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Bipolar gradual resistive switching was investigated in ITO/InGaZnO/ITO resistive switching devices. Controlled intrinsic oxygen vacancy formation inside the switching layer enabled the establishment of a stable multilevel memory state, allowing for RESET voltage control and non-degradable data endurance. The ITO/InGaZnO interface governs the migration of oxygen ions and redox reactions within the switching layer. Voltage–stress-induced electron trapping and oxygen vacancy formation were observed before conductive filament electroforming. This device mimicked biological synapses, demonstrating short- and long-term potentiation and depression through electrical pulse sequences. Modulation of post-synaptic currents and pulse frequency-dependent short-term potentiation were successfully emulated in the InGaZnO-based artificial synapse. The ITO/InGaZnO/ITO memristor exhibited spike–amplitude-dependent plasticity, spike–rate-dependent plasticity, and potentiation–depression synaptic learning with low energy consumption, making it a promising candidate for large-scale integration. [ABSTRACT FROM AUTHOR]

Reliability and packing density concerns are the two major shortcomings of spin transfer torque and spin orbit torque based magnetic memory, respectively. Voltage controlled magnetic anisotropy (VCMA) becomes energy efficient and fast, showing transcendence for the writing mechanism in the magnetic tunnel junction. Deterministic switching cannot be achieved by VCMA alone in the out of plane nanomagnet. It requires an external in-plane magnetic field, but the use of an external field is inconvenient for on-chip applications. We exploit stress and exchange bias provided by an antiferromagnetic material to mitigate the external magnetic field requisite. We perform macro-spin simulations using the Landau–Lifshitz–Gilbert equation at room temperature. We use the VCMA effect cum stress effect to investigate field free switching performance, and this improves the write error rate (WER) to 5 × 10 − 5 against WER of 0.1 with the VCMA effect alone. We studied the effects of applied voltage (amplitude and pulse width), exchange bias field, and VCMA coefficient on the switching performance in detail. This proposed two-terminal device can be helpful in achieving high cell density to implement nonvolatile magnetic memory. [ABSTRACT FROM AUTHOR]

To enhance the dynamic performance and robustness of the voltage control system of islanded microgrid inverters, a new control strategy combining integral sliding mode (ISM) control and composite nonlinear feedback (CNF) control is proposed. In ISM control, firstly, a new reaching law is designed to improve movement quality in the reaching phase by improving the power term and introducing the inverse tangent function. Then, to improve disturbance observation accuracy, a variable gain extended state observer is designed by improving the regulation mechanism of the state variables according to deviation control. Using the idea of variable damping, linear and nonlinear feedback are combined into CNF control. Specifically, linear feedback provides a small damping ratio for faster system response, while nonlinear feedback increases the damping ratio to improve steady‐state performance. Simulation results show that the integral sliding mode‐composite nonlinear feedback (ISM‐CNF) control strategy cam balances convergence speed and chattering better and achieves higher steady‐state accuracy than conventional strategies. Moreover, ISM‐CNF control has better robustness to reference voltage variations and disturbances caused by sudden load changes. Therefore, the ISM‐CNF control strategy can accomplish voltage control of islanded microgrid inverters quickly and steadily, effectively suppressing system disturbances and enhancing stability and power quality. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

This paper proposes novel multi-energy inertia support for simultaneous frequency and voltage control of an isolated hybrid power system (IHPS). Multi-energy storage (gas inertia – hydrogen storage, thermal inertia – solar thermal storage, hydro inertia – gravity hydro storage, chemical inertia – battery energy storage) supported by demand side management (DSM) for simultaneous voltage and frequency regulation and backed by biodiesel generators, are the essential elements of IHPS. A novel control strategy of concurrent virtual droop control, virtual damping control, virtual inertia control, and virtual negative inertia control is proposed to utilise multiple inertia sources and to improve LFC and AVR performance effectively. The effective coordination of inertia sources in eradicating oscillations in IHPS, is aided by a developed cascaded proportional integral-tilt-integral-sliding mode (PI-TISMC) controller. The performance of PI-TISMC is compared with PID, PI-PID, and PI-SMC controllers. A maiden attempt has been done by training five diverse classes of optimization techniques to optimize the parameters of controllers in the present work. The results are evaluated in MATLAB and it is evident from the results that the performance of frequency control is improved by 6.5%, 7.8% and 3.4 s (over shoot, undershoot, and settling time). The performance of frequency control is improved by 6.5%, 7.8% and 3.4 s (over shoot, undershoot, and settling time). Similarly, the performance of voltage control is improved by 6.7%, 4.8% and 2.3 s (over shoot, undershoot, and settling time) by employing developed PI-TISMC controller and proposed concurrent inertia control. The combination exhibits superior performance in minimizing oscillations in IHPS due to variations in loading and solar insolation. [ABSTRACT FROM AUTHOR]

Due to the use of multi winding high-frequency isolation transformers in the three port isolated bidirectional DC–DC converter to achieve port isolation and power transmission, there is a power coupling problem between each port. This article proposes a Model Prediction Control (MPC) strategy to address this issue. Considering the control objectives for each port of the Triple Active Bridge (TAB) DC–DC converter, a discrete predictive model of the TAB converter is established based on phase-shifting modulation and average model. The MPC problem is solved optimally and a predictive controller is designed with control accuracy to achieve decoupling control effect between each port. And the traditional single voltage closed-loop control, diagonal matrix decoupling control, and model predictive control proposed in this paper are compared through simulation. Finally, a TAB converter experimental platform is built based on the DSP control chip TMS320F28335. The experimental results are verified the effectiveness and superiority of the proposed method, as well as its faster dynamic characteristics and power decoupling ability between each port. [ABSTRACT FROM AUTHOR]

