Search Results (338)

Renewable energy’s growing penetration erodes traditional power systems’ inherent dynamic symmetry—balanced inertia, damping, and frequency response. This paper proposes a self-adaptive virtual synchronous generator (VSG) control strategy for a photovoltaic hybrid energy storage system (PV-HESS) based on a radial basis function (RBF) neural network. The strategy establishes a dynamic adjustment framework for inertia and damping parameters via online learning, demonstrating enhanced system stability and robustness compared to conventional VSG methods. In the structural design, the DC-side energy storage system integrates a passive filter to decouple high- and low-frequency power components, with the supercapacitor attenuating high-frequency power fluctuations and the battery stabilizing low-frequency power variations. A small-signal model of the VSG active power loop is developed, through which the parameter ranges for rotational inertia (J) and damping coefficient (D) are determined by comprehensively considering the active loop cutoff frequency, grid connection standards, stability margin, and frequency regulation time. Building on this analysis, an adaptive parameter control strategy based on an RBF neural network is proposed. Case studies show that under various conditions, the proposed RBF strategy significantly outperforms conventional methods, enhancing key performance metrics in stability and dynamic response by 16.98% to 70.37%. Full article

To further enhance economic efficiency and optimize energy conservation and emission reduction performance, an optimized energy management strategy (EMS) tailored for the hybrid power system of rubber-tyred gantry cranes is proposed. Wavelet packet decomposition (WPD) was employed as the signal processing approach, and this method was further integrated with EMS for hybrid power systems. Through a three-layer progressive architecture comprising WPD frequency–domain decoupling, fuzzy logic real-time adjustment, and PSO offline global optimization, a cooperative optimization mechanism has been established in this study between the frequency-domain characteristics of signals, the physical properties of energy storage components, and the real-time and long-term states of the system. Firstly, the modeling and simulation of the power system were conducted. Subsequently, an EMS based on WPD and limit protection was developed: the load power curve was decomposed into different frequency bands, and power allocation was implemented via the WPD algorithm. Meanwhile, the operating states of lithium batteries and supercapacitors were adjusted in combination with state of charge limits. Simulation results show that this strategy can achieved reasonable allocation of load power, effectively suppressed power fluctuations of the auxiliary power unit system, and enhanced the stability and economy of the hybrid power system. Afterward, a fuzzy controller was designed to re-allocate the power of the hybrid energy storage system (HESS), with energy efficiency and battery durability set as optimization indicators. Furthermore, particle swarm optimization algorithms were adopted to optimize the EMS. The simulation results indicate that the optimized EMS enabled more reasonable power allocation of the HESS, accompanied by better economic performance and control effects. The proposed EMS demonstrated unique system-level advantages in enhancing energy efficiency, extending battery lifespan, and reducing the whole-life cycle cost. Full article

Triboelectric nanogenerators (TENGs) offer intrinsically high open-circuit voltages in the kilovolt range; however, conventional diode rectifier interfaces clamp the voltage prematurely, restricting access to the high-energy portion of the mechanical cycle and preventing delivery-centric control. This work develops a unified physical basis for contact–separation (CS) TENGs by confirming the consistency of the canonical $V_{oc}$–$C_s$ relation with a dual-capacitor energy model and analytically establishing that both terminal voltage and storable electrostatic energy peak near maximum plate separation. Leveraging this insight, a self-powered gas-discharge-tube (GDT) rectifier bridge is devised to replace two diodes and autonomously trigger conduction exclusively in the high-voltage window without auxiliary bias. An inductive buffer regulates the current slew rate and reduces $I^{2}R$ loss, while the proposed topology realizes two decoupled power rails from a single CS-TENG, enabling simultaneous sensing/processing and actuation. A low-power microcontroller is powered from one rail through an energy-harvesting module and executes an operator-based nonlinear controller to regulate the actuator-side rail via a MOSFET–resistor path. Experimental results demonstrate earlier and higher-efficiency energy transfer compared with a diode-bridge baseline, robust dual-rail decoupling under dynamic loading, and accurate closed-loop voltage tracking with negligible computational and energy overhead. These findings confirm the practicality of the proposed self-powered architecture and highlight the feasibility of integrating operator-theoretic control into TENG-driven rectifier interfaces, advancing delivery-oriented power extraction from high-voltage TENG sources. Full article

