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An iterative tuning method for multi-band power system stabilizers is proposed, which utilizes the contoured controller Bode (CCBode) plot. The typical multi-band power system stabilizer, PSS4B, is conceptualized as a series connection of two filters: a band-pass filter and a phase compensator. The tuning process involves a space searching approach for the phase compensator to ensure its phase–frequency response remains within acceptable bounds. Subsequently, the CCBode plot is employed to adjust the magnitude–frequency response of the band-pass filter, thereby enhancing stability performance across a broad frequency range. The method proposed can be applied to the parameter design of the multi-band power system stabilizer PSS4B in the power system to suppress the low-frequency oscillations of the local mode and inter-regional mode in the system. The effectiveness of this proposed method is demonstrated through case studies of the four -machine/two-area system and the North China Power Grid. [ABSTRACT FROM AUTHOR]

For noise reduction at a low-to-moderate Reynolds number, airfoil trailing-edge tonal noise has multiple prominent tones. Among these tones, secondary tones are greatly influenced by external disturbances such as oscillations commonly in the environment. In previous experiments, the spatial movement of sources was found to be related to an inherent high-frequency oscillation. Therefore, the spatial influence of external low-frequency oscillations was investigated in this study. By using tripping tapes to construct different symmetry source regions on the pressure side with side secondary tones, a transient spatial analysis of an NACA0012 airfoil at 2 degrees was performed by microphone arrays when a 10 Hz pressure oscillation was significant at 24 m/s. Temporally, this 10 Hz periodic strength change became more intense at a broader frequency bandwidth for a longer source region. Furthermore, a substantial time delay, significantly larger than the sound propagating time difference between microphones, was observed exclusively along the spanwise direction. This delay led to a periodic directivity pattern, particularly when two 0.2 m source regions were separated by a 0.2 m or 0.4 m tripping region. This low-frequency oscillation introduces an asymmetric transient switching pattern for symmetric spanwise source regions. Consequently, the response of airfoils to external oscillations in field tests should be considered. [ABSTRACT FROM AUTHOR]

This paper investigates an optimal methodology for mitigating low-frequency oscillation concerns in power systems. The study explores the synergistic integration of a power system stabilizer (PSS) and a flexible alternating current transmission system (FACTS) to formulate an intelligent controller. A comprehensive analysis encompasses various PSS design strategies, including lead-lag (LL), proportional-derivative-integral (PID), and fractional-order proportional-integral-derivative (FOPID) controllers. The FACTS device selected for this investigation is a static VAR compensator (SVC), highlighting the exceptional efficacy of FOPID-based PSS over alternative strategies with a power oscillation damper. The study extends its scope to encompass a comparative assessment of two distinct optimization algorithms: the moth flame optimization (MFO) and the antlion optimization (ALO). The research is conducted using a single-machine infinite bus power system (SMIB) as the case study platform. A total of four diverse test scenarios are executed under varying operating conditions. The evaluation of the developed method employs six distinct performance indices to investigate the developed controller thoroughly. The outcomes reveal that the MFO-optimized FOPID-PSS and SVC controller outperforms other control schemes. This optimized configuration demonstrates substantial improvements across all performance indices. These findings underscore the superior capabilities of the proposed approach in enhancing power system stability and performance. [ABSTRACT FROM AUTHOR]

The low-frequency oscillation (LFO) has occurred in the train–network system due to the introduction of the power electronics of the trains. The modeling and analyzing method in current researches based on electrified railway unilateral power supply system are not suitable for the LFO analysis in a bilateral power supply system, where the trains are supplied by two traction substations. In this work, based on the single-input and single-output impedance model of China CRH5 trains, the node admittance matrices of the train–network system both in unilateral and bilateral power supply modes are established, including three-phase power grid, traction transformers and traction network. Then the modal analysis is used to study the oscillation modes and propagation characteristics of the unilateral and bilateral power supply systems. Moreover, the influence of the equivalent inductance of the power grid, the length of the transmission line, and the length of the traction network are analyzed on the critical oscillation mode of the bilateral power supply system. Finally, the theoretical analysis results are verified by the time-domain simulation model in MATLAB/Simulink. [ABSTRACT FROM AUTHOR]

