Control Strategy Of Generator Research Articles

Morphological, Molecular, and Pathogenic Characterization of Rhizoctonia solani Isolates Associated with Bean Drying in Northern Sinaloa, Mexico.

Objective: The objective of this study was to characterize, using morphology, DNA sequence analysis, and pathogenicity, R. solani isolates associated with bean plants with root rot symptoms in commercial plots in northern Sinaloa. Design/methodology/approach: During the 2020-2021 cycle, diseased plants infected by Rhizoctonia were collected in the municipalities of Ahome, El Fuerte, and Guasave. Pure fungal isolates were obtained in specific media; which were morphologically characterized in PDA medium and preserved. Subsequently, the pathogenicity of the isolates was evaluated and they were molecularly identified. Genomic DNA was extracted from the isolates, part of the RPB2 gene was amplified by PCR, and the amplified products were sequenced. Results: Phylogenetic analysis with RPB2 sequence data confirmed the identification of 63 isolates as R. solani and allowed them to be assigned to the anastomosis group (AG): AG-4. Of the total isolates analyzed, 86% correspond to the AG-4 HGI anastomosis subgroup and 14% to the AG-4 HGIII subgroup. In pathogenicity, the percentage of germination and severity of the isolates were evaluated, showing different levels of pathogenicity. Limitations of the study/implications: None. Findings/conclusions: Rhizoctonia solani AG-4 anastomosis subgroups HGI and HGIII are associated with bean drying in northern Sinaloa. Therefore, this study will serve as a basis for other studies that generate control strategies for this pathogen.

Study on improved control strategy of virtual synchronous generator

Virtual synchronous generator (VSG) control technology for photovoltaic, energy storage, wind power, and other new energy to provide flexibility in the grid interface characteristics, is conducive to improving the stability of the power system, and has been widely considered by many scholars. Firstly, an improved VSG control method is proposed through simulation and analysis, which realizes the complete decoupling of the frequency response time constant and the inertia quantity of the active power control loop and reduces the complexity of the parameter design of the VSG system. Secondly, to avoid the frequent action of the VSG system caused by small-scale frequency change perturbation, this study proposes a VSG frequency optimization control method for VSG frequency control with rated angular velocity ωset feedforward composed of multivariate factors when considering a primary frequency regulation dead zone. Thirdly, the impact of VSG parameter design on the system is investigated through the system response characteristics of power scheduling, primary frequency regulation at the grid connection, and the small-signal dynamic characterization of the improved VSG. Finally, Simulation and experimental verification yielded an active power overshoot of 7% and a maximum frequency deviation of 0.17 Hz for the improved system. The improved control method resulted in an improvement of 0.1 s in the frequency response time and a reduction of 0.15 Hz in the oscillation amplitude. The response speed of the improved control method is much better, while the oscillation amplitude is reduced to meet the grid's regulation requirements. The simulation and experimental analysis verify the feasibility of the improved VSG control method.

Study of Resistive SFCL for Stability Increase of BTB-VSC-HVDC System Based on Virtual Synchronous Generator Control Strategy

Study of Resistive SFCL for Stability Increase of BTB-VSC-HVDC System Based on Virtual Synchronous Generator Control Strategy

Multi-objective parameter design and economic analysis of VSG-controlled hybrid energy systems in islanded grids