Virtual power plants (VPPs) provide essential regulation capabilities by aggregating diverse distributed energy resources (DERs). Accurately assessing the value of VPPs from the grid’s side is essential for improving market mechanism design and, in turn, encouraging participation of VPPs. However, existing assessment methods neglect the refined evaluations integrating Automatic Generation Control (AGC)-based operational simulations derived from economic dispatch results, thereby failing to comprehensively capture the multi-dimensional benefits VPPs contribute to the grid. To bridge this gap, this study proposes a multi-dimensional benefit assessment method of VPPs and a simulation method from the grid’s perspective. First, the environmental, security, and economic benefits of VPPs are characterized. A decoupled quantitative assessment framework based on the Vickrey-Clarke-Groves (VCG) mechanism is then established to evaluate these benefits by analyzing system cost variations induced by VPP aggregation. Next, the method of actual operation simulation based on scheduling outcomes is discussed. The corresponding system operation costs are obtained under various scenarios. Case studies utilizing real-world data from a provincial power grid in China analyzed the benefits of VPPs across multiple scenarios defined by varying renewable energy penetration rates, aggregation sizes, and output stability. Notably, the value of the VPP differs significantly across renewable energy penetration levels. Under high penetration, its value increases by 18.5% compared with the low-penetration case, and the value of security and ancillary services accounts for the largest share (50.3%), a component frequently overlooked in existing literature. These findings offer valuable insights for optimizing electricity market mechanisms. Full article

As a multi-switching power electronic circuit with complex variable topology, the three-level active neutral point clamped (ANPC) converter is a complex system with strong coupling and low linearity. It has numerous high-speed switching devices, a large number of switch states, and a high matrix dimension. Modeling each switch will undoubtedly further increase the circuit size. While in real-time simulation, updating all states of the model to produce outputs within a single time step results in a significant computational load, causing an increasing consumption of FPGA hardware resources as the number of switches and circuit size grow. In order to solve this problem, the current common practice is to decompose the entire complex power electronic system into smaller serial subsystems for modeling. The overall modeling approach for small circuits can be achieved, but when the size of the circuit increases, the overall modeling complexity and difficulty are increased or even impossible to achieve. Decoupling power electronic circuits with this decomposition into subsystem modeling not only reduces the matrix dimension and simplifies the modeling process, but also improves the computational efficiency of the real-time simulator. However, this inevitably generates simulation delays between different subsystems, leading to numerical oscillations. In an effort to overcome this challenge, this paper adopts the method of parallel computation after subsystem partitioning. There is no one-beat delay between different subsystems, and there is no loss of accuracy, which can improve the numerical stability of the modeling and can effectively reduce the step length of real-time simulation and alleviate the problem of real-time simulation resource consumption. In addition, to address the problems of low accuracy due to the traditional forward Euler method as a solver and the possibility of significant errors at some moments, this paper uses a modified prediction correction method to solve the discrete mathematical model, which provides higher accuracy as well as higher stability. And, different from the traditional control method, this paper uses an improved FCS-MPC strategy to control the switching transients of the ANPC model, which achieves a very good control effect. Finally, a simulation step size of less than 60 ns is successfully realized by empirical demonstration on the Speedgoat test platform. Meanwhile, the accuracy of our model can be objectively evaluated by comparing it with the simulation results of the Matlab Simpower system. Full article