Unmanned sailboats, harnessing wind for propulsion, offer great potential for extended marine research due to their virtually unlimited endurance. The sails typically operate at high attack angles, which contrasts with aircraft that maintain small angles to prevent stalling. Despite the reduction in lift during stalling, the resultant increase in drag contributes significantly to the sail's thrust. However, the sail often experiences vortex shedding due to high attack angles, leading to low-frequency oscillations and erratic navigation. This study employs large-eddy simulations (LESs) on a 3D NACA0012 sail at a Reynolds number of 3.6 × 105, which is validated by experimental data. It observes the lift and drag coefficients across attack angles from 5 to 90 degrees and compares these with a Dynarig sail. The findings reveal that higher attack angles amplify fluctuations in lift and drag coefficients. Vortex shedding, resulting from flow separation, creates pressure changes and oscillations in aerodynamic forces. Fast Fourier transformation (FFT) analysis identifies dominant frequencies between 0.5 and 10 Hz, indicating low-frequency oscillations. The study's insights into the impact of attack angle and sail type on the oscillation frequency are favorable for the design of unmanned sailboats, aiding in the prediction of wind-induced frequencies and optimal attack angle determination. [ABSTRACT FROM AUTHOR]

Copyright of Electric Machines & Control / Dianji Yu Kongzhi Xuebao is the property of Electric Machines & Control and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The large-scale wind power grid connection will change the power distribution between the original system tide and synchronous machine, and the interaction between wind turbine and synchronous machine affects the system's damping oscillation characteristics. Traditional synchronous generators' extra damping control provides an important means for DFIG to improve system damping characteristics. Different types of PSS have different suppression effects on low-frequency oscillations. In this paper, four types of IEEE PSS models are built in DIGSILENT/PowerFactory to study the suppression effects of DFIG additional different types of PSS on low-frequency oscillations of power systems, and the suppression effect of four types of PSS on system low-frequency oscillation after connecting to the DFIG reactive power control loop is compared and analyzed from two perspectives: eigenvalue and time-domain simulation. The MRAC control principle is used to improve PSS4B, and the total least squares-estimation of signal parameters via rotational invariance technique identification method is used to obtain the system transfer function, and the controller parameters are calculated in real time using the adaptive law based on the gradient approach. Finally, the MRAC–PSS4B is connected to the DFIG rotor-side controller's reactive power control loop, and the improvement effect of the designed MRAC–PSS4B controller on the power system's low-frequency oscillation characteristics under different contact line transmission power is confirmed. [ABSTRACT FROM AUTHOR]

Abstract The low-frequency oscillation (LFO) has occurred in the train–network system due to the introduction of the power electronics of the trains. The modeling and analyzing method in current researches based on electrified railway unilateral power supply system are not suitable for the LFO analysis in a bilateral power supply system, where the trains are supplied by two traction substations. In this work, based on the single-input and single-output impedance model of China CRH5 trains, the node admittance matrices of the train–network system both in unilateral and bilateral power supply modes are established, including three-phase power grid, traction transformers and traction network. Then the modal analysis is used to study the oscillation modes and propagation characteristics of the unilateral and bilateral power supply systems. Moreover, the influence of the equivalent inductance of the power grid, the length of the transmission line, and the length of the traction network are analyzed on the critical oscillation mode of the bilateral power supply system. Finally, the theoretical analysis results are verified by the time-domain simulation model in MATLAB/Simulink.

Power electronic traction transformers (PETTs) will be increasingly applied to locomotives in the future for their small volume and light weight. However, similar to conventional trains, PETTs behave as constant power loads and may cause low-frequency oscillation (LFO) to the train-network system. To solve this issue, a mathematical model of the PETT is firstly proposed and verified based on the extended describing function (EDF) method in this paper. In the proposed model, the LLC converter is simplified to an equivalent circuit consisting of a capacitor and a resistor in parallel. It is further demonstrated that the model can apply to various LLC converters with different topologies and controls. Particularly, when the parameter differences between cells are not obvious, the PETT can be simplified to a single-phase rectifier (i.e., conventional train) by equivalent transformation. Based on the model of PETT, the system low-frequency stability and influential factors are analyzed by using the generalized Nyquist criterion. Lastly, the correctness and accuracy of theoretical analyses are validated by off-line and hardware-in-the-loop simulation results.