Photovoltaic (PV) systems offer cost-effective power solutions for outlying islands but often compromise system stability due to reduced inertia. This study introduces a Virtual Synchronous Generator (VSG) control strategy, integrated with Energy Storage Systems (ESS) and PV, to enhance system inertia. By optimizing coordination between these energy sources, the proposed method mitigates oscillations and improves grid stability. However, PV-VSG systems are generally not favored by energy providers due to the requirement for pre-curtailment of power output. To address this, the paper proposes a parameter design method for VSG control of ESS and PV, utilizing multi-objective genetic algorithm (MOGA) optimization to simultaneously increase the frequency nadir and minimize the settling time after disturbances. Additionally, an adaptive curtailment decision and parameter design method based on artificial neural networks is introduced to enhance the feasibility of PV-VSG systems by reducing PV pre-curtailment and prioritizing PV power release and ESS charging during frequency oscillations. Real data from the Penghu Archipelago in Taiwan are used to build a dynamic model in DIgSILENT, enabling interaction with MOGA. The Value at Risk (VaR) method with dual stochastic variables is employed to assess the allowable PV installed capacity. The results show that when VaR is set at 1%, the proposed PV-VSG method can increase PV penetration by 57.5% compared to scenarios without VSG. Furthermore, compared to traditional PV-VSG methods, the proposed approach achieves a 16.8% increase in PV penetration and reduces annual PV curtailment by 25 MWh. This study also evaluates the economic impact of planners choosing different risk levels, offering valuable insights for grid development in remote or island regions.

Modelling and dynamic characteristics of wind turbine drivetrain based on the variable coefficient sliding mode controller

Vibration is inevitable in operation of mechanical equipment, but severe vibrations will cause serious harm to wind turbines (WTs). This paper takes the drivetrain of 8 MW WT as the object, established a multi-body electromechanical coupling model of WT and verified the accuracy of the established model through the WT drivetrain in the laboratory. Subsequently, based on this model, time-frequency domain analysis was conducted on the vibration response of the WT drivetrain under different control strategies of the generator, and the influence of the generator control strategy on the vibration of the drivetrain was studied. The result shows that the generator control strategy has a significant impact on the vibration response amplitude of the drivetrain, but has a relatively small impact on the frequency component. Meanwhile, the sliding mode controller designed in this paper has good anti-interference ability, which can make the system quickly reach dynamic stability, and effectively suppress the vibration of the main components in the drivetrain. Under the new controller’s control, the transverse vibration displacement of some parts of the WT drivetrain can be reduced by up to nearly 60 %. This paper provides new ideas and new methods for the active vibration reduction control of WT drivetrain.

Evaluation of advanced control strategies for PMSG in wind turbines: backstepping fuzzy logic control and adaptive neural network control approaches

This study presents a comparative analysis of two advanced control strategies for Permanent Magnet Synchronous Generators (PMSGs) in wind turbines: Backstepping Fuzzy Logic Control and Adaptive Neural Network Control. The aim is to evaluate their effectiveness in handling structured and unstructured uncertainties and enhancing system performance. Backstepping Fuzzy Logic Control integrates backstepping techniques with fuzzy logic regulation to improve flexibility and robustness. This method addresses the limitations of traditional PI controllers by enhancing adaptability to parameter variations and external disturbances. In contrast, Adaptive Neural Network Control employs neural networks with dynamic compensators to address high uncertainties and nonlinearities, aiming to surpass the performance of conventional PI controllers. The study involves simulations to compare these control strategies based on several criteria: robustness in managing parameter changes and external disturbances, flexibility in adapting to dynamic conditions, and overall performance including efficiency and stability. Simulation results indicate that both strategies offer significant improvements over traditional PI controllers. Backstepping Fuzzy Logic Control demonstrates strong adaptability and robustness, while Adaptive Neural Network Control shows superior efficiency and optimality, particularly in high-uncertainty environments. This comparative analysis provides insights into the strengths and limitations of each approach, offering guidance for selecting the most suitable control strategy based on specific operational requirements. The findings contribute to advancing control methodologies in wind energy systems and suggest directions for future research and practical implementation.

A heuristic-fuzzy improved virtual synchronous generator control strategy for charging station frequency regulation

To make use of charging station (CS) frequency regulation (FR) capability to get a better FR effect, a CS virtual synchronous generator (VSG) frequency control strategy based on the heuristic-fuzzy logic controller (FLC) is proposed in this paper. First, a CS VSG control architecture with heuristic-FLC is designed. Second, considering electric vehicle (EV) users' charging demands, a CS FR capability evaluation model based on the constant current-constant voltage (CC-CV) charging process and a V2G power response model based on frequency up/down-regulation participation factor are designed. Furthermore, a heuristic-FLC optimized by genetic algorithm (GA) is designed to improve the FR effect of the VSG control strategy. Simulation results show that the proposed strategy can make full use of the CS FR capability and get a better FR effect. In addition, the V2G power response model proposed in this paper can achieve the orderly responses of EVs in a CS under different scenarios.