The stability and reliability of modern power systems, especially those with several renewable energy sources, strongly rely on load frequency control (LFC) and automatic voltage regulation (AVR) for frequency and voltage control under inconstant load demands. In this study, a new cascade tilt integral derivative-fractional order proportional tilt integral derivative (TID-FOPTID) controller is presented that is polished through the salp swarm algorithm (SSA) for LFC of a multi-area power system with AVR in all control areas. The system integrates capacitive energy storage (CES) and deals with governor dead-band and generation rate constraint nonlinear effects in a thermal-hydro-gas three-area multi-source power system (TAMSPS). The analysis of results, due to the SSA-based TID-FOPTID controller compared to TID-FOTID and TID-FOTID + 1 shows a positive outcome. Integrating CES brings additional improvement in the system performance, the overshoot/undershoot, and settling time are minimized. Finally, the sensitivity analysis reveals that the suggested controller will be effective and reliable for enhancing the frequency stability of the complex power system with a high RES integration level. [ABSTRACT FROM AUTHOR]

Finite control set model predictive control (FCS‐MPC) has been widely used in the control of three‐phase voltage source converter (VSC), but its control performance declines sharply at low sampling frequencies. This paper proposes an optimal control set expansion method with slip window selection and online parameter modification to improve the performance and robustness of FCS‐MPC. First, the performance of different control set expansion methods is compared. Then, an optimal control set expansion method that carries 12 virtual vectors is proposed. Last, a slip window selection strategy and an online parameter modification algorithm are proposed to reduce the computational burden and improve the controller's robustness respectively. Experimental result show that the proposed method significantly improves the control accuracy and carries good robustness and anti‐disturbance ability. Compared with existing typical MPC strategies, the proposed method obtains better current quality with lower switching frequency and requires less calculation. Moreover, the design of the proposed method is simple and there is no weighting factor to be tuned, which increases the method's practicality. [ABSTRACT FROM AUTHOR]

The active power control of photovoltaic (PV) inverters without energy storage can flatten the fluctuating power and support the voltage amplitude and frequency of the grid. When operated in grid‐forming voltage‐control mode, because the PV power can change rapidly and widely, the PV inverter needs to track the power commands quickly and precisely. Traditionally, this goal is achieved with the estimation of PV power curve or PI‐based multiple‐loop feedback control, where flexibility, availability and accuracy are not satisfactory. Therefore, a CC/VC‐based power tracking (CVPT) method is proposed, which only uses single‐loop in control. The proposed method does not need to tune multiple loops and can respond faster, which is important for grid‐forming voltage control. Furthermore, the different operating modes due to the limitation of PV maximum power are analysed, and a mode switch method is proposed. Simulation and experimental results demonstrate that the PV inverter can cope with power disturbances from both the power and grid sides and maintain the quality of grid voltage. [ABSTRACT FROM AUTHOR]

In the construction of new power systems, the traditional network security protection mainly based on boundary protection belongs to static defense and still relies mainly on manual processing in vulnerability repair, threat response, etc. It is difficult to adapt to the security protection needs in large-scale distributed new energy, third-party aggregation platforms, and flexible interaction scenarios with power grid enterprise systems. It is necessary to conduct research on dynamic security protection models for IoT and other Blockchain-based IoT architectures. This article proposes a network security comprehensive protection model P2AEDR based on different interaction modes of cloud–edge interaction and cloud–cloud interaction. Through continuous trust evaluation, dynamic access control, and other technologies, it strengthens the internal defense capabilities of power grid business, shifting from static protection as the core mode to a real-time intelligent perception and automated response mode, and ultimately achieving the goal of dynamic defense, meeting the security protection needs of large-scale controlled terminal access and third-party aggregation platforms. Meanwhile, this article proposes a dynamic trust evaluation algorithm based on deep learning, which protects the secure access and use of various resources in a more refined learning approach based on the interaction information monitored in the system. Through experimental verification of the dynamic trust evaluation algorithm, it is shown that the proposed model has good trust evaluation performance. Therefore, this research is beneficial for trustworthy Power IoT and other Blockchain-based IoT architectures. [ABSTRACT FROM AUTHOR]

This article presents the measurement verification of a novel strategy for inrush current reduction in an unloaded three-phase Dy transformer. The strategy combines appropriate pre-magnetization of transformer cores with an original control switching system using initial phase values of the supply voltage as control variables. Measurements were recorded for primary voltages and currents as well as secondary voltages during transient states at start-up under no-load conditions. Various inrush scenarios were examined across the full angular spectrum of initial phase angles, both polarities, and in regard to different pre-magnetization current values. A detailed analysis of the inrush currents was performed using proprietary automated software based on the recorded data. A comparative study with a nonlinear mathematical model of the transformer was also conducted. Additionally, key technical aspects of the designed system for implementing the proposed pre-magnetization strategy with controlled voltage energization are discussed. [ABSTRACT FROM AUTHOR]

The increasing number of distributed generators (DGs) leads to the frequent occurrence of voltage violations in distribution networks. The soft open point (SOP) can adjust the transmission power between feeders, leading to the evolution of traditional distribution networks into flexible distribution networks (FDN). The problem of voltage violations can be effectively tackled with the flexible control of SOPs. However, the centralized control method for SOP may make it difficult to achieve real-time control due to the limitations of communication. In this paper, a distributed voltage control method is proposed for FDN with SOPs based on the multi-agent deep reinforcement learning (MADRL) method. Firstly, a distributed voltage control framework is proposed, in which the updating algorithm of the intelligent agent of MADRL is expounded considering experience sharing. Then, a Markov decision process for multi-area SOP coordinated voltage control is proposed, where the control areas are divided based on electrical distance. Finally, an IEEE 33-node test system and a practical system in Taiwan are used to verify the effectiveness of the proposed method. It shows that the proposed multi-area SOP coordinated control method can achieve real-time control while ensuring a better control effect. [ABSTRACT FROM AUTHOR]