The identification of poorly damped low-frequency oscillations (LFOs) is very crucial for maintaining small signal stability in power systems. The Total least square estimation of signal parameters via rotational invariance techniques (TLS-ESPRIT) is a model parameter estimation method, which works efficiently even in noisy conditions. However, the TLS-ESPRIT requires prior information about the number of modes present in the signal. Different techniques are proposed in the literature for model order (MO) estimation of signal, but they consider presumed tolerance value for the selection of probable separation boundary between two subspaces. As tolerance value fluctuates with noise level, these techniques become inefficient and harder to automate for online estimation. So, the main contribution of the proposed work is to design an efficacious MO estimation technique, which will efficiently eliminate the requirements of tolerance value to overcome the aforementioned limitations. So, in this proposed work, a sequential partitioning technique known as Partitioning Around Medoids (PAM) is adopted for the precise estimation of LFOs order of Phasor measurement unit (PMU) data. The MO estimation is done by separating the prominent eigen values of autocorrelation matrix (ACM) iteratively into two components i.e signal subspace and noise subspace. Since the PAM algorithm operates in two layers of clustering and robust towards high variance noise, hence the insignificant eigen values are hindered from getting clustered in the signal subspace. The robustness of the proposed technique is validated by conducting comparative study with Exact Model Order (EMO), modified sequential cumulative sum (modified-SCUSUM) and sequential eigen value contribution (SEVC) methods for synthetic signals, two area test system, practical probing data of Western Electricity Coordinating Council (WECC) system and oscillatory power data of WSCC 9 bus system simulated on Real Time Digital Simulator (RTDS). [ABSTRACT FROM AUTHOR]

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Since low-frequency oscillation seriously threatens the safe operation of the power system, the power system stabilizer (PSS) can effectively suppress the oscillation. In this paper, a hybrid parameter optimization method combining the moth-flame optimization (MFO) algorithm and fuzzy logic controller (FLC) is proposed to address the problem of poor adaptability of the parameter tuning method in the conventional power system stabilizer (CPSS). This method can optimize the parameters of PSS in different processes. Initially, the optimal parameters of PSS under the current perturbation are given by the MFO algorithm. During the online operation of the system, as perturbation changes, the parameters of the PSS will also be adaptively tuned by the FLC in real-time when the system operating conditions change. According to this method, a fuzzy adaptive proportional–integral–differential (FPID) controller is designed based on the moth-flame optimization algorithm (MFO-FPID), and it is used as PSS to improve dynamic stability performance during oscillation. Moreover, its parameters can be adaptively adjusted in different perturbation scenarios. The designed MFO-FPID controller is applied to the single machine infinite bus (SMIB) power system to compare the dynamic performance with other controllers, that is, proportional–integral–differential (PID) and CPSS. The result shows that the MFO-FPID controller can suppress the oscillation very well, and the control effect is the best. [ABSTRACT FROM AUTHOR]

The summer precipitation over Yangtze River Basin(YRB)are closely related to the low-frequency oscillations at mid-high latitude over Eurasia, so quantitatively diagnosing the contribution of the circulation anomalies at different scales to precipitation is of great significance in improving the prediction accuracy of droughts and floods. Based on ERA5 daily reanalysis data and CN05.1 daily precipitation data, a circulation index(CI)is defined to classify the summer Eurasian circulation into double-ridge(DR)type and double-trough(DT)type, and the low-frequency oscillation characteristics and the impact of different scales circulation anomalies on precipitation over YRB were investigated. The results show that DR and DT types reflect the different phases of the same low-frequency oscillation cycle of CI, which both have a dominant periodicity of 10-30 days and exert substantial influences on precipitation over YRB. The main results are as follows: Both two types exhibit a wave train with alternating positive and negative low-frequency height anomalies at 500 hPa over Eurasian mid-high latitude and propagates eastward at the speed of 5°(longitudes)per day; when DR type reaches the peak phase, the northeastern winds at 850 hPa from the north of low-frequency anticyclone over Okhotsk Sea are conducive to the invasion of dry and cold air from mid-high latitude area to YRB, which converges with the southwestern winds from the west of anticyclone over South China Sea, leading to the transportation of water vapor from South China Sea and Pacific to YRB and the strongest low-frequency precipitation lagging circulation 2 days, which is opposite to the DT type; the impact of Eurasian circulation on low-frequency precipitation over YRB is dominated by the background water vapor(greater than 30 days)and low-frequency circulation(10-30 days), followed by the synoptic-scale circulation(less than 10 days)and the background circulation(greater than 30 days), respectively. The contribution of moisture convergence term is about 3 times larger than that of moisture advection term, indicating that the wet advection leads to sufficient moisture conditions, and then precipitation is produced through strong moisture convergence. [ABSTRACT FROM AUTHOR]