This study presents the development and experimental validation of a novel wind turbine emulator (WTE) based on a doubly fed induction generator (DFIG). The proposed architecture employs an induction motor (IM) driven by a variable frequency drive (VFD) to emulate wind turbine dynamics, offering a cost-effective and low-maintenance alternative to traditional DC motor-based systems. The contribution of this work lies, therefore, not in the hardware topology itself, but in the complete real-time software implementation of the control system using C language and RTLib, which enables higher sampling rates, faster PWM updates, and improved execution reliability compared with standard Simulink/RTI approaches. The proposed control structure integrates tip–speed ratio (TSR)-based maximum power point tracking (MPPT) with flux-oriented vector control of the DFIG, fully coded in C to provide optimized real-time performance. Experimental results confirm the emulator’s ability to accurately replicate real wind turbine behavior under varying wind conditions. The test bench demonstrates fast dynamic response, with rotor currents settling in 11–18 ms, and active/reactive powers stabilizing within 25–30 ms. Overshoots remain below 10%, and steady-state errors are limited to ±1 A for currents and ±100 W/±50 VAR for powers, ensuring precise power regulation. The speed tracking error is approximately 0.61 rad/s, validating the system’s ability to follow dynamic references with high accuracy. Additionally, effective decoupling between active and reactive loops is achieved, with minimal cross-coupling during step changes. Full article

The Modular Multilevel Converter (MMC) has gained significant popularity over the past decade due to its versatility. The MMC features have been leveraged in numerous fields, including high-voltage DC transmission, electric vehicle power trains, motor drives, and wind energy conversion. In controlling the MMC, the circulating current (i.e., the current flowing through both the upper and lower converter arms without delivering power to the load) has consistently been the most critical variable. In early applications, it was perceived as a source of losses, but more recently, it has become evident that injecting a specific current could reduce voltage and energy ripples. This paper presents a theoretical framework, based on time-scale analysis, useful for modeling and controlling MMCs. The new approach is adopted for generating the circulating current reference, which is expressed as a linear combination of orthogonal functions. The goals are to decouple the control of the voltages of the upper and lower converter arms and manage additional harmonic components of the circulating current for voltage ripple reduction on module capacitors. The simulations and experimental results demonstrate the effectiveness of the proposed control strategy. Full article

Background: Repetitive transcranial magnetic stimulation (rTMS) is an established neuromodulatory method, yet its multiscale neurophysiological effects in autism spectrum disorder (ASD) remain insufficiently characterized. Recent EEG analytic advances—such as spectral parameterization, long-range temporal correlation (LRTC) assessment, and connectivity modeling—enable quantitative evaluation of excitation–inhibition (E/I) balance and network organization. Objective: This study aimed to examine whether an eight-session, EEG-guided mixed-frequency rTMS protocol—combining inhibitory 1 Hz and excitatory 10 Hz trains individualized to quantitative EEG (qEEG) abnormalities—produces measurable changes in spectral dynamics, temporal correlations, and functional connectivity in a pediatric ASD case. Methods: An 11-year-old right-handed female with ASD (DSM-5-TR, ADOS-2) underwent resting-state EEG one week before and four months after intervention. Preprocessing used a validated automated pipeline, followed by spectral parameterization (FOOOF), detrended fluctuation analysis (DFA), and connectivity analyses (phase-lag index and Granger causality) in MATLAB (2023b). No inferential statistics were applied due to the single-case design. The study was conducted at Cosmos Healthcare (London, UK) with in-kind institutional support and approved by the Atlantic International University IRB (AIU-IRB-22-101). Results: Post-rTMS EEG showed (i) increased delta and reduced theta/alpha/beta power over central regions; (ii) steeper aperiodic slope and higher offset, maximal at Cz, suggesting increased inhibitory tone; (iii) reduced Hurst exponents (1–10 Hz) at Fz, Cz, and Pz, indicating decreased long-range temporal correlations; (iv) reorganization of hubs away from midline with marked Cz decoupling; and (v) strengthened parietal-to-central directional connectivity (Pz→Cz) with reduced Cz→Pz influence. Conclusions: Mixed-frequency, EEG-guided rTMS produced convergent changes across spectral, aperiodic, temporal, and connectivity measures consistent with modulation of cortical E/I balance and network organization. Findings are preliminary and hypothesis-generating. The study was supported by in-kind resources from Cosmos Healthcare, whose authors participated as investigators but had no influence on analysis or interpretation. Controlled trials are warranted to validate these exploratory results. Full article

