To tackle the potential grid overloading issue induced by excessive Electric Vehicles (EV) charging demand, a Low Voltage (LV) grid congestion management algorithm with three centralised EV charging management schemes is proposed in this study. The developed algorithm integrates grid information and aims at tackling the foreseen congestion issues by operating on the EV charging processes. This is done through linear programming (LP) or iterative calculations. While the first charging scheme aims at managing the congestion by only affecting the elements with the greatest influence on the congestion, the other two aim at ensuring impartiality towards all users and the overall energy transfer to the EVs, respectively. The simulated results are compared in terms of performance criteria such as grid impact, user satisfaction and fulfilment of charging energy demand. Overall, this study shows that the first scheme brings the best results from a grid perspective. On the other hand, the last scheme leads to competitive results from a grid point of view and the best overall results from a user perspective.@en

This paper presents a robust control approach for non-isolated Modular Multiport Converters (MMPC) capable of integrating multiple energy sources and loads. The objective of this robust control approach is to mitigate cross-coupling challenges inherent in MIMO systems and effectively manage the parametric uncertainties associated with the converter as well as input and output disturbances. To achieve this objective, the paper begins with deriving the general nonlinear dynamic equations of an n-level step-up multi-port DC/DC converter (MPDCnLSU). Subsequently, for a case study involving a 3-level step-up multi-port DC/DC converter (SMPDC3LSU) the equations are linearized to obtain the state-space model. Following the derivation of the converter model, a controller comprising two control loops is designed. The outer loop, responsible for regulating the voltage of output ports, is synthesized through a robust μ-optimal method using the D-G-K iterative procedure, while the inner loop, responsible for regulating the current sharing among the parallel modules and generating PWM signals, is stabilized via multiple PI controllers. Finally, hardware-in-the-loop (HIL) test results derived from OPAL-RT 4610, and experimental results from a prototype are used to validate this control approach. The proposed decoupled mixed μ synthesis method ensures robust performance and stability and results in a less conservative controller design for the MPDC3LSU.@en

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.

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The development of lithium-ion batteries has experienced massive progress in recent years. Battery aging models are employed in advanced battery management systems (BMSs) to optimize the use of the battery and prolong its lifetime. However, Li-ion battery cells often experience fluctuations in battery capacity and performance during cycling, which makes capacity prediction more difficult. Moreover, the reason for the capacity regeneration phenomenon occurring after resting periods is not clear yet, as well as the influence of cycling conditions on capacity regeneration. A relationship between this phenomenon to cycling state of charge (SoC) ranges and current rates was investigated in this article on a battery cell with lithium nickel manganese cobalt (NMC) oxide positive electrode. Experimental results show that the capacity increase is a consequence of decreased internal impedance after the resting period. The experiments also showed that a significant power drop and subsequent power regeneration after a resting period occurs only for specific SoC ranges, and applying a resting period after battery cycling can mitigate this power fading process. The semi-empirical model of battery degradation including capacity regeneration is proposed in this article based on physical processes inside of the cell retaining low computational requirements. The acquired results can be utilized in BMSs for more accurate state of health (SoH) estimation and to prolong battery lifetime.

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Quasi-resonant boundary-conduction mode (QR-BCM) and triangular current mode (TCM) have found widespread use in the literature and industry due to their good performance at relatively low complexity. However, additional control challenges occur when these modulations are applied to the four-switch buck-boost (FSBB) converter, due to a discontinuity in switching frequency in multimode operation. This article presents the first closed-loop operation of a variable-frequency, multimode, quasi-resonant BCM control scheme including smooth mode transitions. The proposed control utilizes feed-forward mode transition techniques, based on software interrupt handlers integrated into the digital control scheme. In contrast to most soft-switching schemes in the literature, the proposed digital control does not imperatively rely on high-frequency current measurements but uses dc measurements and high-frequency voltage measurements instead. A 10 kW prototype is developed with which the proposed modulation is compared with three other soft-switching modulation schemes. Our results indicate that the losses of FSBB converter can be reduced by up to 60% using the proposed modulation. Especially at partial powers and high voltages, significant efficiency gains can be achieved.

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Modular Multilevel Converters (MMCs) offer significant advantages in the medium to high-voltage settings. The modular architecture of MMCs allows for redundant submodules (SMs) to improve overall reliability. These redundant SMs can be deployed using various redundancy strategies, such as Load-Sharing Active Redundancy Strategy (LS-ARS), Fixed-Level Active Redundancy Strategy (FL-ARS), and Standby Redundancy Strategy (SRS). The primary contribution of this paper is the introduction of guidelines for applying Monte Carlo Simulation (MCS) and a comprehensive methodology for its application across various redundancy strategies. This enables precise planning of preventive maintenance and estimation of the number of faulty SMs with a specific lifespan in the MMC. More importantly, MCS is applied to estimate the reliability of the MMC applying Mission Profile for SRS and LS-ARS where analytical solutions are unavailable. An analysis of uncertainty and the applicability of MCS is also presented to demonstrate the advantages of MCS over analytical methods. The computational time required for applying MCS across different redundancy strategies and arm levels is also assessed.