An iterative tuning method for multi-band power system stabilizers is proposed, which utilizes the contoured controller Bode (CCBode) plot. The typical multi-band power system stabilizer, PSS4B, is conceptualized as a series connection of two filters: a band-pass filter and a phase compensator. The tuning process involves a space searching approach for the phase compensator to ensure its phase–frequency response remains within acceptable bounds. Subsequently, the CCBode plot is employed to adjust the magnitude–frequency response of the band-pass filter, thereby enhancing stability performance across a broad frequency range. The method proposed can be applied to the parameter design of the multi-band power system stabilizer PSS4B in the power system to suppress the low-frequency oscillations of the local mode and inter-regional mode in the system. The effectiveness of this proposed method is demonstrated through case studies of the four -machine/two-area system and the North China Power Grid.

Estimation of electromechanical mode properties is crucial in modern power systems for providing the operators with an adequate indication of the stress in the system. Measurement-based approaches use signal processing algorithms for mode identification and parameter estimation. This paper presents a novel framework for the assessment of low-frequency oscillation modes using real-world synchrophasor data with minimum computational effort. A nonstationary approach known as Time-Varying Filter based Empirical Mode Decomposition (TVF-EMD) technique is used to identify the dominant low-frequency modes present in the ambient PMU data. The combination of TVF-EMD with Teager Kaiser Energy Operator (TKEO) precisely estimates the instantaneous mode parameters, such as frequency, amplitude, and damping ratio. The efficacy of the proposed approach is demonstrated by applying it in a synthetic signal, simulated data of a standard IEEE test system, and in real-world PMU data of the Indian power grid. The proposed method is compared with the existing methodologies and the observations reveal that the proposed method has robust performance in estimating the instantaneous mode features in the power system with less computational complexities. • Oscillatory mode assessment in power systems using real world synchrophasor measurement. • Time Varying Filter based EMD (TVF-EMD) approach is used to identify the oscillatory modes assisted with Teager Kaiser Energy Operator (TKEO). • The proposed method is compared with the existing nonstationary algorithms like Variational mode decomposition and Empirical mode decomposition. • Verified with synthetic data, simulation data from a IEEE 16 machine 68 bus standard system and recorded PMU measurement from Indian Power Grid. [ABSTRACT FROM AUTHOR]

Regional persistent extreme cold events are meteorological disasters that cause serious harm to people's lives and production; however, they are very difficult to predict. Low-temperature weather systems and their effects have a significant low-frequency oscillation period (10–20 d and 30–60 d). This paper uses deep learning to analyze the extended-range time scale and predict regional persistent extreme cold events. The dominant low-frequency oscillation components of cold events are obtained via wavelet transform and Butterworth filtering. The low-frequency oscillation component is decomposed via empirical orthogonal function decomposition to extract the main spatial mode and time coefficient. A convolutional neural network is used to establish the correlation between large-scale circulations and the time coefficient of the low-frequency oscillation component of the lowest temperature. The proposed deep learning model exhibits good prediction accuracy for regional persistent extreme cold events with low-frequency oscillations. [ABSTRACT FROM AUTHOR]