Fault Characterization for AC/DC Distribution Networks Considering the Control Strategy of Photovoltaic and Energy Storage Battery

In order to cope with the failure of existing fault analysis schemes for AC/DC distribution networks with a high proportion of distributed generations, this paper proposes a fault characteristic analysis method for AC/DC distribution networks that considers the influence of distributed generation control strategies. Firstly, a transient model for the AC/DC distribution network connected to distributed generations is built. Then, the fault characteristics of the AC/DC distribution network in different stages, such as the capacitor discharge stage, inductive renewal stage, and steady state stage, is analyzed. Finally, detailed simulation analysis is conducted using PSCAD/EMTDC to validate the effectiveness of the developed scheme by the superior approximation performance between simulated curves and calculated curves.

Virtual synchronous generator control with parameters optimization based on new WaOA algorithm for grid-feeding inverters

The widespread integration of renewable energy sources (RESs) within traditional power systems causes a considerable impact, such as a decrease in total inertia, damping properties, and large frequency deviation. To tackle this issue, numerous research have been proposed to introduce the virtual synchronous generator (VSG) control strategy as an effective solution applied to power electronics inverters operating in grid-forming or grid-feeding control modes. However, the proper tunning of the inertia and damping parameters is considered as a significant challenge to ensure the system stability and reliability. In this paper, an efficient meta-heuristic Walrus Optimization Algorithm (WaOA) -based VSG control intended for grid-feeding inverters within a weak grid is proposed. The objective of this work is to offer a proper tuning of the VSG parameters, thereby improving the dynamic characteristics of the microgrid (MG) and guaranteeing a stable operation. In addition, it highlights the adopted optimization technique which is introduced on VSG control while ensuring minimum objective function value. Through offline simulations in MATLAB/Simulink, the superiority of the suggested WaOA method is first confirmed, in which it offers the lowest Integral Square Error (ISE) fitness function value of 0.026, compared to the Mountain Gazelle Optimizer (MGO) and Tunicate Swarm Algorithm (TSA) with 0.027 9 and 0.0281, respectively. Second, the performance of the WaOA-based VSG control is compared to the ones based on MGO and TSA techniques under active and reactive power variations. The obtained results demonstrate that the proposed VSG control ensures a better transient performance, especially in terms of under and overshoots.

Structural Design and Control Research of Multi-Segmented Biomimetic Millipede Robot.

Due to their advantages of good stability, adaptability, and flexibility, multi-legged robots are increasingly important in fields such as rescue, military, and healthcare. This study focuses on the millipede, a multi-segmented organism, and designs a novel multi-segment biomimetic robot based on an in-depth investigation of the millipede's biological characteristics and locomotion mechanisms. Key leg joints of millipede locomotion are targeted, and a mathematical model of the biomimetic robot's leg joint structure is established for kinematic analysis. Furthermore, a central pattern generator (CPG) control strategy is studied for multi-jointed biomimetic millipede robots. Inspired by the millipede's neural system, a simplified single-loop CPG network model is constructed, reducing the number of oscillators from 48 to 16. Experimental trials are conducted using a prototype to test walking in a wave-like gait, walking with a leg removed, and walking on complex terrain. The results demonstrate that under CPG waveform input conditions, the robot can walk stably, and the impact of a leg failure on overall locomotion is acceptable, with minimal speed loss observed when walking on complex terrain. The research on the structure and motion control algorithms of multi-jointed biomimetic robots lays a technical foundation, expanding their potential applications in exploring unknown environments, rescue missions, agriculture, and other fields.

