner based on the predictions of system statuses. However, the performance of DMPC is affected by inaccurate predictions resulting from uncertain parameters in nominal prediction models. Particularly, these inaccuracies in predicting propulsion loads and solar panel generation powers can lead to power imbalances when implementing the control actions determined by DMPC. To address this challenge, this paper proposed a novel reinforcement learning compensated DMPC (RL-C-DMPC) to distributively compensate for the control actions determined by DMPC baseline control, thereby rectifying the power imbalances caused by uncertain parameters in nominal prediction models. A value-decomposition-network-based training and distributed testing mechanism is designed for our proposed RL-C-DMPC. Furthermore, a method for range selection of compensation rate is specifically proposed for the energy management of shipboard power systems. To validate the effectiveness of our proposed RL-C-DMPC, we conduct a comprehensive case study utilizing real-life voyage data and historical solar power generation data in the area of the voyage to build the environment for training and testing. By comparing power imbalances between DMPC and RL-C-DMPC, our results indicate significant reductions in power imbalances so that frequency stability can be better ensured. Furthermore, via the case study, we also evaluate the communication robustness of RL-C-DMPC.@en

Distributed model predictive control (DMPC) has become a focus in the energy management of shipboard power systems due to its capabilities for privacy preservation, robustness, and distributing computing burdens to local processors. DMPC determines control actions in a distributed manner based on the predictions of system statuses. However, the performance of DMPC is affected by inaccurate predictions resulting from uncertain parameters in nominal prediction models. Particularly, these inaccuracies in predicting propulsion loads and solar panel generation powers can lead to power imbalances when implementing the control actions determined by DMPC. To address this challenge, this paper proposed a novel reinforcement learning compensated DMPC (RL-C-DMPC) to distributively compensate for the control actions determined by DMPC baseline control, thereby rectifying the power imbalances caused by uncertain parameters in nominal prediction models. A value-decomposition-network-based training and distributed testing mechanism is designed for our proposed RL-C-DMPC. Furthermore, a method for range selection of compensation rate is specifically proposed for the energy management of shipboard power systems. To validate the effectiveness of our proposed RL-C-DMPC, we conduct a comprehensive case study utilizing real-life voyage data and historical solar power generation data in the area of the voyage to build the environment for training and testing. By comparing power imbalances between DMPC and RL-C-DMPC, our results indicate significant reductions in power imbalances so that frequency stability can be better ensured. Furthermore, via the case study, we also evaluate the communication robustness of RL-C-DMPC.@en

Distributed model predictive control (DMPC) has become a focus in the energy management of shipboard power systems due to its capabilities for privacy preservation, robustness, and distributing computing burdens to local processors. DMPC determines control actions in a distributed manner based on the predictions of system statuses. However, the performance of DMPC is affected by inaccurate predictions resulting from uncertain parameters in nominal prediction models. Particularly, these inaccuracies in predicting propulsion loads and solar panel generation powers can lead to power imbalances when implementing the control actions determined by DMPC. To address this challenge, this paper proposed a novel reinforcement learning compensated DMPC (RL-C-DMPC) to distributively compensate for the control actions determined by DMPC baseline control, thereby rectifying the power imbalances caused by uncertain parameters in nominal prediction models. A value-decomposition-network-based training and distributed testing mechanism is designed for our proposed RL-C-DMPC. Furthermore, a method for range selection of compensation rate is specifically proposed for the energy management of shipboard power systems. To validate the effectiveness of our proposed RL-C-DMPC, we conduct a comprehensive case study utilizing real-life voyage data and historical solar power generation data in the area of the voyage to build the environment for training and testing. By comparing power imbalances between DMPC and RL-C-DMPC, our results indicate significant reductions in power imbalances so that frequency stability can be better ensured. Furthermore, via the case study, we also evaluate the communication robustness of RL-C-DMPC.@en

Due to the simplicity and flexibility of the structure of the Second-Order Generalized Integrator based Quadrature Signal Generator (SOGI-QSG), it has been widely used over the past decade for many applications such as frequency estimation, grid synchronization, and harmonic extraction. However, the SOGI-QSG will produce errors when its input signal contains a dc component or harmonic components with unknown frequencies. The accuracy of the signal detection methods using it may hence be compromised. To overcome the drawback, the First-Order System (FOS) concept is first used to illustrate the principle of the SOGI-QSG, based on which, an improved Second-Order SOGI-QSG (SO-SOGI-QSG) is then proposed by referring the relationship of the standard FOS and the second-order system. The proposed SO-SOGI-QSG inherits the simplicity of the SOGI-QSG, while it has much stronger attenuation ability for both low- and high-frequency components. A detailed parameter design procedure for the SO-SOGI-QSG is provided in this paper as well. The effectiveness of the proposed SO-SOGI-QSG is finally validated by experimental results.@en

