Search Results (345)

This research paper presents Volvo SmartCell, an AC battery technology that integrates modular multilevel converters and battery cells to form a unified system for electric vehicle propulsion and power supply. The research work addresses the broader challenge of reducing driveline cost and complexity by replacing traditional components such as inverters, onboard chargers, centralized DC/DC converters, vehicle control units and many more. SmartCell uses distributed Cluster Boards comprised of H-bridges which are controlled via wireless communication to generate AC voltage, deliver redundant low voltage power, and support cell level protection mechanisms. The prototype testing demonstrates that the system can supply traction power by engaging clusters according to the required voltage depending on motor speed, achieve AC grid charging by synthesizing sinusoidal voltages without a dedicated charger, and provide autonomous DC/DC operation through cluster level voltage regulation. Simulations further indicate that multilevel voltage generation can reduce switching losses and improve electric machine efficiency compared to conventional systems. Additional benefits include active cell balancing, support for mixed cell chemistries, and high redundancy through multiple independent power branches. Challenges remain in wireless bandwidth limitations and cost optimization of Cluster Boards. Ongoing development aims to enhance communication robustness and validate safety for non-isolated grid charging. Full article

In large-scale offshore wind power transmission systems, the offshore converter valves are typically based on the half-bridge Modular Multilevel Converter (MMC) topology. This design leads to considerable weight and high costs, presenting a critical bottleneck for the development of offshore wind power transmission. This paper proposes a hybrid topology consisting of paralleled MMCs connected in series with a Diode Rectifier Unit (DRU) to achieve lightweight offshore converter valves. The parallel configuration enhances the steady-state current-carrying capacity of the valve group to match the DRU valve group, and power balance among the paralleled MMCs is realized through an additional DC current-sharing control loop. A calculation method for the main circuit parameters of this lightweight topology is presented, along with a complete parameter calculation process. A design example based on actual engineering capacity is provided. PSCAD simulation results verify that the electrical quantities during steady-state operation of the hybrid topology are consistent with the designed parameters, confirming the correctness of the proposed parameter calculation method. Full article

The widespread development of medium-voltage and high-voltage direct current transmission systems has highlighted the modular multilevel converter (MMC) as a crucial enabling technology. However, the overall performance and lifetime of the MMC strongly depend on the integrity of its submodules (SMs), making online capacitance condition monitoring a critical requirement. Unlike recent related studies that rely on computationally heavy matrix-based algorithms or “black-box” artificial neural networks requiring massive offline training datasets, this paper proposes a parametric, adaptive linear neuron network. Mapped directly to the physical equations of the MMC, the method simultaneously exploits the arm current, SM switching state, and capacitor voltage to identify online parametric variations caused by aging or harsh conditions. The proposed scheme is fully non-intrusive, requiring no additional hardware sensors or signal injections, thereby reducing implementation complexity. The simulation results obtained in MATLAB/Simulink (vR2024b) demonstrate the method’s fast convergence and a quantified steady-state estimation error within ±1%. Furthermore, the estimator exhibits strong robustness under severe operating conditions, successfully maintaining accuracy during a 20% capacitance reduction, a 100% active power step variation, dc-link voltage fluctuations, measurement noise, grid unbalances, and harmonic perturbations. Full article

The urgency of global sustainability challenges increased policy attention to Education for Sustainable Development (ESD), particularly in relation to Sustainable Development Goal 4.7, which calls for the systematic integration of sustainability competences across education systems. This article examines how organisational and structural approaches to continuous professional development (CPD) can support the institutionalisation of ESD beyond individual teacher training. The article adopts a case-based analytical approach drawing on programme documentation and evaluation data from two initiatives coordinated by the teacher training department of the District Government of Arnsberg in North Rhine-Westphalia, Germany: the Erasmus+ consortium EFFORT-A, which links international mobility with school development processes, and the regional programme WIRkstatt Zukunft, which implements the Whole School Approach through modular training and school-based consultancy. The analysis indicates that multi-level governance, structured networking, leadership engagement, and formal contracting mechanisms are associated with the integration of ESD within school cultures, curricula, and organisational routines. Challenges are identified regarding resource allocation, policy coherence, and the long-term sustainability of project-based formats. The article concludes that sustained ESD implementation requires CPD systems that combine international perspectives with regionally anchored support structures and align individual professional learning with institutional development strategies, offering recommendations for policymakers and educational leaders. Full article