The application of virtual synchronous generator technology in inertial control of new energy vehicle power generation

Introduction: With the rapid development of human society and economy, the power generation technology of various new energy vehicles has begun to receive widespread attention.Methods: Due to the lack of inertia and frequency stability in the new energy vehicle power generation system, this paper proposes a power generation control method that combines linear active disturbance rejection control technology and virtual synchronous generator technology. This method first introduces the control strategy and inertial response of the virtual synchronous generator. Then, it uses linear active disturbance rejection control technology to improve the virtual synchronous generator technology to deal with the uncertainty and external interference in the system.Results: The results showed that when the virtual inertia coefficient was 0, and the new energy vehicles would hardly intervene in the regulation of the grid voltage. When the virtual inertia coefficient was 5, the decline rate of the DC bus voltage of new energy vehicles had slowed down. When the virtual inertia coefficient increased, the power output of new energy vehicles can be increased to the grid. When the load suddenly increased, and the corresponding DC bus voltage decreased more slowly. In the VSG output power comparison, under the research method, the frequency fluctuation only increased by 0.09 Hz and returned to the rated frequency of 50 Hz. Additionally, the dynamic process of the system output power was the shortest, lasting only 0.05 s.Discussion: The above results show that the research method has significant superiority and effectiveness in improving the inertial response and overall stability of the new energy vehicle power system.

Modified time domain randomization technique for multi-shaker non-stationary non-Gaussian random vibration control

Traditional random vibration environmental tests simulate stationary Gaussian random vibration environments. In this work, the generation and closed-loop control of multi-shaker non-stationary non-Gaussian random vibration signals with the modified time domain randomization technique are studied. The amplitude modulation function is introduced to control the non-stationary and non-Gaussian characteristics that the root mean square value of the generated signal changes with time. The kurtosis relationship between the one frame pseudo-random signal and consecutive true random signal is derived theoretically. It is found that the kurtosis of the consecutive non-stationary random signal is determined by the amplitude modulation function and kurtosis of the pseudo-random signal. The standard deviation of the time-varying root mean square reflects the non-stationary characteristics of the generated signal. A control strategy for multi-shaker non-stationary non-Gaussian random vibration environmental test is proposed. The non-stationary and non-Gaussian characteristics are extracted from the measured response signals so that the power spectral densities, kurtoses and non-stationary characteristics can be controlled simultaneously. The results from the simulation examples and multi-shaker vibration experiments prove the feasibility and practicability of the proposed non-stationary non-Gaussian random signal generation method and control strategy.

Generalized Predictive Control of the Active and Reactive Stator Powers of the DFIG for Wind Energy Generation

This paper proposes a Generalized Predictive Control (GPC) strategy for Wind Power Generation (WPG) based on a doubly fed induction generator (DFIG). The objective is to study and apply a robust active and reactive power control strategy based on GPC of the DFIG, this is likely to optimize the energy production and improve the quality of the energy produced. In order to maximize the amount of WPG taken even when the turbine is uncertain or the wind speed varies abruptly, the design is built utilizing the Maximum Power Point Tracking (MPPT) theory. Through numerical modeling with the aid of the Matlab/Simulink software, the predictive control (GPC) of the active and reactive stator powers of the DFIG was validated. A comparison between the GPC of the GADA and the indirect method based on a typical PI controller is developed in order to illustrate the viability of the suggested method. According to the simulation results of this comparison, the suggested method is viable and has promising results.

A novel virtual synchronous generator control scheme of DFIG-based wind turbine generators based on the rotor current-induced electromotive force