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Distributed generation, such as photovoltaics (PVs), and electrification of heating and transportation with heat pumps (HPs) and electric vehicles (EVs) will play a major role in the energy transition. However, these low-carbon technologies (LCTs) do not come without side effects such as voltage violations, power loss increase, component overloading, higher energy consumption, power peaks, and power quality issues, e.g., harmonics and phase unbalance. This work constitutes a review analysis and summary of all the important findings concerning the various grid impact issues that can appear due to the grid integration of these 3 LCTs. The work also encapsulates various research characteristics such as grid topology, seasons, simultaneous operation under various LCT combinations, penetration levels, etc. Moreover, it incorporates a qualitative analysis of the impact level of the most investigated grid issues and quantitative comparisons between the different grid types and LCTs. It has been shown that the combined integration of PVs-EVs and PVs-HPs can result in mitigation effects without extra solutions. Moreover, voltage deviations and unbalance affect more the rural grids while component overloading is more hazardous for suburban grids. Finally, proposed mitigation solutions, such as energy storage, smart charging, etc., are correlated with their respective grid impact issues.

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This article presents a dual-side capacitor tuning and cooperative control strategy for wireless electric vehicle (EV) charging. To improve the efficiency of wireless EV charging across broad output voltages and wide-range load variations, this article introduces a reconfigurable WPT system by incorporating two switch-controlled-capacitors (SCCs) into the double-sided LCC (DLCC) compensation network. Based on the analytical model of the system, optimal capacitor tuning factors are derived to reduce the rms values of the inductor currents and to minimize the turn-off currents across the semiconductors. Furthermore, a dual-side cooperative control strategy is proposed. Through the collaborative control of the inverter, rectifier, and SCCs, the proposed method achieves dual-side optimal zero-voltage-switching (ZVS), wide power regulation, and maximum efficiency tracking simultaneously. Compared with the existing triple-phase-shift (TPS) method, the proposed approach improves the system efficiency across a wide range of dc output voltages and power levels. Experimental results demonstrate that the proposed method achieves a maximum efficiency improvement of up to 1.8% in the boost mode and 1.9% in the buck mode.

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Targeting a climate-neutral maritime sector drives the adoption of the All-Electric Ship (AES). While AESs can utilize both ac and dc Shipboard Power Systems (SPS), a dc system offers advantages in efficiency, power density, and source synchronization. However, the enhanced network complexity of dc grids combined with the high penetration of power electronic devices and harsh environmental conditions can compromise the system's reliability. Therefore, this paper provides an overview of the reliability aspect of dc-SPSs, addressing the power system design, adequacy assessment, and reliability improvement. First, the performance trade-offs associated with the SPS design are examined, revealing how changes in the power system topology and dc bus structure impact the vessel's reliability along with other performance parameters. Second, a hierarchical reliability model framework is proposed for the adequacy assessment of dc-SPSs, considering the reliability from the component level up to the system level. To determine the system-level reliability, multiple probabilistic methods, including simulation and analytical models, are compared using a propulsion subsystem example. Finally, an overview of the reliability improvement strategies is provided, addressing methods at the system, device, and component level. These three topics combined aim to provide guidance in the design of future reliable dc shipboard power systems.

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The energy transition encourages using heat pumps at the residential level, which results in a multi-carrier energy system when combined with PV and battery storage. Optimally controlling such systems has proven challenging. The numerous constraints required, different response times per energy carrier, and the need for forecasting methods also increase the complexity and computational cost. We propose an adaptable energy management system strategy for any system architecture with a reduced number of constraints using genetic algorithms with a discrete-continuous approach for the power setpoints. Using random forest regression, we also created short-term estimation models for the PV generation and electric and thermal demand, with error distributions centred near 0 %. Our results demonstrate that the strategy can solve the power allocation problem in the order of 1 s, including forecasting 60 minutes, minimizing electric costs, and ensuring thermal comfort.@en

