Many DC energy solutions have emerged as potential candidates to enhance the electrical infrastructure in a localized approach, allowing future expansion in the transportation sector despite the congestion of the utility grid. However, the risk of designing large power converter units as controllable substations in complex networks, such as electric railway systems, has encouraged the sophistication of modeling and testing tools. This paper presents a high-fidelity, real-time model implementation of a controllable substation for DC traction power systems. This representative model is developed to facilitate the testing of different upgrading options to understand and quantify how these changes will affect the system and, more importantly, which features are critical to further increasing the sustainability of the railways. This is applied to a case study of the Dutch railway system in Wierden. It is found that while controllable substations can reduce voltage drops from an average of 400 V to only about 230 V, the benefit they bring in regenerative braking harvesting does not outweigh the investment costs, calling for further investigation of energy storage systems as another potential solution.

The operation of residential energy hubs with multiple energy carriers (electricity, heat, mobility) poses a significant challenge due to different carrier dynamics, hybrid storage coordination and high-dimensional action-spaces. Energy management systems oversee their operation, deciding the set points of the primary control layer. This paper presents a novel 2-stage economic model predictive controller for electrified buildings including physics-based models of the battery degradation and thermal systems. The hierarchical control operates in the Dutch sequential energy markets. In particular common assumptions regarding intra-day markets (auction and continuous-time) are discussed as well as the coupling of the different storage systems. The best control policy it is best to follow continuous time intra-day in the summer and the intra-day auction in the winter. This sequential operation comes at the expense of increased battery degradation. Lastly, under our controller, the realized short-term flexibility of the thermal energy storage is marginal compared to the flexibility delivered by stationary battery pack and electric vehicles with bidirectional charging.

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.

Low-carbon technologies (LCTs) such as Electric vehicles (EVs), heat pumps (HPs), and PV systems increase phase unbalance due to uneven phase distribution. Phase unbalance can lead to overheating, suboptimal capacity utilization, and power losses. This work analyzes the unbalance impact inflicted by the grid integration of PVs, HPs, and EVs under different combinations and penetration levels. The main novelty of this study is the use of different types of real-world distribution grids (rural, suburban, and urban) for the LCT unbalance impact comparison, while simultaneously considering the influence of several unbalance factors; LCT phase connections and grid distributions, the seasonal effect, and the power and consumption levels, the latter of which have been evaluated as mitigation strategies. The results showed that the combined integration of PVs, EVs, and HPs can cause high voltage unbalance, especially in grids with high existing loading. The seasonal effect was the most impactful unbalance factor, intensifying unbalance by the integration of PVs-HPs and PVs-EVs combinations during Winter and Summer, respectively. Furthermore, reductions in the power and consumption levels of the LCTs decreased the unbalance total violation duration in a range between 11% and 25% for all distribution grids. Reducing the LCT consumption levels also decreased the unbalance magnitude, which reached up to 15% for the urban grid under 100% HP and PV penetration. Finally, it was found that consumption duration enhances unbalance, such as the peak power levels, because it increases the simultaneity of technologies operating in different phases.

This study investigates the techno-economic impacts of various pricing policies on a photovoltaic (PV) system combined with battery energy storage (BES) as a single integrated system within a Dutch residential building. With the increasing adoption of PV systems, managing reverse power flow and grid stability becomes crucial. The study evaluates different scenarios, including net metering, feed-in tariffs (FiT) with time-of-use (TOU), RTP pricing, and subsidised BES. Using a multi-objective genetic algorithm, the optimal size and charging/discharging patterns of the PV-BES system were determined. The optimisation simultaneously minimises the Net Present Cost (NPC) and maximises the Self-Consumption Rate (SCR), to determine the PV-BES size that achieves an optimal balance between economic and technical performance. Results indicate that RTP pricing significantly enhances SCR. While the levelised cost of electricity (LCOE) and payback periods (PBP) are initially higher in the RTP pricing scenario, subsidising BES can mitigate these disadvantages. Additionally, incorporating price limit control variables into the energy management system (EMS) optimises the charging/discharging cycles, extending BES lifetimes and potentially increasing future revenues. These findings provide insights for policymakers to balance economic benefits and grid technical requirements through effective PV-BES integration.