This paper investigates the potential capability of recently proposed flexible power transmisssion device, namely, variable frequency transformer (VFT), to effectively mitigate low‐frequency oscillations (LFOs). VFT with a high rotational inertia has an inherent natural damping capacity that may be utilized to attenuate power system oscillations. To provide additional system damping, a comprehensive approach is presented, which integrates the coordination of VFT with superconducting magnetic energy storage (SMES). An intelligently designed novel cascaded lead‐lag fuzzy logic controller (CLLFLC) utilizing a global stabilizing control signal constitutes the supervisory controller for VFT and SMES. The stabilizing feedback signal that contains information about overall system dynamics can be easily obtained through wide area measurement systems (WAMS) and is determined using participation factor (PF) analysis. In addition, a newly developed optimization technique known as K‐means optimizer (KO) is used for optimizing CLLFLC parameters utilized for the carefully orchestrated operation of VFT and SMES. Numerous simulation studies are conducted on two‐area multigenerator interconnected network to validate the resilience of the suggested approach. The findings demonstrate that the proposed control strategy with optimized gain parameters efficaciously damped the LFOs. To show the superior damping effectiveness of the suggested KO‐CLLFLC controller, a comparative performance evaluation with a damping controller designed on residue approach was also undertaken. [ABSTRACT FROM AUTHOR]

Aiming at the problem of weakly or negatively damped low-frequency oscillations caused by cross-zone transmission of electricity from large wind farms, this paper proposes a fast terminal sliding-mode additional damping controller based on the Lyapunov stability theory. By investigating the flexible power regulation characteristics and the capability of dynamic frequency response to damping regulation of doubly-fed wind turbines (DFIG), a rotor magnetic chain controller is designed according to the relationship between the applied voltage and magnetic chain of DFIG rotor and the sliding mode variable structure control method. When low-frequency oscillations occur in the system, the desired magnetic chain value will deviate from the actual magnetic chain value. The additional damping controller outputs an adaptive control signal for the rotor-side power control link to increase the active output of the wind farm and suppress low-frequency oscillations in the system. A simulation model of the wind power grid-connected system is established in MATLAB/Simulink for off-line simulations, and a real-time simulation experiment of a large wind farm cross-zone transmission model based on real time digital simulation system is conducted. The results of both off-line and real-time simulations show that when low-frequency oscillations occur in the system, the proposed control method can quickly regulate the active power emitted by the DFIG and enhance the damping level of the system, which is effective in suppressing low-frequency oscillations in the system.

For noise reduction at a low-to-moderate Reynolds number, airfoil trailing-edge tonal noise has multiple prominent tones. Among these tones, secondary tones are greatly influenced by external disturbances such as oscillations commonly in the environment. In previous experiments, the spatial movement of sources was found to be related to an inherent high-frequency oscillation. Therefore, the spatial influence of external low-frequency oscillations was investigated in this study. By using tripping tapes to construct different symmetry source regions on the pressure side with side secondary tones, a transient spatial analysis of an NACA0012 airfoil at 2 degrees was performed by microphone arrays when a 10 Hz pressure oscillation was significant at 24 m/s. Temporally, this 10 Hz periodic strength change became more intense at a broader frequency bandwidth for a longer source region. Furthermore, a substantial time delay, significantly larger than the sound propagating time difference between microphones, was observed exclusively along the spanwise direction. This delay led to a periodic directivity pattern, particularly when two 0.2 m source regions were separated by a 0.2 m or 0.4 m tripping region. This low-frequency oscillation introduces an asymmetric transient switching pattern for symmetric spanwise source regions. Consequently, the response of airfoils to external oscillations in field tests should be considered.

Unmanned sailboats, harnessing wind for propulsion, offer great potential for extended marine research due to their virtually unlimited endurance. The sails typically operate at high attack angles, which contrasts with aircraft that maintain small angles to prevent stalling. Despite the reduction in lift during stalling, the resultant increase in drag contributes significantly to the sail’s thrust. However, the sail often experiences vortex shedding due to high attack angles, leading to low-frequency oscillations and erratic navigation. This study employs large-eddy simulations (LESs) on a 3D NACA0012 sail at a Reynolds number of 3.6 × 105, which is validated by experimental data. It observes the lift and drag coefficients across attack angles from 5 to 90 degrees and compares these with a Dynarig sail. The findings reveal that higher attack angles amplify fluctuations in lift and drag coefficients. Vortex shedding, resulting from flow separation, creates pressure changes and oscillations in aerodynamic forces. Fast Fourier transformation (FFT) analysis identifies dominant frequencies between 0.5 and 10 Hz, indicating low-frequency oscillations. The study’s insights into the impact of attack angle and sail type on the oscillation frequency are favorable for the design of unmanned sailboats, aiding in the prediction of wind-induced frequencies and optimal attack angle determination.