This paper presents a fuzzy sliding mode control method for voltage control of islanded AC/DC hybrid microgrid. The T‐S fuzzy model is utilized to approximate initial non‐linear dynamic model of the microgrid. The fuzzy rules and membership functions are designed according to the coupling relationship between AC part and DC part. To reduce the influence of external disturbance and cyber‐attacks, an integral sliding mode controller is considered. Furthermore, a sufficient condition is proposed with H∞${H}_\infty $ attenuation performance to ensure the asymptotic stability of sliding motion. The set of gain matrices can be acquired via solving the linear matrix inequalities deduced from the Lyapunov stability analysis. The reachability to the proposed sliding mode surface can be guaranteed via switching control law based on a Lyapunov function. In addition, to eliminate chattering performance of the sliding mode control theory, the fuzzy logic controller is designed to optimize the switching region in boundary layers of saturation functions. Finally, the simulation results for the islanded AC/DC hybrid microgrid are implemented to verify the robustness and effectiveness of the designed fuzzy sliding mode control method. [ABSTRACT FROM AUTHOR]

In this paper, a single-phase five-level active neutral-point-clamped with coupled inductors (ANPC-CI) rectifier topology is studied to meet the needs of efficient and reliable power electronic converters. A sliding mode model predictive power control method is proposed to achieve high-efficiency energy conversion, precise voltage control, and low harmonic distortion. By analyzing the working states, establishing a mathematical model and introducing the theory of instantaneous power, the outer loop sliding mode power control and the inner loop model predictive power control algorithms are designed. When compared with traditional PI-DPC algorithm, this algorithm avoids the tedious setting of parameters, reduces input power fluctuations, and improves the system dynamic response speed. The superiority of the sliding mode model predictive power control is verified by simulation and experimental results. [ABSTRACT FROM AUTHOR]

The principles of multi-level output voltage control of an autonomous power supply system implemented on the basis of a three-phase constant speed self-excited induction generator with a regulated source of reactive power connected to the stator terminals and containing both a multi-modular electronic power converter and excitation capacitors are proposed. To regulate the voltage of the specified system, a stator voltage oriented vector control algorithm has been developed. Using the developed dynamic simulation model, numerical investigations of electromechanical processes in the system supplying RL-load of the local consumers were carried out to verify the effectiveness of the proposed principles of voltage control and the proposed vector control algorithm of the generator. The main advantages of applying multi-module electronic power converters in autonomous power supply systems using a self-excited induction generator with a short circuited rotor winding and an electronic power converter connected to the stator terminals for reactive power control are noted. References 10, figures 3, table 1. [ABSTRACT FROM AUTHOR]

With the rapid development of 5G base station construction, significant energy storage is installed to ensure stable communication. However, these storage resources often remain idle, leading to inefficiency. To enhance the utilization of base station energy storage (BSES), this paper proposes a co-regulation method for distribution network (DN) voltage control, enabling BSES participation in grid interactions. In this paper, firstly, an energy consumption prediction model based on long and short-term memory neural network (LSTM) is established to accurately predict the daily load changes of base stations. Secondly, a BSES aggregation model is constructed by using the power feasible domain maximal inner approximation method and Minkowski summation to evaluate the charging and discharging potential and adjustable capacity of BSES clusters. Subsequently, a BSES demand assessment and optimal scheduling model for low voltage regulation in DN is developed. This model optimizes the charging and discharging strategies of BSES to alleviate low voltage problems in DN. Finally, the simulation results effectively verify the feasibility of the proposed optimal scheduling method of BSES for voltage regulation in DN. [ABSTRACT FROM AUTHOR]

This manuscript investigates the transformative shift in electricity generation and distribution towards distributed power networks, particularly microgrids, amid escalating energy demand and environmental concerns. Emphasizing a pioneering technoeconomic conservation voltage reduction–based demand response approach, the study integrates conservation voltage reduction as a controllable demand response method within distributed power networks, highlighting the developed droop control method for effective regulation. Conservation voltage reduction, a no‐cost procedure for minimizing loss, is applied to reduce voltage during peak periods to conserve power, decrease active and reactive power losses through precise load modeling, and enhance consumption efficiency. The most significant challenge of this project is the simultaneous use of conservation voltage reduction with the uncertainties of distributed generation sources, resulting to reduce losses and ultimately lower operating costs, a topic not previously studied in existing literature. The contributions include introducing a novel approach based on droop control to manage resources and presenting a detailed control strategy tailored to distributed power networks for improving voltage stability with minimal costs. Importantly, the proposed method demonstrates superior accuracy, achieving up to an 18% improvement over existing methods. This research contributes to comprehensive solutions for optimizing energy consumption, enhancing grid stability, and adapting to the evolving distributed power systems landscape. [ABSTRACT FROM AUTHOR]

ABSTRACT The unidirectional multilevel rectifier has immense potential in high‐power medium‐voltage industrial applications. This paper proposes a multiobjective control method based on the combination of optimal‐vector‐pair modulated model predictive control (OVP‐M2PC) and a phase‐shifted modulation strategy for a unidirectional five‐level rectifier. This strategy takes both of the inductor current tracking and capacitor voltage balancing as the control objectives. First, an optimal vector pair is determined based on the AC‐side current variation rate, and then, through combining the calculated action duration of OVP with carrier phase‐shifted modulation, inductor current tracking is achieved. Second, capacitor voltage balancing control is carried out by compensating for the duty cycles which also decouples the input current tracking and output capacitor voltage balance control. Compared with traditional FCS‐MPC, under the proposed control strategy, complex cost function calculation and weighting factor tuning are not required, which much reduced computational burden. Multiobjective control is achieved with better performance in both steady‐state and dynamic conditions. The superiority of the proposed strategy over traditional FCS‐MPC are validated through simulations and hardware experiments. [ABSTRACT FROM AUTHOR]