This paper focuses on the research of virtual synchronous generator (VSG) control technology for the doubly-fed induction generator (DFIG)-based wind turbines. The key for DFIG VSG operation is to construct an internal electromotive force (EMF) with the virtual rotor motion characteristic in the stator. The existing control schemes use the rotor or mutual flux-induced EMF as the internal EMF. Since the flux corresponds to a composite magnetic field generated together by the stator and rotor current. Any variations in the stator current caused by external disturbances will reflect on the rotor current to keep the flux constant. The rotor overcurrent is inevitable under a large external disturbance, threatening the safety of the rotor-side converter (RSC). Moreover, the flux is immeasurable. The accurate flux control depends on flux observers, increasing the complexity; while the control without observers cannot ensure the effectiveness, leading to control failure. To address these problems, a novel DFIG VSG control scheme with the rotor current-induced EMF as the internal EMF is proposed in this paper. The internal EMF is corresponded to the single magnetic field generated only by the rotor current. This can lead to the following benefits: the rotor current will not vary with the stator current and can be limited under large external disturbances, ensuring the safety of the RSC; the rotor current can be directly measured without the need for extra observers, reducing the difficulty of control implementations; the underlying controlled vector is unified with the traditional grid-following DFIG, favoring the retrofit of the installed DFIGs. Compared to the existing schemes, this scheme has a larger equivalent internal impedance. An additional rotor current-terminal voltage magnitude droop control is added to effectively restrain the problems brought by this larger impedance. Simulation and analysis results demonstrate that the proposed DFIG VSG control scheme effectively addresses problems in the existing schemes. Moreover, the results also exhibit that the scheme has a robust adaptability across a wide range of short-circuit ratios and possesses the grid-forming ability independent of SGs.

Adaptive transient overvoltage control strategy for wind farm based on data‐driven

AbstractTo achieve the transient overvoltage suppression of doubly fed induction generator (DFIG) terminals and the point of common coupling (PCC) in the wind farm (WF), an adaptive overvoltage control strategy based on data‐driven approach is proposed. Firstly, the PCC reactive power demand and DFIG overvoltage threshold are derived, respectively. Secondly, three regression models are developed through surface fitting to determine three variables: the maximum overvoltage of each DFIG, the PCC maximum overvoltage, and the reactive power demand of each DFIG. Subsequently, the K‐means clustering method is adopted to group all DFIGs, and then the reactive power requirement of the PCC is proportionally distributed to each group of DFIGs. Lastly, a coordinated control strategy of DFIGs and static var generator (SVG) is designed based on the values of three regression models, which can adaptively adjust the reactive power absorbed by each DFIG and SVG. In particular, the de‐load control is adopted to enlarge the maximum reactive power capacity of DFIG. The simulation results show that the proposed control strategy can timely and effectively restore the transient overvoltage of the wind farm to the normal range during the gird failure, ensuring the stable operation of the wind farm.

Angle Position Compensation Control Strategy for High-Speed Power Generation of Aerospace Integrated Switched Reluctance Starting/Generating System

Angle Position Compensation Control Strategy for High-Speed Power Generation of Aerospace Integrated Switched Reluctance Starting/Generating System

Applying a 2 kW Polymer Membrane Fuel-Cell Stack to Building Hybrid Power Sources for Unmanned Ground Vehicles

The novel constructions of hybrid energy sources using polymer electrolyte fuel cells (PEMFCs), and supercapacitors are developed. Studies on the energy demand and peak electrical power of unmanned ground vehicles (UGVs) weighing up to 100 kg were conducted under various conditions. It was found that the average electrical power required does not exceed ~2 kW under all conditions studied. However, under the dynamic electrical load of the electric drive of mobile robots, the short peak power exceeded 2 kW, and the highest current load was in the range of 80–90 A. The electrical performance of a family of PEMFC stacks built in open-cathode mode was determined. A hydrogen-usage control strategy for power generation, cleaning processes, and humidification was analysed. The integration of a PEMFC stack with a bank of supercapacitors makes it possible to mitigate the voltage dips. These occur periodically at short time intervals as a result of short-circuit operation. In the second construction, the recovery of electrical energy dissipated by a short-circuit unit (SCU) was also demonstrated in the integrated PEMFC stack and supercapacitor bank system. The concept of an energy-efficient, mobile, and environmentally friendly hydrogen charging unit has been proposed. It comprises (i) a hydrogen anion exchange membrane electrolyser, (ii) a photovoltaic installation, (iii) a battery storage, (iv) a hydrogen buffer storage in a buffer tank, (v) a hydrogen compression unit, and (vi) composite tanks.