In response to the demands for high reliability, excellent dynamic response, and high-precision control of advanced aircraft actuation systems, this study focuses on the control technology for the master-master operating mode of dual-redundancy electro-hydrostatic actuation (EHA) systems. A multi-domain coupling model integrating motor magnetic circuit saturation, hydraulic viscosity-temperature characteristics, and mechanical clearances was established, based on which a current-loop decoupling technique using vector control was developed. Furthermore, the study combined adaptive sliding mode control (ASMC) and an improved active disturbance rejection control (ADRC) to enhance the robustness of the speed loop and the disturbance rejection capability of the position loop, respectively. To address the key challenges of synchronous error accumulation and uneven load distribution in the master-master mode, a dual-redundancy dynamic model accounting for hydraulic coupling effects was developed, and a two-level cooperative control strategy of "position synchronization-dynamic load balancing" was proposed based on the cross-coupling control (CCC) framework. Experimental results demonstrate that the position loop control error is less than ±0.02 mm, and the load distribution accuracy is improved to over 97%, fully meeting the design requirements of advanced aircraft. These findings provide key technical support for the engineering application of power-by-wire flight control systems in advanced aircraft. Full article

The renewable power grid is a complex system with multiple symmetries, in which active power and reactive power play different but symmetrical roles. In weak power grid condition, the virtual synchronous generators (VSGs) are prone to large power angles and high impedance ratios in the transmission lines, leading to severe coupling between active and reactive power. This coupling causes mutual interference between the active and reactive power outputs of the VSG, increasing the dynamic oscillations and prolonging the regulation time. To solve this problem, a power decoupling strategy for VSGs based on active disturbance rejection control (ADRC) is proposed in this paper. The ADRC control decouples the VSG, a dual-input, dual-output coupled system, into two single-input, single-output systems by observing and compensating for disturbances. This approach eliminates the coupling between the VSG’s power loops without considering virtual impedance. Compared with the conventional virtual impedance power decoupling method for VSGs, the proposed ADRC strategy can deal with multi-variable systems with different orders without complex and detailed high-order models, effectively decoupling the active power and reactive power of the VSG and improving the stability of the power grid. Full article

Virtual synchronous generator (VSG) simulates the dynamic characteristics of synchronous generator, offering significant advantages in flexibly adjusting virtual inertia and damping parameters. However, their dynamic stability is susceptible to constraints such as control parameter design, grid disturbances, and the intermittent nature of distributed power sources. This study addresses the degradation of transient performance in traditional sliding mode control for VSG, caused by insufficient multi-parameter cooperative adaptation. It proposes an adaptive sliding mode control strategy based on radial basis function (RBF) neural networks. Through theoretical analysis of the influence mechanism of virtual inertia and damping coefficient perturbations on system stability, the RBF neural network achieves dynamic parameter decoupling and nonlinear mapping. Combined with an integral-type sliding surface to design a weight-adaptive convergence law, it effectively avoids local optima and ensures global stability. This strategy not only enables multi-parameter cooperative adaptive regulation of frequency fluctuations but also significantly enhances the system’s robustness under parameter perturbations. Simulation results demonstrate that compared to traditional control methods, the proposed strategy exhibits significant advantages in dynamic response speed and overshoot suppression. Full article