Power electronic converters are widely used in various fields of electrical equipment. Due to their fast dynamics and non-linear nature, controlling them requires dealing with various complexities. Therefore, having a well-designed, high-speed, and robust controller is critical to ensure the effective operation of these devices. In a DC-DC converter, steady-state performance with minimum error and fast dynamic response relies on controller design. This paper presents the design of a multi-stage PID controller with an N-filter combined with a one plus proportional derivative (1+PD) controller. This controller illustrates fast tracking reference voltage; additionally, it shows incredible results when the DC-DC converter operates in different modes. The parameters of the proposed controller are effectively determined using the golden eagle optimization (GEO) algorithm. Furthermore, a comprehensive comparison between the proposed controller, proportional–integral–derivative (PID), and fractional order PID (FOPID) controllers, as well as different metaheuristic optimization methods in various conditions, has been conducted to demonstrate the effectiveness of the proposed controller. The behavior of the closed-loop system under different conditions has been thoroughly investigated. The superior time and frequency domain characteristics of the closed-loop system with the PIDn(1+PD) controller highlight its superiority over other controllers. The demonstrated enhancements in settling time, voltage regulation accuracy, and transient response emphasize the potential applicability of the proposed control strategy in real-world power electronics systems, particularly in scenarios requiring high efficiency, stability, and dynamic performance. [ABSTRACT FROM AUTHOR]

Dielectric elastomers (DE), renowned for their lightweight, rapid response, high energy density, and efficient conversion, have garnered significant attention in the realm of avian flight bionics. However, a lack of understanding of the mechanical principles underlying flapping wing biomimetics has hindered accurate simulations of actual bird flight postures. To address this, a stiffness-variable DE-based wing (DEW) has been designed, inspired by the characteristics of seagulls, to mimic the wing deformations across different bird flight phases. The evolution of the DEW’s deformation is modeled based on the differential equation describing the bending curve of a DE cantilever beam. By applying different voltage cycles, three continuous avian flight postures have been replicated: takeoff, cruising, and hovering. The simulation results demonstrate that the stiffness-variable DEW effectively mimics the wing deformations observed in birds during different flight postures, closely resembling real-world flight conditions. This study has the potential to serve as an important reference for exploring changes in bird flight behavior, thereby advancing the application of DE materials in the field of soft robotics. [ABSTRACT FROM AUTHOR]

Commercial off‐the‐shelf (OTS) photovoltaic systems coupled with battery energy storage units (PV‐BES) are typically designed to increase household self‐consumption, neglecting their potential for voltage regulation in low voltage distribution networks (LVDNs). This work proposes an enhanced sensitivity‐based combined (ESC) control method for voltage regulation, using BES control as level 1 and reactive power compensation as level 2. A centralized controller manages charging/discharging intervals, while local inverters handle real‐time power rates and reactive power, ensuring effective LVDN voltage regulation. The BES set points are obtained concerning the measured local bus voltage and according to enhanced sensitivity coefficients. The enhancement algorithm ensures that the full capacity of BES is utilized and that there is adequate capacity during charging and discharging time intervals. The proposed method, tested on 8‐bus and 116‐bus LV test feeders, outperforms OTS and an adaptive decentralized (AD) control method by completely preventing overvoltage issues, minimizing various changes in the direction of BES power, and reducing voltage deviation without significantly affecting consumers' grid dependency. [ABSTRACT FROM AUTHOR]

This article aims to investigate different dc‐bus voltage balancing control modes for a modular HVDC drive train applied to offshore wind energy. The modular structure discussed consists of a stacked polyphase bridge converter connected to the modules of a segmented generator. Three voltage control modes are analysed: non‐voltage balancing, voltage balancing allowing overcurrent, and voltage balancing with power derating. Assembly imperfections and operation differences can cause parametric deviations across modules leading to generation unbalance. When operating with voltage balancing with power derating, none has ac overcurrent or dc overvoltage. However, when the turbine is already operating at nominal power, a reduction in total power is required for this to occur. On the other hand, non‐voltage balancing or voltage balancing allowing overcurrent could bring more generated power to the system as the optimal output power allows dc overvoltage or ac overcurrent in some of the modules, respectively. Therefore, there is a trade‐off between efficiency and oversizing the system's components. A sensitivity analysis is performed to identify the expected dc‐bus voltage deviation. Experimental results in a low‐power prototype validate the voltage balancing control modes and a case study demonstrates the impact on energy yield in an offshore wind turbine. [ABSTRACT FROM AUTHOR]

Aiming to improve the voltage distribution and realize the proportional sharing of active and reactive power in the distribution network (DN), this article proposes a distributed optimal control strategy based on the grouping cooperation mechanism of the distributed generation (DG). The proposed strategy integrates the local information of the DG and the global information of the DN. Considering the high resistance/reactance ratio of DN, distributed optimization control strategies for node voltage control and active power management are developed with the consensus variable of active utilization rate. And distributed strategy for reactive power management is proposed with a consensus variable of reactive utilization rate. The convergence of the distributed control system for each group is proved. The validity and robustness of the proposed strategy are verified by several simulations in the IEEE 33‐bus system. [ABSTRACT FROM AUTHOR]

The point of common coupling (PCC) voltage feedforward control strategy can effectively reduce the startup inrush current and improve the anti‐interference ability of the LCL‐type converters, which is widely used in the renewable energy converters control field. With the high penetration of the new energy, the increase of grid impedance leads to the weakening of the grid. Under weak grid conditions, the PCC voltage feedforward control strategy will generate an additional feedback loop of grid‐side current, which has a great impact on the stability of the system. In this paper, the damping characteristic of the PCC voltage feedforward control strategy and the effect on the open loop characteristic of the system have been deeply analyzed. An improved PCC voltage feedforward control strategy based on a proportional plus band‐pass filter is proposed, which can effectively improve the phase margin and achieve active damping under weak grid conditions, therefore, the robustness of the converters can be effectively improved. A three‐phase LCL‐type AC/DC converter platform is built and comparative experiments are carried out to verify the effectiveness of the proposed algorithm. The experimental results are consistent with the theoretical analysis. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

In this paper, a modular resonant inverter is proposed for high frequency industrial heating applications. To maintain a uniform heating profile, the inverter is operated in constant power mode. A hybrid voltage and frequency control is proposed. Voltage control is used for active power tracking while frequency control is used to minimise circulating current due to reactive power and to achieve soft switching for the inverter switches. Analytical and test results are shown to verify the proposed approach. [ABSTRACT FROM AUTHOR]