Optimal wind power generation system by honey badger algorithm with differential evolution strategies

The purpose of this study is to build an optimal hybrid wind power system consisting of a permanent magnet direct-drive wind power generation unit, a hybrid energy storage system (HESS), a power electronic converter, and loads. Moreover, a reasonable control method is designed for each part, and a honey badger algorithm (HBA) with differential evolution strategies is employed to realize the coordinated control of each unit and improve the system stability. The real anti-interference capability of wind power system can be improved by the proposed HBA with differential evolution strategies (IHBA). Firstly, the wind hybrid system model is constructed, in which the wind power generation unit adopts the variable step climbing method to achieve the maximum power point tracking control; the HESS designs the power distribution method based on the bus voltage; the converter supplying energy to the AC load introduces the virtual synchronous generator (VSG) control strategy. Secondly, due to the existence of energy exchange in each unit of the system, VSG has more parameters and its control performance is influenced by the system itself, this study proposes HBA with differential evolution strategies for system parameter optimization and constructs an IHBA-VSG model with the objective of minimizing the bus voltage fluctuation value. The IHBA improves original honey badger algorithm by three mechanisms which are time control function, Gaussian variation factor and differential evolution strategy. Finally, the parameters obtained from the HBA with differential evolution strategies optimization search are substituted into the wind hybrid system, and the simulation system is built by MATLAB/Simulink. The simulation results show that when the environment of the system changes or the load on the AC side changes abruptly, the proposed control method can reduce the bus voltage fluctuation by 2.9%− 18.22% compared with the honey badger algorithm Optimized VSG (HBA-VSG), and can reduce the bus voltage fluctuation by 5.09%− 17.98% compared with the traditional droop control without considering the system interaction. This study can effectively improve the stability of wind power generation system and promote the development of new energy industry.

Review of Mechanisms and Suppression Methods for Low-Frequency Pressure Fluctuations in Open-Jet Wind Tunnels

Low-frequency pressure fluctuations are common in open-jet wind tunnels, affecting test accuracy and posing safety risks to the wind tunnels. These oscillations can be caused by different mechanisms in different wind tunnels, and it is often necessary to identify the specific mechanism responsible for the oscillation and develop appropriate control methods. This paper presents a comprehensive review of the current state of research on low-frequency pressure fluctuations in subsonic open-jet wind tunnels, with a particular emphasis on their generation mechanisms and control strategies. The primary source of excitation is attributed to the edgetone feedback formed by the impingement of the jet on the collector. The sound wavelength corresponding to the edgetone frequency is close to that of the plenum scale, facilitating resonance with both plenum-associated vibration modes and specific-order standing wave modes within the circuit loop, resulting in significant low-frequency pulsations. Passive control methods such as nozzle vortex generators and collector breathing gaps have been extensively employed due to their cost-effectiveness and efficiency. The concluding section highlights some unresolved issues that require further investigation in this field.

Transient stability analysis of a grid-connected type-4 wind turbine with grid-forming control during the fault

Thanks to the ability of the inertia provision and the voltage support, the virtual synchronous generator with reactive power control (RPC) is a promising solution among various grid-forming control schemes. This paper analyzes the transient angle stability of the grid-connected type-4 wind turbine with virtual synchronous generator and reactive power control strategy during the fault. By deriving the analytical criterion with the transient energy function, various key factors on the transient stability of the system can be revealed comprehensively and jointly. Additionally, the impacts of the integral coefficient of the RPC and the power reference switching delay on the transient stability are also analyzed by plotting the phase portraits of the derived third-order large-signal model of the grid-connected wind turbine system. The analytical result can be helpful for the determination of the parameters of the grid-connected wind turbine in order to keep transient stable and keep connected with the grid during the fault. Finally, the robustness and the effectiveness of the theoretical analysis results are validated by the electromagnetic transient simulation in MATLAB/Simulink under various conditions.