Under extreme fault conditions or during maintenance restarts, DC collection wind farms may experience a total blackout due to protective isolation. Addressing the black-start challenges arising from the unidirectional power flow structure and weak damping characteristics inherent to DC step-up collection wind farms, this paper proposes a sequential black-start control scheme predicated on grid-source coordination. A representative topology and an equivalent black-start model of the DC collection system are established to analyze the start-up mechanism and to design an active voltage build-up strategy with virtual impedance for the grid-side Modular Multilevel Converter (MMC). Meanwhile, generator-side permanent-magnet direct-drive wind turbines exploit their self-excitation capability and optimized pitch control to realize islanded self-bootstrapping and stable rotational speed. In addition, we develop a two-stage soft cut-in strategy that combines open-loop voltage scanning for pre-synchronization with closed-loop constant-current ramping of DC/DC converters, together with control logic for sequentially connecting multiple units to the DC grid. Simulation results show that the proposed approach smoothly restores the system from a zero-energy state to the rated operating point without external power sources, confirming the feasibility of full-farm start-up using the grid-side converter station and unit self-bootstrapping. Full article

Distinct from the traditional Modular Multilevel Converter (MMC) which focuses on fundamental frequency operation, the Static Var and Filter (SVF) within the Multi-Source Line-Commutated Converter (SLCC) system is tasked with the core function of high-frequency harmonic filtering. This paper reveals a unique engineering reliability issue stemming from this functional difference: to satisfy the Nyquist sampling theorem for precise tracking and elimination of high-frequency harmonics, the update frequency of the capacitor voltage balancing algorithm in the SLCC-SVF system is forced to increase significantly. Mathematical modeling and quantitative analysis demonstrate that this strong coupling between harmonic tracking demands and the voltage sorting strategy directly drives an abnormal surge in the average switching frequency (reaching over five times that of the fundamental condition), severely threatening device safety. To address this, an optimized adaptive hybrid modulation strategy is proposed. The system operates under Nearest Level Modulation (NLM) in normal conditions and automatically transitions to Carrier Phase-Shifted PWM (CPS-PWM)—leveraging its closed-loop balancing capability—when switching frequency or junction temperature exceeds safety thresholds. Furthermore, a non-integer frequency ratio optimization theory for low-modulation indices is constructed specifically for SVF conditions to prevent low-frequency oscillations. PLECS simulation results validate the theoretical analysis, showing that the proposed strategy effectively reduces the average switching frequency by approximately 20% under complex harmonic conditions, significantly enhancing thermal stability and operational reliability while guaranteeing filtering performance. Full article

The increasing demand for high-power electric vehicle charging systems with Vehicle-to-Grid (V2G) capability highlights the need for modular, scalable power converters. This paper proposes a hierarchical control strategy for a high-power, multi-port electric vehicle charging station. The system, based on a Series-Parallel Modular Multilevel Converter (SP-MMC) with isolated modules, is managed by a coordinated control strategy that integrates proportional-integral-resonant regulators, nearest-level control with voltage sorting, and single-phase-shifted modulation. The proposed system enables simultaneous, independent regulation of multiple bidirectional, isolated direct current ports while maintaining grid-side power quality and internal variables of the SP-MMC. The proposed control is validated using real-time Model-In-the-Loop (MIL) simulations that include sequential port activation, bidirectional power flow, and charging operation. MIL results demonstrate stable operation with controlled DC-link voltage ripple, accurate per-port current tracking, and near-unity grid power factor under multi-port operation. Full article

Modular multilevel converter (MMC) is widely employed in high-voltage direct current (HVDC) systems for the long-distance renewable energy transmission, where the larger submodule (SM) capacitors significantly increase its size, weight and cost. Conventional capacitor voltage fluctuation suppression methods, such as composite harmonic injection (CHI) strategies, can achieve lightweight MMC. However, these approaches often neglect the dynamic constraints between harmonic injection parameters and their coupled effect on modulation wave, which not only leads to suboptimal global solutions but also increases the risk of system overshoot. Therefore, this paper proposes a comprehensive CHI parameters optimization method to minimize capacitor voltage fluctuations, thereby allowing for a smaller SM capacitor. First, the analytical expression of SM average capacitor voltage is developed, incorporating the injected second-order harmonic circulating current and third-order harmonic voltage. On this basis, an objective function is defined to minimize the sum of the fundamental and second-order harmonic components of the average capacitor voltage, with the harmonic injection parameters and modulation index as optimization variables. Then, these parameters are optimized using a particle swarm optimization (PSO) algorithm, where their constraints are set to prevent modulation wave overshoot and additional power loss. Finally, the optimization method is validated through a ±500 kV, 1500 MW MMC-HVDC system under various power conditions in PSCAD/EMTDC (version 4.6.3). In addition, simulation results demonstrate that the proposed method can achieve a 13.33% greater reduction in SM capacitance value compared to conventional strategies. Full article