Owing to the intermittent characteristics of renewable energy sources (RESs) and the unpredictability of load demand, integrating multiple RESs and energy storage systems (ESSs) has become imperative. Modular Multiport Converters (MMPC) have emerged as a viable solution to meet this need, offering superior performance, efficiency, and reliability compared to multiple SISO DC/DC converters. To this end, this paper presents a comprehensive model of an MMPC, which is bidirectional and capable of operating in both step-up and step-down modes. Following the derivation of the converter model, a robust μ-controller using the D − G − K iterative procedure is designed. This controller addresses the cross-coupling challenges inherent in MIMO systems and effectively overcomes the parametric uncertainties associated with the converter. 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 increasing number of electric vehicles (EVs) means both a challenge and an opportunity for the electric grid. Different charging algorithms have been proposed in the literature to tackle these specific challenges and make use of the potential services that EVs can provide. However, to properly investigate the conflicting objectives, a multi-objective approach is paramount. These algorithms provide a family of solutions instead of just one, so the decision-maker can see the connection and trade-offs between the objectives. This paper proposes a highly customisable multi-objective framework based on an expanded version of the augmented ε-constraint 2 method. Together with a mixed integer linear programming (MILP) formulation, it is used to solve a charging station scheduling problem. An energy management system (EMS) executes the calculated schedules to show the effect on the individual EVs. Numerical simulations based on market and EV data from the Netherlands demonstrate the adaptability and effectiveness of the proposed algorithm.

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.

Highly self-sufficient energy hubs offer a promising solution to mitigate grid congestion in favor of grid operators and to reduce grid fees for the benefit of energy hub operators. Meanwhile, the energy hub's capacity may far exceed the grid connection capacity, creating a weak grid situation. As a result, power quality issues such as voltage fluctuations, frequency deviations, and even instability may occur. In this work, a grid-forming energy storage system (GFM-ESS) is integrated to address these potential problems. A model of the GFM-ESS and energy hub is established based on a 50 kW PV-Hydrogen energy hub demonstrator, where PV-generated power is utilized for green hydrogen production. A trade-off design is proposed to identify the optimal balance between the capacity of the GFM-ESS and the grid connection. The voltage and frequency response at the hub's bus are analyzed to evaluate this trade-off. While experiments with the 50 kW demonstrator are ongoing, simulation results are provided to validate the effectiveness of the proposed design.

Due to the increasing requirement of charging power for electric vehicles, especially heavy-duty electric vehicles (HDEVs), this paper proposes novel matrix converter-based three-phase medium voltage AC (MVAC) grid-connected modular high-power wireless charging systems. The stiff DC-link absent power transfer from low-frequency AC to high-frequency AC is achieved by the full-bridge direct matrix converter (FBDMC). The cascaded FBDMC structure is proposed to achieve the MVAC grid connection. The three-phase coupler is used here to generate the rotating magnetic fields to achieve higher transfer capability and power density. The second and third grid harmonics can be cancelled due to the nature of the FBDMC and three-phase system, which results in significantly less DC-link current ripple compared to single-phase wireless charging systems. Several novel connections between FBDMCs and coils are proposed to provide more flexibility and multiplexity for WPT charging. The topology is verified by the simulation in PLECS and by a down-scale experiment setup.

This article investigates the peak-to-peak output voltage ripple for the four-switch buck+boost (FSBB) converter under four-segment inductor current mode zero-voltage switching (ZVS) modulation strategies in a comprehensive way. Based on the operating mode of the FSBB converter and the relative magnitudes of the output current and inductor current at the switching instants, four distinct cases were analyzed, with corresponding voltage ripple expressions derived for each. The analysis presented in this article provides theoretical guidance for the selection of output capacitor size of the FSBB converter under ZVS modulation strategies. In addition, the introduced analytical method was also used to evaluate and compare the output voltage ripple under three state-of-the-art ZVS modulation schemes. To validate the theoretical analysis, two sets of simulations were conducted. Finally, a laboratory FSBB converter prototype was also built and tested for the validation purpose with an input voltage of 150 V, output voltage of 200 V, and operating power of 1.2 kW.

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.