ABSTRACT In low‐voltage applications using low‐Q LC filters, alias‐free capacitor voltage acquisition can be achieved, but synchronous capacitor voltage sampling under high‐Q filters used in high‐voltage applications in grid‐forming converters causes some degree of distortion and results in degradation of the power supply quality. And the inherent 1.5 sampling periods that delay in this approach limit the control bandwidth, reduce the stability region, and result in an inadequate time domain response. Despite these shortcomings, this approach is widely accepted in practice. The conclusion of this paper is that shifting the capacitor voltage sampling instant to 2 µs before the pulse width modulation (PWM) reference voltage update results in almost the same distortion as synchronous sampling. However, it can improve the dynamic performance of the system. A distortion‐acceptable univariate feedback voltage dual‐loop active damping control topology with much reduced computational delay is proposed, which is based on an internal active damping loop using a discrete lead compensator and a proportional resonance controller in the external voltage loop. [ABSTRACT FROM AUTHOR]

ABSTRACT The objective of this submission is to provide flexible reactive power regulation of a photovoltaic (PV)‐driven grid‐connected inverter. Here, inverter is realized as a synchronverter by employing frequency regulation using well‐established swing equation. However, reactive power regulation is accomplished by employing combined AC–DC voltage control in addition to traditional synchronverter control for ensuring smooth tracking of reactive power. Thus, the PV‐driven voltage source converter (VSC) will be injecting available active power as per the prevailing irradiation, temperature, and operator defined reactive power by employing proposed control. The performance of suggested control is evaluated and compared against existing control by considering realistic operational scenarios through a case study. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) are rapidly replacing fossil-fuel-powered vehicles, creating a need for a fast-charging infrastructure that is crucial for their widespread adoption. This research addresses this challenge by improving the control of dual active bridge converters, a popular choice for high-power EV charging stations. A critical issue in EV battery charging is the smooth transition between charging stages (constant current and constant voltage) which can disrupt converter performance. This work proposes a novel feedforward control method using a combination of droop-based techniques combined with a sophisticated linear active disturbance rejection control system applied to a single-phase shift-modulated dual active bridge. This combination ensures a seamless transition between charging stages and enhances the robustness of the system against fluctuations in both input voltage and load. Numerical simulations using MATLAB/Simulink R2024a demonstrated that this approach not only enables smooth charging but also reduces the peak input converter current, allowing for the use of lower-rated components in the converter design. This translates to potentially lower costs for building these essential charging stations and faster adoption of EVs. [ABSTRACT FROM AUTHOR]

This paper describes active battery balancing based on a bidirectional buck converter, a flyback converter, and battery cells by using the proposed chain-loop comparison strategy. The role of the bidirectional buck converter is to charge/discharge the battery pack. During the charging period, the converter is in buck mode, and its output is controlled by constant current/voltage; during the discharging period, the converter is in boost mode, and its output is controlled by constant voltage. The role of the flyback converter is voltage equalization of the battery pack, and its output is controlled by constant current. A chain-loop comparison strategy is used to control battery voltage equalization. In this work, three equalization modes, namely, charging balance, discharging balance, and static balance, were considered. The voltage difference between the maximum and minimum is 0.007 V after a balancing time of 19.75 min, 0.005 V after a balancing time of 24 min, and 0.007 V after a balancing time of 20 min for charging balance, discharging balance, and static balance, respectively. [ABSTRACT FROM AUTHOR]

Coordinated voltage control enables the active management of voltage levels throughout electricity distribution networks by leveraging the voltage support capabilities of existing grid-connected PV inverters. The efficient management of power flows and precise voltage regulation through coordinated voltage control schemes facilitate the increased adoption of rooftop PV systems and enhance the hosting capacity of electricity distribution networks. The research work presented in this paper proposes a coordinated voltage control scheme and evaluates the enhanced hosting capacity utilizing a deep reinforcement learning-based approach. A comparative analysis of the proposed algorithm is presented, and the performance is benchmarked against existing local voltage control schemes. The proposed coordinated voltage control scheme in this paper is evaluated using simulations on a real-world low-voltage electricity distribution network. The evaluation involves quasi-static time series power flow simulations for assessing performance. Furthermore, a discussion is presented that reflects on the strengths and limitations of the proposed scheme based on the results observed from the case study. [ABSTRACT FROM AUTHOR]

This paper focuses on the distributed generation (DG) controller of a PV-based microgrid. An independent DG controller (IDGC) is designed for PV applications to improve Maximum-Power Point Tracking (MPPT). The Extreme-Learning Machine (ELM)-based MPPT method exactly estimates the controller's reference input, such as the voltage and current at the MPP. Feedback controls employ linear PI schemes or nonlinear, intricate techniques. Here, the converter controller is an IDGC that is improved by directly measuring the converter duty cycle and PWM index in a single DG PV-based MG. It introduces a fast-learning Extreme-Learning Machine (ELM) using the Moore–Penrose pseudo-inverse technique and online sequential ridge methods for robust control reference (CR) estimation. This approach ensures the stability of the microgrid during PV uncertainties and various operational conditions. The internal DG control approach improves the stability of the microgrid during a three-phase fault at the load bus, partial shading, irradiance changes, islanding operations, and load changes. The model is designed and simulated on the MATLAB/SIMULINK platform, and some of the results are validated on a hardware-in-the-loop (HIL) platform. [ABSTRACT FROM AUTHOR]

The step-down DC/DC converter is characterized by the parametric uncertainty of its model and its high sensitivity to external disturbances identified by variations in the input voltage, load and output reference voltage. To overcome these limitations, this paper proposes the experimental evaluation of a new adaptive synergetic control law based on the M5P model tree for efficient output voltage control of the step-down type DC/DC converter. A combination of the synergetic technique, the fuzzy logic theory and the machine learning has been used for the first time to develop this advanced control law. The synergetic strategy is exploited to overcome the chattering problem arising from the use of the sliding mode approach which has been applied in previous research. Furthermore, the novel machine learning M5P tree-based approximator was designed and applied to approximate the unknown and imprecise dynamics of the studied converter. The learning data comes from the smart approximator, which is based on fuzzy logic, with the aim of extracting its own advantages and offering them to the new tree-based approximator M5P. This action will make it possible to improve the operation of the fuzzy approximator, which has already been studied in some research. Finally, the developed control strategy was successfully evaluated in the laboratory using the dSPACE 1104 board and compared with the fuzzy adaptive synergetic approach under different conditions of load variations and imposed references. The practical results show that the proposed tree adaptive synergetic approach is competitive with the fuzzy adaptive strategy in terms of ease of practical implementation, fast control execution and better output voltage regulation quality. [ABSTRACT FROM AUTHOR]