The study presents Electric Vehicle (EV) Point-of-View (POV) Vehicle to Grid (V2G) optimisation, where the system knows the trips and energy demand of the EV. This allows it to be less conservative in the departure State of Charge (SoC) of the EV battery. The peak and cost reduction of Vehicle POV optimisation are compared with state-of-the-art Location Point-of-View optimisation, this is, the car can do V2G but it has to depart each location with at least 80% SoC as the next trip energy demand is unknown. A Mix Integer Linear Programming (MILP) V2G optimisation approach is presented to reduce peak demand and total system cost of a fleet of EVs travelling between several residential locations and one common workplace. Simulations were conducted with 26 EVs unevenly distributed between five residential locations and commuters to a common workplace. The results indicate little differences in the reduction of peak demand between both POVs of V2G optimisation. However, the system cost can be further reduced with Vehicle Point-of-View optimization, saving an additional 200 euros annually per household by transporting cheaper energy from workplaces to residential locations.@en

This paper concerns the control problem of the active and harmonic power sharing caused by the mismatched impedance in resistive feeders-dominated microgrids. A distributed model predictive control (DMPC) scheme is suggested to regulate the virtual impedance of each involved unit for power sharing based on the neighbor's state. With the distributed philosophy, the central controller is not required. Moreover, the proposed method benefits resilience to communication failure by designing the communication matrix. Furthermore, it involves propagating information among units in a short period, significantly reducing the communication and computation burden. Finally, the performance of the proposed control scheme is evaluated in terms of its convergence, robustness to communication delay and load variations, resilience to communication failure, and plug-and-play functionality without communication in an inverter-connected system.

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Electric aircraft is a promising alternative to conventional fuel-based aircraft, offering reduced greenhouse gas emissions and enhanced operational efficiency. To ensure seamless operations and optimize energy management, accurate electric aircraft charging demand prediction becomes imperative. This paper presents a study on forecasting the charging demand for future small, short-range electric aircraft. First, battery sizes are determined for various types of small all-electric aircraft and electric vertical takeoff and landing aircraft. Utilizing the electrical circuit model for lithium-ion batteries, this study derives the charging power curve of electric aircraft under the constant current constant voltage charging strategy. Subsequently, charging demand prediction is conducted using the flight schedule of a selected airport, allowing for a realistic assessment of the power requirements for charging electric aircraft. Finally, case studies exploring charging demand under different scenarios are conducted. The results highlight the substantial power demand associated with the charging process, emphasizing the essential infrastructure needs and potential approaches for managing charging power in electric flight.

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The large Electric Vehicle (EV) fleet penetrations can provoke several grid impact issues if no EV smart-charging is implemented. However, many EV smart-charging works assume an accurate prediction of input data, such as the EV driving patterns, which are highly uncertain. This paper addresses the impact and potential management of several uncertainties related to EV smart charging, such as photovoltaic (PV) generation, load demand, arrival state-of-charge (SOC), requested energy, and arrival and departure time of the EVs. The application of different levels of uncertainty budgets is proposed to account for the gradual impact of every uncertainty on smart charging performance. Moreover, potential uncertainty management is investigated with the use of robust optimization (RO) in predictive receding-horizon EV smart charging under the worst-case uncertainty level, and the ''price of robustness"is calculated. The results show that the EV driving uncertainties are more hazardous for the provided charging energy. In contrast, PV generation and load demand uncertainties have a significant impact mostly on the charging cost. Moreover, the price of robustness is very low for EV charging under every uncertainty case.

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Resonant converters are popular in power electronics due to their soft-switching capabilities, which enhance efficiency and prolong component lifetime. Three- phase resonant converters are particularly noteworthy for their higher power density and reduced ripple, making them ideal for demanding applications. A critical aspect of optimizing three-phase LLC resonant converters is the design of a transformer with adequate leakage inductance required for the resonance circuit. This paper compares two distinct transformer designs for such converters: a five-limb shell-type transformer and a symmetrical triangular transformer. Both designs are evaluated in terms of their performance, efficiency, and suitability for integration into the converter architecture. A detailed design procedure using Finite Element Method (FEM) analysis is presented to guide the development of these transformers. The practicality of this approach and its effectiveness are demonstrated through the implementation of a 3.4 kV to 60 V, 50 kVA prototype. This work provides a comparative analysis of transformer designs and introduces a validated methodology for improving the performance of three-phase LLC resonant converters through optimized transformer design.