Due to the simplicity and flexibility of the structure of the Second-Order Generalized Integrator based Quadrature Signal Generator (SOGI-QSG), it has been widely used over the past decade for many applications such as frequency estimation, grid synchronization, and harmonic extraction. However, the SOGI-QSG will produce errors when its input signal contains a dc component or harmonic components with unknown frequencies. The accuracy of the signal detection methods using it may hence be compromised. To overcome the drawback, the First-Order System (FOS) concept is first used to illustrate the principle of the SOGI-QSG, based on which, an improved Second-Order SOGI-QSG (SO-SOGI-QSG) is then proposed by referring the relationship of the standard FOS and the second-order system. The proposed SO-SOGI-QSG inherits the simplicity of the SOGI-QSG, while it has much stronger attenuation ability for both low- and high-frequency components. A detailed parameter design procedure for the SO-SOGI-QSG is provided in this paper as well. The effectiveness of the proposed SO-SOGI-QSG is finally validated by experimental results.@en

At a workshop held on the Aeolian Islands in Sicily during May 2004 a group of academic and industry engineers from all over the world discussed the medium- and long-term future of power electronics and its applications in specific areas. The following main issues were identified and discussed: The demand is not for power electronic solutions but for system integration of electronic power processing. A more multidisciplinary approach is needed. We will witness a proliferation of energy storage in systems. The technology is in place and the improvement in system performance makes it worth while. A large penetration of power electronics into power systems will happen within the next 25-30 years. The main transmission grid will not be affected. The power electronics development will be in distributed generation and in the loads. The success of the integrated starter/generator (ISG), hybrid, or electric cars depends on political decisions more than on technological advances. However, the success of a recent Japanese hybrid car and the cost of oil could trigger the critical momentum for large-scale use of power electronics in automotive applications. We are moving toward standardized power supply building blocks for computers and other applications. The main push is for lower cost, and production technology becomes the important issue. Demands for improved performance in a diversity of applications will stimulate R&D in power electronics in the future. Intelligent control and energy management will come easily. Thermal and passive component integration is equally important and will require attention.@en

At a workshop held on the Aeolian Islands in Sicily during May 2004 a group of academic and industry engineers from all over the world discussed the medium- and long-term future of power electronics and its applications in specific areas. The following main issues were identified and discussed: The demand is not for power electronic solutions but for system integration of electronic power processing. A more multidisciplinary approach is needed. We will witness a proliferation of energy storage in systems. The technology is in place and the improvement in system performance makes it worth while. A large penetration of power electronics into power systems will happen within the next 25-30 years. The main transmission grid will not be affected. The power electronics development will be in distributed generation and in the loads. The success of the integrated starter/generator (ISG), hybrid, or electric cars depends on political decisions more than on technological advances. However, the success of a recent Japanese hybrid car and the cost of oil could trigger the critical momentum for large-scale use of power electronics in automotive applications. We are moving toward standardized power supply building blocks for computers and other applications. The main push is for lower cost, and production technology becomes the important issue. Demands for improved performance in a diversity of applications will stimulate R&D in power electronics in the future. Intelligent control and energy management will come easily. Thermal and passive component integration is equally important and will require attention.@en

This paper proposes an improved analytical stray capacitance model for inductors. It considers the capacitances between the winding and the central limb, side limb, and yoke of the core. The latter two account for a significant proportion of the total capacitance with the increase of the core window utilization factor. The potential of the floating core/shield is derived analytically, which enables the model to apply not only for the grounded core/shield, but also for the floating core/shield cases. On the basis of the improved model, an analytical optimization method for the stray capacitance in inductors is proposed. Moreover, a global Pareto optimization is carried out to identify the tradeoffs between the stray capacitance and ac resistance in the winding design. Finally, the analysis and design are verified by finite element method simulations and experimental results on a 100-kHz dual active bridge converter.@en

This paper proposes an improved analytical stray capacitance model for inductors. It considers the capacitances between the winding and the central limb, side limb, and yoke of the core. The latter two account for a significant proportion of the total capacitance with the increase of the core window utilization factor. The potential of the floating core/shield is derived analytically, which enables the model to apply not only for the grounded core/shield, but also for the floating core/shield cases. On the basis of the improved model, an analytical optimization method for the stray capacitance in inductors is proposed. Moreover, a global Pareto optimization is carried out to identify the tradeoffs between the stray capacitance and ac resistance in the winding design. Finally, the analysis and design are verified by finite element method simulations and experimental results on a 100-kHz dual active bridge converter.@en

This paper proposes an improved analytical turn-on power loss model for 650-V GaN eHEMTs. The static characteristics, i.e., the parasitic capacitances and transconductance, are firstly modeled. Then the turn-on process is divided into multiple stages and analyzed in detail; as results, the time-domain solutions to the drain-source voltage and drain current are obtained. Finally, double-pulse tests are conducted to verify the proposed power loss model. This analytical model enables an accurate and fast switching behavior characterization and power loss prediction.@en