The increasing energy demand in information technologies requires novel low‐power procedures to store and process data. Magnetic materials, central to these technologies, are usually controlled through magnetic fields or spin‐polarized currents that are prone to the Joule heating effect. Magneto‐ionics is a unique energy‐efficient strategy to control magnetism that can induce large non‐volatile modulation of magnetization, coercivity and other properties through voltage‐driven ionic motion. Recent studies have shown promising magneto‐ionic effects using nitrogen ions. However, either liquid electrolytes or prior annealing procedures are necessary to induce the desired N‐ion motion. In this work, magneto‐ionic effects are voltage‐triggered at room temperature in solid state systems of CoxMn1‐xN films, without the need of thermal annealing. Upon gating, a rearrangement of nitrogen ions in the layers is observed, leading to changes in the co‐existing ferromagnetic and antiferromagnetic phases, which result in substantial increase of magnetization at room temperature and modulation of the exchange bias effect at low temperatures. A detailed correlation between the structural and magnetic evolution of the system upon voltage actuation is provided. The obtained results offer promising new avenues for the utilization of nitride compounds in energy‐efficient spintronic and other memory devices. [ABSTRACT FROM AUTHOR]

With the rapid development of 5G base station construction, significant energy storage is installed to ensure stable communication. However, these storage resources often remain idle, leading to inefficiency. To enhance the utilization of base station energy storage (BSES), this paper proposes a co-regulation method for distribution network (DN) voltage control, enabling BSES participation in grid interactions. In this paper, firstly, an energy consumption prediction model based on long and short-term memory neural network (LSTM) is established to accurately predict the daily load changes of base stations. Secondly, a BSES aggregation model is constructed by using the power feasible domain maximal inner approximation method and Minkowski summation to evaluate the charging and discharging potential and adjustable capacity of BSES clusters. Subsequently, a BSES demand assessment and optimal scheduling model for low voltage regulation in DN is developed. This model optimizes the charging and discharging strategies of BSES to alleviate low voltage problems in DN. Finally, the simulation results effectively verify the feasibility of the proposed optimal scheduling method of BSES for voltage regulation in DN. [ABSTRACT FROM AUTHOR]

In this paper, a method for determining line drop compensator (LDC) parameters for step voltage regulators and on‐load tap changers is proposed to avoid voltage violations in distribution systems with voltage fluctuations due to photovoltaic (PV) generation and electric vehicle (EV) charging. Distribution system operators need to effectively solve voltage problems caused by the widespread installation of distributed energy resources with the existing voltage regulators to construct an efficient and rational infrastructure. Our focus was on improving the method for determining the LDC parameters for the existing voltage regulators based on LDC control. A mechanism to dynamically change the LDC parameters depending on the situations in the distribution system was developed by using a mixture of experts, one of the machine learning techniques, and real‐time voltage and power flow information from information technology switches. The power flow calculations were performed using a distribution system model constructed based on the topology, loads, and generation characteristics of an actual distribution system in the Hokuriku region. The effectiveness of the proposed method was evaluated in terms of its improved effect on PV and EV hosting capacity, as well as the impact on the frequency of tap operations of voltage regulators. © 2024 The Author(s). IEEJ Transactions on Electrical and Electronic Engineering published by Institute of Electrical Engineers of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

ABSTRACT The multiple‐input and multiple‐output (MIMO) DC–DC converters offer various advantages such as improved efficiency and reduced component count. However, the preference of these converters over other types of converters is dependent on the specific application and requirements. Various types of boost‐derived MIMO DC–DC converters are discussed in the literature. However, these converters are either nonisolated or isolated types. In the paper, a MIMO‐based cascaded boost hybrid interlink converter (CBHIC) has been proposed. The proposed converter includes four DC–DC boost converters that are supplied power by two input DC sources. The boosted DC output of these converters can be used independently or in a cascaded manner depending upon the requirement of the load. Further, the cascaded action of these four boost converters leads to the production of two high‐frequency AC outputs. By using bridge rectifiers and high‐frequency transformers, high‐frequency AC voltages are converted into DC. Therefore, two isolated DC output voltages can be achieved using CBHIC. The complementary operation of the cascaded boost converters results in reduction of source current ripples. The design, operating modes, and performance evaluation of the proposed CBHIC have been included in the paper. To validate the efficacy of the proposed CBHIC, a lab prototype of 400 W is prepared. The rms value of high‐frequency AC output voltage at each is isolated port is 141 V. The CBHIC exhibits an efficiency of 94.3 at 400 W. The operation of the converter during voltage control mode is further explored and its dynamic response is studies with the help of experimental results. The obtained simulation and experimental results validate the effectiveness of the proposed converter. [ABSTRACT FROM AUTHOR]

In order to enhance the dynamic performance of aircraft high‐voltage direct current wound rotor synchronous generator (WRSG) system under load variations, a dual internal model control (DIMC) method utilising improved load current feedback (ILCF) is proposed. It employs internal model controllers in both voltage and current loops, thereby significantly augmenting the system's disturbance rejection capabilities. Improved load current feedback is incorporated between the DC voltage loop and the field current loop. Additionally, a method for designing a feedback fitting function is established, enhancing the system's adaptability to changes in operational speed and load. The authors outline parameter design methods for voltage and current loops in DIMC, based on the internal model control principle. Adjustments to these parameters can further enhance the system's disturbance rejection capabilities. Finally, comparative experiments between the PI method with ILCF and the DIMC method with ILCF are conducted on a 15 kW WRSG experimental platform. These experiments demonstrate that the proposed DIMC method with ILCF optimises dynamic performance across the entire speed range, enhancing the competitiveness of WRSG systems in aircraft applications. [ABSTRACT FROM AUTHOR]