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Modular multilevel converters are favorable for efficiently operating high-power usages. The required number of components significantly increases when higher modularity is introduced for the given voltage level, thus reducing the system's reliability. This article suggests a mixed redundancy strategy (MRS) that combines the operational concepts using active and spare redundant submodules. It is shown that more than 50% higher B10 lifetime (the point in time when the system has a 90% probability of survival) is achievable as compared to reliability improvement using fixed-level active redundancy strategy, load-sharing active redundancy strategy, and standby redundancy strategy with the same number of redundant submodules. The tradeoff between operational efficiency and investment cost is explored to define the boundary for selecting the MRS over other redundancy strategies with varying dc-link voltages and average converter loading, considering a ten-year payback period and equivalent B10 lifetime. The change in viability boundary for the MRS is established with increasing B10 lifetime and its sensitivity to power electronic component costs and assumed failure rate. The effect of power capacity with a higher switch current rating is evaluated. Also, the Monte Carlo simulation methodology is proposed to evaluate the practicality and effectiveness of the proposed MRS scheme. Finally, the insights of this study are applied to existing literature.

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Converters that produce an isolated dc output from a three-phase mains supply are often required. Moreover, input power factor correction (PFC) functionality is essential. A standard two-stage conception with ac/dc and dc/dc converters may be used. However, a single-stage or quasi-single-stage solution can simplify the circuitry and increase efficiency; therefore, many variants of single-stage converters have been researched and published. This paper introduces a novel quasi-single-stage resonant topology with an integrated transformer. Additionally, an original control structure is proposed. This converter enables full control over the output dc voltage and current. Another benefit of the proposed converter is a relatively low complexity of its power circuit and control compared to other single-stage converters. The operation principle of the power circuit is explained and the control strategy is also analyzed in detail. A description of the integrated transformer together with aspects of the resonant circuit design are presented. A simulation of the entire converter was performed and evaluated. Furthermore, a test-bench prototype was designed and constructed and is outlined in this paper. The test-bench measurement results are provided and compared to the simulation results. Power factor and efficiency measurements in terms of their dependence on the output voltage and current are included.

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This article discusses the various operating modes of a series resonant balancing converter for bipolar dc grids. It is shown that the converter can be operated in both the capacitive and inductive regions with respect to the resonant frequency of the LC tank. Furthermore, concerning the pulse width modulation signals to the switches, the converter can either be operated by controlling the phase shift between the converter half bridge legs or the duty cycle of the half bridges. A qualitative comparison of the different modes proves that a) the phase shift modes have better soft switching capabilities, b) the capacitive phase shift mode can show zero voltage switching at switch turn-on in the whole operating range, c) the losses in case of capacitive phase shift mode shows best performance at low load power, d) the inductive region power modes show lower rms current for the same power flow compared with capacitive region modes which lead to lower losses at higher output power. The simulation and experimental results depict the operation of all the modes. Finally, a prototype is designed to validate all operating modes, demonstrating $>$99% system efficiency at 1.75 kW.@en

The communication network used in distributed sec-ondary control (DSC) for microgrid power and voltage regulation is vulnerable to cyber-attacks. Unlike the predominantly resilient research on secondary control, which tends to employ passive defense strategies, this paper presents a proactive defense mecha-nism to design a resilient network for microgrid secure operation. This proposed method involves preparing the resilient scheme before attacks occur and facilitates timely resilience during an attack. First, novel metrics are introduced to effectively quantify the impact of various cyber attacks. Then, a multiobjective optimization method is applied to design the communication graph considering the quantified attacks, convergence, time-delay robustness, and communication cost. Simulations are performed on a microgrid consisting of 10 inverter units under different scenarios to validate the effectiveness of the proposed methodology.

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The uncontrolled inclusion of renewable energy sources in the distribution network causes severe overvoltages. Simultaneously, electrification strategies, such as heat pumps and electric vehicles, increase the peak demand, causing undervoltages. The combination of both phenomena has proven challenging for distributed system operators who are accountable for power quality and accessibility. System operators address those voltage issues with network reinforcements, but such projects are costly and time-consuming. We identified that the cost and qualified workforce availability are the main challenges of premature grid reinforcement. This paper evaluated peak-shaving and power curtailment at the low voltage distribution level as market-based alternatives to provide flexibility using the business model canvas. We identified the main actors that would benefit from peak-shaving and power curtailment at the residential level, their relationships, and the value proposition's challenges. We proposed a business model where residential prosumers receive compensation for supporting the network to prevent the distribution system from surpassing the projected power flows. Both alternatives offer system operators more control over the power flow to ensure power quality while decreasing costs, as fewer or no premature grid reinforcements might be needed. The business opportunity resources are categorized as technical and regulatory, highlighting the latter as the main challenge for the business model. We discussed two residential prosumer case scenarios for the Dutch context, one with a PV system and one with a PV and a heat pump. Our analysis suggests that the business models are technically possible for peak-shaving and power curtailment with existing technologies for the selected target. However, the former requires more complex activities and is limited to a narrower segment, as it requires prosumers with PV, storage and high-load devices, such as heat pumps.@en