When offshore wind power is connected to a grid via Modular multilevel converter-based High Voltage Direct Current (MMC-HVDC), the sending-end alternating current (AC) system is susceptible to asymmetrical faults. These faults lead to overcurrent surges, voltage drops, and second harmonic circulating currents, which seriously threaten the safe operation of the system. To quickly suppress fault current surges, achieve precise control of system variables, and improve fault ride-through capability, this study proposes a collaborative control strategy. This strategy integrates generalized virtual impedance current limiting, positive- and negative-sequence collaborative feedforward control, and model-predictive control-based suppression of arm energy and circulating currents. The positive- and negative-sequence components of the voltage and current are quickly separated by extending and decoupling the decoupled double synchronous reference frame phase-locked loop (DDSRF-PLL). A generalized virtual impedance with low positive-sequence impedance and high negative-sequence impedance was designed to achieve rapid current limiting. Simultaneously, negative-sequence current feedforward compensation and positive-sequence voltage adaptive support are introduced to suppress dynamic fluctuations. Finally, an arm energy and circulating current prediction model based on model predictive control (MPC) is established, and the second harmonic circulating currents are precisely suppressed through rolling optimization. Simulation results based on PSCAD/EMTDC show that the proposed control strategy can effectively suppress the negative-sequence current, significantly improve voltage stability, and greatly reduce the peak fault current. It significantly enhances the fault ride-through capability and operational reliability of offshore wind power MMC-HVDC-connected systems and holds significant potential for engineering applications. Full article

The development of integrated renewable energy and high-density thermal energy storage systems has been fueled by the need for environmentally friendly heating and cooling in buildings. In this paper, MiniStor, a hybrid thermochemical and phase-change material storage system, is presented. It is equipped with a heat pump, advanced electronics-enabled control, photovoltaic–thermal panels, and flat-plate solar collectors. To optimize energy flows, regulate charging and discharging cycles, and maintain operational stability under fluctuating solar irradiance and building loads, the system utilizes state-of-the-art power electronics, variable-frequency drives and modular multi-level converters. The hybrid storage is safely, reliably, and efficiently integrated with building HVAC requirements owing to a multi-layer control architecture that is implemented via Internet of Things and SCADA platforms that allow for real-time monitoring, predictive operation, and fault detection. Data from the MiniStor prototype demonstrate effective thermal–electrical coordination, controlled energy consumption, and high responsiveness to dynamic environmental and demand conditions. The findings highlight the vital role that digital control, modern electronics, and Internet of Things-enabled supervision play in connecting small, high-density thermal storage and renewable energy generation. This strategy demonstrates the promise of electronics-driven integration for next-generation renewable energy solutions and provides a scalable route toward intelligent, robust, and effective building energy systems. Full article

Wearable multi-modal body fluid monitoring enables continuous, non-invasive, and context-aware assessment of human physiology. By integrating biochemical and physical information across multiple modalities, wearable systems overcome the limitations of single-marker sensing and provide a more holistic view of dynamic health states. This review offers a system-level overview of recent advances in multi-modal body fluid monitoring, structured into three hierarchical dimensions. We first examine sensing-combination strategies such as multi-marker analysis within single fluids, coupling biochemical signals with bioelectrical, mechanical, or thermal parameters, and emerging multi-fluid acquisition to improve analytical accuracy and physiological relevance. Next, we discuss platform-integration mechanisms based on biochemical, physical, and hybrid sensing principles, along with monolithic and modular architectures enabled by flexible electronics, microfluidics, microneedles, and smart textiles. Finally, the data-processing patterns are analyzed, involving cross-modal calibration, machine learning inference, and multi-level data fusion to enhance data reliability and support personalized and predictive healthcare. Beyond summarizing technical advances, this review establishes a comprehensive framework that moves beyond isolated signal acquisition or simple metric aggregation toward holistic physiological interpretation. It guides the development of next-generation wearable multi-modal body fluid monitoring systems that overcome the challenges of high integration, miniaturization, and personalized medical applications. Full article