Summary: Virtual synchronous generators (VSGs) are comprised of an outer power loop and inner cascaded control loops. The dynamic performance of the output interface is severely degraded when microgrid loads exhibit variability and nonlinearity. Therefore, robustness against load disturbances must be possessed by any voltage control scheme. In this paper, a proportional resonance‐linear active disturbance rejection control (PR‐LADRC) scheme based on an improved linear extended state observer (ILESO) is proposed for VSG voltage control. In comparison with the traditional linear extended state observer (LESO), the differential state variable of the output voltage is utilized to increase the observation bandwidth; consequently, the proposed ILESO can effectively overcome the disadvantage of phase lag when tracking disturbances. Additionally, a proportional resonance controller is incorporated into the LESO feedforward channel to suppress voltage harmonics. The proposed scheme enhances the disturbance observation bandwidth compared to traditional strategies, resulting in a substantial improvement in both the disturbance observation capability of LADRC and the harmonic suppression ability of the VSG system. Theoretical analysis and simulations are conducted to validate the effectiveness of the proposed PR‐LADRC approach. [ABSTRACT FROM AUTHOR]

This paper presents the effect of dead time on active power transfer of the dual active bridge (DAB) and a novel mitigation technique for the same. The whole power range is categorized into five zones based on the switching instant link current direction and the modified active power expressions with effect of dead time are derived for each zone. The novel compensation method for dead time improves the performance of any general optimized techniques for DAB with extended phase shift. Firstly, the link current values at different switching instants are estimated using the mathematical expressions obtained using a linear piece-wise method. Secondly, the values are used for compensation logic formulation in the whole power range. The compensation process is applied to two different configurations, open loop (circulating mode) and close loop (voltage control mode). The mid-power zone is compensated using a constant phase shift modification and the low power zone is compensated using a PI controller based phase shift modification. Finally, the effectiveness of the proposed compensation technique is verified through MATLAB Simulink model and 1.2 kW experimental prototype. [ABSTRACT FROM AUTHOR]

Although field medical microgrids have been widely studied as an important component of future medical power systems, current sharing control in field medical microgrids under false information injection (FDI) attacks has rarely been researched. Based on this, this paper proposes a distributed fuzzy control method for power sharing in field medical microgrids considering communication networks under FDI attacks. First, the field medical microgrid is modeled as a multi-bus DC microgrid system with power coupling. To provide voltage control and initial current equalization, fractional order PI control is applied. In order to reduce the model complexity, the concept of block modeling is employed to transform the model into a linear heterogeneous multi-agent system. Secondly, a fully distributed current sharing fuzzy control strategy is proposed. It can precisely realize current sharing control and reduce the communication bandwidth. Finally, the proposed control strategy is verified by simulation results. [ABSTRACT FROM AUTHOR]

PMUs and micro PMUs are an emerging technology that is gaining increasing importance in the monitoring and control of electric distribution grids. Their ability to provide accurate, real-time information on power quality, along with their ability to quickly detect and isolate any problems on the grid, make them a key tool for increasing grid safety and reliability. In terms of research and development, there is a growing interest in developing more advanced and reliable Micro PMUs that can provide more detailed and accurate information about the grid. In addition, there is a growing focus on integrating Micro PMUs with other grid control and monitoring systems, such as frequency and voltage control systems, to achieve greater efficiency in grid management. In this research, a commercial PMU is tested during transient conditions typical of distribution grids such as load insertion and de-insertion and distributed generation. The system involves simulating a grid in a Simulink environment and transforming digital signals into analog signals to be supplied to the PMU. Some indices such as TVE, ROCOF are then used for performance analysis. [ABSTRACT FROM AUTHOR]

This letter presents a 28 GHz balun‐first low noise amplifier (LNA) featuring a wide dB‐linear variable gain range. The architecture of LNA includes three‐stage cascode amplifiers. An integrated balun at the input stage provides RF ESD protection and converts a single‐ended signal to a differential one (S‐to‐D). A transformer‐based dual‐resonant matching network is designed and analyzed to achieve wideband performance. To realize a continuous dB‐linear variable gain range and consistent input/output matching, gain control is implemented in the second stage using a 5‐bit digital‐to‐analog converter (DAC) for a 32 dB gain range. The DAC can generate a nonlinear analog voltage to control the gate of the common‐gate transistor in the second cascode stage, inversely compensating for the nonlinear gain variations of the cascode amplifier. The LNA is fabricated in 65‐nm CMOS process with a core size of 0.154 mm². Measurement results exhibit a maximum gain of 33.5 dB and a minimum noise figure (NF) of 3.65 dB with a 3‐dB bandwidth of 23–29.5 GHz. The measured variable gain range is approximately 32 dB across 32 different gain states, with a linear gain step of ~1 dB per state and an IP1dB ranging from −6.5 dBm to −35.25 dBm. The power consumption is 35.4–48 mW from a 1.2 V supply voltage. [ABSTRACT FROM AUTHOR]

For maintenance of distributed wind power networks, it remains important to realize intelligent operation scheduling strategies for wind power equipments according to their working status. As a consequence, this paper proposes a deep learning-based optimal scheme for distributed wind power networks. First of all, an adaptive status assessment model is constructed to identify time-varying operation status for unit components. Then, based on the predicted operation risk of unit components, a preventive maintenance decision model is formulated to realize flexible decision-making of maintenance tasks. Finally, a dynamic maintenance task scheduling model based on extreme learning machine (ELM) neural network is designed. The ELM neural network-based scheduling approach is expected to use a historical strategy library to assist in revising realtime voltage control strategy. Also, we conduct some experiments to evaluate the performance of the proposed method through simulation modeling. The obtained results show that real-time voltage control accuracy for wind power networks with an incomplete observation area is improved. [ABSTRACT FROM AUTHOR]