Aiming at the low-frequency oscillation problem of high-proportion wind power and energy storage connected to the power system, this paper establishes a system small signal model according to the matrix similarity theory, which lays a foundation for the research on oscillation characteristics, mechanism analysis, and suppression measures. Combined with the different installation positions of the inverter-side converter and the inverter-side POD (Power Oscillation Damper) controller of the energy storage device, the suppression mechanism and damping oscillation ability of the two on low-frequency oscillation were analyzed. Under multiple optimization objectives, the parameters of the damping controller are optimized by Pareto and improved particle swarm algorithms. Finally, through Matlab/Simulink simulation, the effectiveness of the Pareto and improved particle swarm algorithm in suppressing low-frequency oscillation of the system is verified. [ABSTRACT FROM AUTHOR]

The existing low-frequency oscillation analysis method of a multi-grid-forming-VSC (voltage source converter) is greatly affected by modeling accuracy, and its oscillation mode can only be determined by acquiring the control parameters of the system. Therefore, a method of identifying low-frequency oscillation characteristics of multi-VSC based on VMD (variational mode decomposition) and a Prony algorithm was proposed in this paper. The Prony algorithm is sensitive to noise, and its identification accuracy is greatly affected by noise. Thus, the VMD algorithm was utilized to denoise the measured data. Then, the Prony algorithm was applied to analyze the low-frequency oscillation of the measured data of single VSC and multi-VSC grid-connected systems, and its applicability to different grid-forming VSCs was verified. The error comparison results showed that the proposed low-frequency oscillation identification method had high accuracy. Furthermore, the influence of the number of parallel VSCs, grid strength and active output on the low-frequency oscillation of the system was investigated. Finally, the effectiveness of the proposed low-frequency oscillation method was verified by building a physical experimental platform. [ABSTRACT FROM AUTHOR]

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Shanghai Jiao Tong University (1006-2467) is the property of Journal of Shanghai Jiao Tong University Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The grid integration of large-scale wind power will alter the dynamic characteristics of the original system and the power distribution among synchronous machines. Meanwhile, the interaction between wind turbines and synchronous machines will affect the damping oscillation characteristics of the system. The additional damping control of traditional synchronous generators provides an important means for wind turbines to enhance the damping characteristics of the system. To improve the low frequency oscillation characteristics of wind power grid-connected power systems, this paper adds a parallel virtual impedance link to the traditional damping controller and designs a DFIG-PSS-VI controller. In the designed controller, the turbine active power difference is chosen as the input signal based on residual analysis, and the output signal is fed back to the reactive power control loop to obtain the rotor voltage quadrature component. With DigSILENT/PowerFactory, the influence of the controller parameters is analyzed. In addition, based on different tie-line transmission powers, the impact of the controller on the low-frequency oscillation characteristics of the power system is examined through utilizing the characteristic root and time domain simulation analysis. [ABSTRACT FROM AUTHOR]

