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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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

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

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

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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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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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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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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This article proposes an analytic approach to design the typical power factor correction (PFC) control of an electric vehicle (EV) charger to ensure small signal stability in weak grid conditions. Compared to the previous works, the proposed method considers the dynamics of all the control loops, i.e., phase-locked loop (PLL), voltage loop (VL), and current loop (CL). The impacts of key influential parameters on stability are analyzed. Furthermore, the upper limits of the PLL and VL bandwidth to ensure small signal stability are derived. Accordingly, the influences of the CL bandwidth, short circuit ratio (SCR), and the filter inductance on the upper limit of the PLL bandwidth and the VL bandwidth are quantified. Consequently, a design procedure that eliminates the need to model the input impedance for tuning the controller to prevent small signal instability is proposed. Simulations and experiments validate the analysis.@en

Communication-based distributed secondary control is deemed necessary to restore the state of islanding AC microgrids to set points. As its limited global information, the microgrids become vulnerable to cyber-attacks, which by falsifying the communicating singles, like the angular frequency, can disturb the power dispatch in the microgrids or even induce blackout by pushing the microgrids beyond the safe operation area and triggering the protection. To make the microgrids more cyber secure, adaptive resilient control for the secondary frequency regulation is proposed. It assumes that each converter is communicating with its adjacent converters. With the proposed control, the weight of the communication channel being attacked is automatically reduced, and the more the communicating signals are falsified, the further the weight of that communication channel is weakened. The proposed approach does not rely on attack detection and thereby is easy to implement; Besides, it still works when challenged by a combination of multi-attack signals; Moreover, it applies to multiple communication lines getting attacked cases. Finally, the effectiveness and feasibility of the proposed resilient control scheme are validated by both simulations and experimental results.

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This article presents a detailed procedure for deriving the generalized average model (GAM) of a dual active bridge converter. The proposed model incorporates higher orders of harmonic components to increase accuracy. Moreover, the turn ratio of the high-frequency transformer (N_t) is considered for realistic modeling, which removes the conventional assumption of unity turn ratio. A detailed model of the DAB will ensure an accurate control design. Required mathematical expressions are derived and explained thoroughly, with an example showcasing a GAM model of the DAB converter up to the ninth harmonics. Several GAM models using different harmonic orders (first, third, fifth, seventh, and ninth harmonics) are derived and compared to the PLECS simulation model and a real-time simulation of the DAB converter on the PLECS RT-Box-2. Results show that including up to the ninth harmonics in the proposed model of the DAB converter leads to achieving accurate voltage and current amplitudes that are almost identical to the simulation outputs and even better than the experimental results.

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In the production of green hydrogen, electrolyzers draw power from renewable energy sources. In this paper, the design of Solid State Transformer (SST) for large-scale H ₂ electrolyzers is benchmarked. The three most promising topologies are chosen for design and comparison, including Modular Multi-level Converter (MMC) based SST, Modular Multi-level Resonant (MMR) based SST, and Input-Series-Output-Parallel (ISOP) based SST. The distance between converter towers for insulation and maintenance, the insulation system of the transformer, and the cooling system are designed with practical considerations in order to have an accurate estimation of the volume and weight of the SST. Losses in the switches are calculated based on equations, and losses in passive components are calculated based on FEM simulation. The operating frequency for each topology is optimized to minimize loss, weight, and volume. The best of each topology is then compared with each other to identify the most suitable one for large-scale H ₂ electrolyzers.

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This article presents an optimal multivariable control (OMC) strategy for the LCC-LCC compensated wireless power transfer systems. To mitigate reactive power and achieve higher efficiency, the proposed OMC method incorporates dual-side hybrid modulation and primary-side switch-controlled-capacitor (SCC) tuning into the triple-phase-shift (TPS) control. First, the impact of hybrid modulation and SCC tuning on the system characteristics is investigated. The inverter and rectifier zero-voltage-switching (ZVS) conditions are then analyzed to achieve dual-side ZVS with minimal reactive power. Furthermore, a multivariable optimization problem is established based on the power loss analysis. The solution to this problem provides optimal control variables that minimize the overall system loss. Through collaborative modulation and control of the inverter, rectifier, and SCC, the proposed method reduces the rms values of the currents and lowers the turn-off currents for the converters. As a result, this approach improves efficiency in both light- and heavy-load conditions, enabling wide output regulation and full-range efficiency optimization simultaneously. Finally, the proposed method is benchmarked with the existing TPS method. Experimental results demonstrate that the proposed method achieves higher dc-to-dc efficiency in the power range of 0.2-2.2 kW, with a maximum efficiency improvement of up to 6.3%.

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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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This paper presents a hybrid modulation (HM) scheme to facilitate secondary-side control in wireless power transfer (WPT) systems. To achieve broad power regulation in WPT systems, the conventional pulse width modulation (PWM) exhibits a significant efficiency drop under light loads, while the existing pulse density modulations (PDMs) lead to considerable current and voltage ripples. To address this issue, an optimal discrete PDM (D-PDM) is proposed for active rectifier modulation. By symmetrically and uniformly distributing pulses, the proposed optimal D-PDM eliminates even-subharmonics in rectifier input voltage, thereby reducing the current distortions and output voltage ripple while removing the capacitor DC blocking voltages. Moreover, the pulse width regulation is incorporated into the optimal D-PDM, enabling continuous output tuning and further minimizing subharmonics in the voltage. Based on a WPT prototype, the proposed HM is benchmarked with the existing PWM and PDMs. Experimental results show that the proposed HM significantly mitigates current and voltage ripples while facilitating continuous tuning when compared with the existing PDMs. Additionally, when compared to the PWM, the proposed HM demonstrates notable efficiency improvements within the 10%-60% power range, achieving a maximum efficiency enhancement of up to 5.5%.

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Power electronics converters are essential for power generation, transmission, and distribution. The modular multilevel converter (MMC) is highly valued for its versatility, high efficiency, and robust control capabilities. Since MMC is composed of many components, its reliability is crucial for maintaining the availability of electrical power systems. The reliability of the MMC can be evaluated using different methods, such as the military handbook (MIL) and the Mission Profile (MP) methods. By comparing the reliability estimation of the MMC using the MIL and MP methods, this study offers insights into the effectiveness of these approaches. Also, it shows the significant difference in final results between the two applied methods. These findings contribute to the understanding and improvement of the reliability assessment of power electronics converters. Also, the impact of redundancy is scrutinized to make the comparison more thorough.

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This paper presents a control strategy for active power decoupling in a Solid State Transformer (SST) using a cascaded H-bridge (CHB) converter, dual active bridge (DAB) converters, and a high-frequency link (HFL). The strategy balances capacitor voltage and decouples power flow, significantly reducing second harmonic voltage ripple in DC link capacitors and potentially reducing their size.

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The role of power electronics in advancing electrification and sustainability is pivotal. The Modular Multilevel Converter (MMC) is a leading candidate for connecting offshore wind farms to the power grid. However, one of the primary concerns with MMC is its reliability, primarily due to the high number of components, with semiconductors and capacitors being the main sources of failures. This study examines how the modularity and redundancy of the MMC affect its reliability and, consequently, its impact on power system adequacy. Our findings reveal a substantial influence of MMC's modularity and redundancy on power system adequacy. A high level of modularity with no redundancy leads to the worst-case scenario. On the other hand, lower modularity combined with higher redundancy results in the best scenario for power system adequacy. However, it's important to note that lower modularity and higher redundancy come with increased capital costs of MMC, representing a trade-off between reliability and affordability that we explore in this paper.

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