To improve the voltage regulation of asynchronous generators during load switching, a Lyapunov-based control strategy has been proposed to stabilize the generator's voltage by connecting a static synchronous compensator. By constructing a Lyapunov function from the mathematical model, the error tracking problem is transformed into a global asymptotic stability problem of the Lyapunov function at the equilibrium point. The outer loop linearizes the direct current (DC) voltage control process, while the inner loop replaces integral terms with differential terms. The proposed Lyapunov method achieves linearized voltage control with a quadratic outer loop structure and the inner loop differential structure exhibits a shorter transient process, outperforming traditional methods. Simulation and experimental tests were then used, where the latter was a down-scale laboratory prototype experiment. Compared to traditional (voltage-oriented control) VOC, the outer loop (Lyapunov-function-based control) LBC reduces the DC voltage transient processes by approximately 9.4 milliseconds, while the inner loop LBC reduces both alternating current (AC) and DC voltage transient processes by approximately 2.6 ms and 8.7 ms, respectively. [ABSTRACT FROM AUTHOR]

This paper proposes goal-function-based decentralized control of microgrids. In addition to being an instrument for maintaining the grid voltage and frequency stability, each grid-tie inverter generates a current component with the aim of compensating for voltage distortion in the node where it is connected. The designed goal-function does not need to rely on the assumption that a microgrid is dominantly inductive or resistive to derive its control law, as is mostly the case with the droop-based approach. The priorities of the proposed scheme can be adjusted according to user preferences. In addition, the control algorithm is independent of network topology, can be applied in both islanded and non-islanded microgrids, and secure system scalability. The proposed method is verified by detailed simulations. [ABSTRACT FROM AUTHOR]

Flexible user-side resources are of great potential in providing power regulation so as to effectively address the challenges of reverse power flow and overvoltage issues in distribution networks characterized by high photovoltaic (PV) penetration. However, existing distributed algorithms typically implement control signals after the convergence of the algorithms, making it difficult to track frequent and rapid fluctuations in PV power outputs in real time. Given this background, an online-distributed control algorithm for the real-time power regulation of flexible user-side resources is proposed in this paper. The objective of the established control model is to minimize network losses by dynamically adjusting active power outputs of flexible user-side resources and reactive power outputs of PV inverters while respecting branch power flow and voltage magnitude constraints. Furthermore, by deconstructing the centralized problem into a primal–dual one, a distributed control strategy based on the dual ascent method is implemented. With the proposed method, agents can achieve global optimality by exchanging limited information with their neighbors. The simulation results verify the good balance between economic efficiency and voltage control performance of the proposed method. [ABSTRACT FROM AUTHOR]

Ca2+ release from the sarcoplasmic reticulum (SR) plays a central role in excitation-contraction coupling (ECC) in skeletal muscles. However, the mechanism by which activation of the voltage-sensors/dihydropyridine receptors (DHPRs) in the membrane of the transverse tubular system leads to activation of the Ca2+-release channels/ryanodine receptors (RyRs) in the SR is not fully understood. Recent observations showing that a very small Ca2+ leak through RyR1s in mammalian skeletal muscle can markedly raise the background [Ca2+] in the junctional space (JS) above the Ca2+ level in the bulk of the cytosol indicate that there is a diffusional barrier between the JS and the cytosol at large. Here, I use a mathematical model to explore the hypothesis that a sudden rise in Ca2+ leak through DHPR-coupled RyR1s, caused by reduced inhibition at the RyR1 Ca2+/Mg2+ inhibitory I1-sites when the associated DHPRs are activated, is sufficient to enable synchronized responses that trigger a regenerative rise of Ca2+ release that remains under voltage control. In this way, the characteristic response to Ca2+ of RyR channels is key not only for the Ca2+ release mechanism in cardiac muscle and other tissues, but also for the DHPRdependent Ca2+ release in skeletal muscle. [ABSTRACT FROM AUTHOR]

This paper develops a distributed secondary control strategy for direct current (DC) microgrid based on the distributed state estimation under false data injection (FDI) attacks. FDI attacks occurring on sensors, communication links, and control channels are fully considered, and a distributed state estimation–based secondary control is designed to filter out the effects of attack signals introduced in the secondary control. The secondary control is designed based on a consistent Kalman filtering algorithm, which is able to improve the accuracy by introducing corrections to the current predicted values from the previous moment of the neighbors. In addition, the consistency gain matrix is transformed into consistency coefficients to improve the correction speed. The filtered secondary control signal is fed into the primary control for voltage recovery and precise power distribution. A rigorous proof based on Lyapunov's technique shows that the method guarantees the convergence of global voltage regulation under FDI attacks. Simulation results show that the proposed method can achieve voltage recovery and accurate power distribution when the DC microgrid is subjected to FDI attacks. [ABSTRACT FROM AUTHOR]

As photovoltaic energy is clean, renewable, and less noisy, it is increasingly integrated into the grid. This integration aims to overcome energy deficits and get rid of pollution from conventional sources. In this paper, a two-stage configuration of PV energy conversion to a three-phase grid has been studied. The control of this configuration can be divided into two parts, such as DC bus control and AC bus control. The DC bus is controlled by MPPT control. The AC bus is controlled by DC link voltage control, phase-looked loop control, and voltage source inverter control. The contribution in this study aims to improve the quality of energy injected via a new hybrid approach to MPPT control. The proposed control is a combination of robust sliding-mode control and incremental inductance. Unlike conventional hybridization, the proposed control estimates correct the error upon entry of the conductance incremental control. This correction provides an adaptive incremental step for increment conductance control. The proposed control is compared with three other controls under MATLAB/Simulink. Such as incremental conductance, variable step size incremental conductance, and conventional hybrid MPPT incremental inductance-sliding mode control. The simulation results show a remarkable minimization of the ripple phenomenon and the chatter phenomenon. Thus, the quality of the energy injected into the network is improved, such as by reducing the total harmonic distortion of the current and increasing efficiency. [ABSTRACT FROM AUTHOR]