The increased penetration of power electronics interfaced resources in modern power systems is unlocking new opportunities and challenges. New concepts like multiport converters can further enhance the efficiency and power density of power electronics-based solutions. The triple active bridge is an isolated multiport converter with soft switching and high voltage gain that can integrate different sources, storage, and loads, or act as a building block for modular systems. However, the triple active bridge suffers from power flow cross-coupling, which affects its dynamic performance if it is not removed or mitigated. Unlike the extensive literature on two-port power converters, studies on modeling and control comparison for multiport converters are still lacking. Therefore, this paper presents and compares different modeling and decoupling control approaches applied to the triple active bridge converter, highlighting their benefits and limitations. The converter operation and modulation are introduced, and modeling and control strategies based on the single phase shift power flow control are detailed. The switching model, generalized full-order average model, and the reduced-order model derivations are presented thoroughly, and a comparison reveals that first harmonic approximations can be detrimental when modeling the triple active bridge. Furthermore, the model accuracy is highly sensitive to the operating point, showing that the generalized average model better represents some dynamics than the lossless reduced-order model. Furthermore, three decoupling control strategies are derived aiming to mitigate cross-coupling effects to ensure decoupled power flow and improve system stability. To assess their performance, the TAB converter is subjected to power and voltage disturbances and parameter uncertainty. A comprehensive comparison reveals that linear PI controllers with an inverse decoupling matrix can effectively control the TAB but exhibit large settling time and voltage deviations due to persistent cross-coupling. Furthermore, the decoupling matrix is highly sensitive to inaccuracies in the converter’s model parameters. In contrast, linear active disturbance rejection control and sliding mode control based on a linear extended state observer achieve rapid stabilization, demonstrating strong decoupling capability under disturbances. Furthermore, both control strategies demonstrate robust performance under parameter uncertainty. Full article

Carbon capture and power-to-X are becoming increasingly relevant in the context of decarbonization and supply security. Actinobacillus succinogenes is capable of transforming CO₂ into succinate, whereby product formation is significantly limited by the availability of NADH. The aim of this work was to further develop a bioelectrochemical system (BES) in order to provide additional reduction equivalents and thus increase yield and titer. To this end, a new BES configuration was established. A conventional stirred tank reactor (STR) is coupled via a bypass to an H-cell, in which the redox mediator neutral red (NR) is electrochemically reduced and then returned back to the bioreactor. The indirect electron transfer decouples the electrochemical reduction from the biology and results in increased intracellular availability of NADH. The present approach resulted in an increase in yield from 0.64 g·g⁻¹ to 0.76 g·g⁻¹, corresponding to an increase of 18%. At the same time, a titer of 16.48 ± 0.19 g·L⁻¹ was achieved in the BES, compared to 12.05 ± 0.18 g·L⁻¹ in the control. The results show that the mediator-assisted, partially decoupled BES architecture significantly improves CO₂-based succinate production and opens up a scalable path to the use of renewable electricity as a reduction source in power-to-X processes. Full article

Smart transformers (STs), which are power electronic-based transformers with control and communication capabilities, facilitate managing future distribution grids with distributed generators (DGs) and battery energy storage systems (BESSs). This paper presents a current-fed quadruple active-bridge (CF-QAB) DC–DC converters-based cascaded H-bridge (CHB) ST architecture in which it is easy to coordinate the system-level power transmission and distribution. Compared with the QAB/DAB + Boost baseline, this topology achieves a reduction of approximately 20% in device count. For the core component of the proposed ST architecture, the operation principles are illustrated and the small-signal model is derived. Based on that, the control system obtained by using the individual channel design method is proposed to decouple the highly coupled LV and BESS DC ports, which significantly simplify the control system structure and design process. The experimental results are shown to validate the effectiveness of the proposed DC–DC converter and associated control system. Full article

The optimal control of cooling water systems is of great significance for energy saving in chiller plants. Previously optimal control methods optimize the flow rate, temperature or temperature difference setpoints but cannot control pumps and cooling tower fans directly. This study proposes a direct optimal control method for pumps and fans based on derivative control strategy by decoupling water flow rate optimization and airflow rate optimization, which can make the total power of chillers, pumps and fans approach a minimum. Simulations for different conditions were performed for the validation and performance analysis of the optimal control strategy. The optimization algorithms and implementation methods of direct optimal control were developed and validated by experiment. The simulation results indicate that total power approaches a minimum when the derivative of total power with respect to water/air flow rate approaches zero. The power-saving rate of the studied chiller plant is 13.2% at a plant part-load ratio of 20% compared to the constant-speed pump/fan mode. The experimental results show that the direct control method, taking power frequency as a controlled variable, can make variable frequency drives regulate their output frequencies to be equal to the optimized power frequencies of pumps and fans in a timely manner. Full article