The development of high-performance DC circuit breakers (DCCBs) and rapid fault detection schemes is a crucial and challenging part of advancing Modular Multilevel Converter (MMC) HVDC grids. This paper introduces a new current-limiting DCCB that uses the differential discharge times of shunt capacitors to generate artificial current zero-crossings, thus facilitating arc quenching. This mechanism significantly reduces the effect of fault currents on the MMC. The shunt capacitors and arresters in the proposed breaker also offer voltage support during faults, effectively stopping transient traveling waves from spreading to nearby non-fault lines. This feature creates an effective line protection boundary in multi-terminal HVDC systems. Additionally, a fast fault detection scheme with primary and backup protection is proposed. A four-terminal MMC-HVDC (±500 kV) simulation model is built in PSCAD/EMTDC to validate the scheme. The results demonstrate the excellent fault detection performance of the proposed method. The voltage and current behavior during the interruption process of the new DCCB is also analyzed and compared with that of a hybrid DCCB. Full article

Grid-forming (GFM) converters are promising for renewable energy integration, but their overcurrent limitation during grid faults remains a critical challenge. Existing overcurrent-limiting strategies were primarily developed for two-level converters and are often inadequate for Modular Multilevel Converters (MMCs). By overlooking the MMC’s unique topology and internal physical constraints, these conventional methods compromise both operational safety and grid support capabilities. Thus, this paper proposes a dynamic asymmetric overcurrent-limiting strategy for grid-forming MMCs that considers multiple physical constraints. The proposed strategy establishes a dynamic asymmetric overcurrent boundary based on three core physical constraints: capacitor voltage ripple, capacitor voltage peak, and the modulation signal. This boundary accurately defines the converter’s true safe operating area under arbitrary operating conditions. To address the complexity of the boundary’s analytical form for real-time application, an offline-trained neural network is introduced as a high-precision function approximator to efficiently and accurately reproduce this dynamic asymmetric boundary. The effectiveness of the proposed strategy is verified by hardware-in-the-loop experiments. Experimental results demonstrate that the proposed strategy reduces the capacitor voltage ripple by 30.7% and maintains the modulation signal safely within the linear range, significantly enhancing both system safety and fault ride-through performance. Full article

This paper proposes a dual−loop model predictive control (MPC) scheme based on grid−side current for modular multilevel converter−based high−voltage direct current (MMC−HVDC) systems. The proposed hybrid control structure combines an MPC−based inner current loop with a PI−based outer voltage loop, designed to enhance dynamic response and steady−state accuracy in HVDC transmission. With the advancement of flexible HVDC technology, modular multilevel converters (MMCs) have been widely adopted due to their excellent scalability and operational flexibility. Model predictive control (MPC), as an advanced control strategy, has demonstrated significant advantages in MMC−HVDC applications. In this study, a dual−loop control system is designed, with MPC as the inner current loop and PI control as the outer voltage loop. This structure effectively enhances control accuracy and ensures system reliability. To validate the effectiveness of the proposed control strategy, a 1000 MW wind power integration MMC−HVDC simulation model was built in Simulink. Simulation results show that the proposed dual−loop MPC strategy can significantly improve control precision and maintain the reliability of the MMC−HVDC system. The proposed strategy is validated through detailed simulations of a 1000 MW wind−integrated MMC−HVDC system, demonstrating superior performance over conventional PI control in terms of overshoot reduction and disturbance rejection. Full article

The integration of large-scale offshore wind power, facilitated by Flexible Fractional Frequency Transmission Systems (FFFTS), presents significant challenges for traditional transmission line protection. The fault current fed by the Modular Multilevel Matrix Converter (M3C) exhibits weak-infeed and controlled characteristics during faults, severely degrading the sensitivity of conventional current differential protection. Moreover, the stringent synchronization requirement for data from both line ends further compromises reliability. To address this issue, this paper proposes a novel differential protection scheme based on the Dynamic Time Warping (DTW) algorithm. The method leverages the DTW algorithm to quantify and compare the variation trends of current waveforms on both sides of the line before and after a fault. By utilizing the pre-fault current as a reference sequence, the scheme constructs a protection criterion that is inherently insensitive to synchronization errors. A key innovation is its capability for fault identification and phase selection under weak synchronization conditions. Simulation results demonstrate that the proposed scheme operates correctly within 0.5 ms, exhibits high sensitivity with a DTW ratio significantly greater than 2.0 during internal faults, and remains stable during external faults. It also shows strong robustness against high transition resistance, noise interference, and current transformer sampling errors. Full article