Electric aircraft represent a promising low-emission alternative to fuel-powered aviation. As the energy source, the battery pack must guarantee key performance metrics such as energy density, power density, lifetime, and safety. Among these, energy density is particularly critical as it directly impacts the range and payload capacity. Additionally, the battery thermal management system (BTMS) of the battery pack is essential to maintain safety, efficiency, and lifetime. Hence, to design a battery pack with improved energy density and optimized thermal and aging performance, a complete electro-thermal-aging (ETA) model at both cell and pack levels is developed to predict pack behavior under operational conditions. Simulations demonstrate that the proposed model achieves an accurate thermal prediction accuracy within 0.87°C during an example all-electric aircraft (AEA) mission profile. Optimization based on the proposed model is conducted, focusing on geometric configurations of the battery pack and coolant flow parameters, including channel wall thickness (L_Al), inlet width (W_cl), cell spacing (D_cell), package wall thickness (L_enc), inlet flow temperature (T_cl,in), and flow velocity (U_cl,in). An optimized liquid-cooled battery module using Samsung 18650-35E cells is designed with [L_Al, W_cl, D_cell, L_enc] = [0.4, 1.6, 20, 0.5]mm, T_cl,in =35°C, and U_cl,in = 0.05ms^-1 during cruise and 0.02ms^-1 during takeoff, climb, and descent. This configuration achieves a maximum temperature of 41.76°C and a maximum cell-to-cell temperature difference of 3.11°C, improving thermal uniformity. The lifetime performance also demonstrates a 5.51% improvement in state-of-health (SOH) after 180 cycles. Based on the module-to-pack structure analysis, the battery pack exhibits energy densities of 227.01Wh kg^-1 gravimetrically and 353.67Wh L^-1 volumetrically. This study facilitates the guideline for compact and lightweight liquid-cooled battery pack design with improved thermal and aging performance for AEA applications.

This paper presents the design and control of 12 kW medium voltage Modular Multilevel Converter (MMC) prototype, providing a general overview on both the component and system levels. A top level functional overview of the sub-module (SM) converter design including features like semiconductor temperature monitoring and protections for over-voltage, overcurrent, and over-temperature to enhance reliability. The paper also offers a comprehensive system overview, utilizing OPALRT as a high-level controller. To demonstrate the effectiveness of the proposed design, a 12-kW, three-phase MMC prototype was constructed, consisting of four full-bridge (FB) SMs in each converter arm. The paper explains communication management and the integration of analog and digital signals between the physical system and the user interface controller. Finally, the system's output under various operating conditions is analyzed and presented.

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.

High-power flexible dc links employ modular multilevel converters (MMC) for compact active power redirection in medium and high voltage grids. During contingencies, such converters may need to provide an enhanced active power capacity to avoid overload in vulnerable grid locations. This paper achieves this target by using the capacitor voltage ripple margin of the MMC submodules (SM) to enhance the dc voltage beyond the rated value. This voltage enhancement enables the enhanced active power capacity of the MMC while maintaining rated electro-thermal stresses on the components. Moreover, dynamically varying the dc side voltage reduces the MMC's circulating current, improving its operating efficiency. Because the average capacitor voltage is controlled to remain constant, the overall stresses and harmonic performance of the enhanced MMC remain the same as in the base case. In this paper, the analytical expressions for the voltage and power enhancement limits are derived, revealing a dependence on the grid-injected reactive power. Furthermore, a controller is designed to achieve stable operation during transient conditions when the power enhancement is carried out. Finally, the enhancement concept is validated using simulations and experiments with a down-scaled laboratory MMC prototype.

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.

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.

The commercialization success of heavy-duty electric vehicles (EVs) is predominantly contingent upon the development of a robust and scalable charging infrastructure. Compared with low-frequency transformers (LFT), modular applications of solid-state transformers (SST) offer a more promising solution for achieving MW-level power scalability in the future. In the DC/DC stage of SSTs, the dual active bridge (DAB) converter is a widely adopted topology. And the optimal modulation plays a crucial role in selecting appropriate switching devices and improving overall efficiency. This paper focuses on the specific case of a 33.3 kW module within the modular charging station for heavyduty EVs, presenting a generalized approach to optimize the current stress of MOSFETs and soft-switching performance. The switching performance of the candidate devices for this case has also been quantitatively discussed and verified to achieve soft switching over a wide load range in PSIM simulation.