Ensuring the efficiency of the use of nutrients of grain, protein, vitamin and mineral feeds in the composition of complete feed mixtures in animal husbandry and crop production, as well as the corresponding reduction in the cost of manufacturing of these products, is the relevance of the presented research and prospects for their development. Therefore, the purpose of the study is to substantiate the effective regime parameters for the preparation of premixes of feed mixtures based on the assessment of the energy parameters of the vibration mixing process. This assessment was carried out by comparing the results of applying vibration, blade, and vibroblade technological operations. Under the conditions of low-frequency vibrations, a decrease in the working resistance of the loosened layer of the mixture is observed, which provided the effect of reducing energy consumption in this process. Therefore, in comparison with conventional vibrating mixers have a higher specific productivity of 5-6 times, provide a reduction in the mixing time by 2-3 times, metal consumption – by 17%, energy consumption – by 30%, capital costs for manufacturing – by 18%, and drive power – by 30-35%, which leads to a reduction in total energy consumption by 3-4 times. As a result, the zone of minimal energy consumption was substantiated, in which the reduction of the resistance of the technological medium allowed radically reducing the friction forces during mixing, while ensuring uniform distribution with the concentration of the components of the mixture required by technological requirements. An increase in the oscillation amplitude is accompanied by a quadratic increase in power consumption, which is conditioned by an increase in energy dissipation in the mass of the mixture in the form of heat. The implementation of reasonable operating mixing modes allowed reducing the energy consumption of the proposed vibro-blade mixing by 2.0-2.5 times compared to conventional blade processing. The practical value of these developments includes the use of vibro-blade working bodies and the vibration-free operation of the drive shaft, which, together with the minimisation of energy consumption for the process, reduces dynamic loads on the support units of the developed mixer

At the moment of electric locomotive passing the neutral-section, the voltage and current of traction network may have low-frequency oscillation (LFO), which will seriously affect the safe operation of the railway. Aiming at eliminating the transient LFO, a modeling method of vehicle-grid coupling system based on flux-current theory is presented in this paper. In the model of electric locomotive, the transient current control strategy and magnetic saturation of on-board transformer are considered, and the equivalent model of excitation inductance of on-board transformer is established based on the flux-current theory. Using this model, based on the Middlebrook impedance ratio criterion, the stability region of vehicle-grid coupling system is analyzed under the influence of average saturation of on-board transformer and control parameters of electric locomotive. The simulation results are analyzed to evaluate and verify the proposed modeling method of LFO. This work has the benefits of defining the opening and closing phase angle region of system stability as well as providing guidance to adaptively modify the control parameters to suppress the LFO.

With the increasing integration of new energy generation into the power system and the massive withdrawal of traditional fossil fuel generation, the power system is faced with a large number of stability problems. The phenomenon of low-frequency oscillation caused by lack of damping and moment of inertia is worth studying. In recent years, virtual synchronous generator (VSG) technique has been developed rapidly because it can provide considerable damping and moment of inertia. While improving the stability of the system, it also inevitably causes the problem of active power oscillation, especially the low mutual damping between the VSG and the power grid will make the oscillation more severe. The traditional time-domain state-space method cannot reflect the interaction among state variables and study the interaction between different nodes and branches of the power grid. In this paper, a frequency-domain method for analyzing low-frequency oscillations considering VSG parameter coupling is proposed. First, based on the rotor motion equation of the synchronous generator (SG), a second order VSG model and linearized power-frequency control loop model are established. Then, the differences and connections between the coupling of key VSG parameters and low-frequency oscillation characteristics are studied through frequency domain analysis. The path and influence mechanism of a VSG during low-frequency power grid oscillations are illustrated. Finally, the correctness of the theoretical analysis model is verified by simulation. [ABSTRACT FROM AUTHOR]

An electric railway system is a typical single-phase grid-connected converter system, and the low-frequency oscillation (LFO) phenomenon in electric railway systems has been widely reported around the world. Previous research has indicated that the LFO is a small-signal instability issue caused by impedance mismatching between the traction network system and electric trains. Therefore, this paper proposes an improved q-axis current control method to reshape the train's impedance. The proposed method can be implemented easily by relating a reverse q-axis reactive current directly to the reference of the q-axis current under the dq current decoupled control. Moreover, considering the additional q-axis reactive current control, a small-signal impedance model of a train–network system is built. The impedance-based analysis results indicate that the proposed q-axis reactive current feedback control can increase the magnitude of the train's impedance, which is beneficial to enhancing the system's stability. Finally, this paper employs experimental results to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

With the virtual synchronous generator (VSG) technology gradually becoming an emerging technology for new energy consumption, its introduction has solved the problems of weak support and weak anti-interference of traditional new energy stations. However, the practice shows that the grid-connected characteristics of VSG limit its large-scale utilization, and there is little research on the interaction between VSG and a multi-machine system. In this paper, small signal models and time domain simulation models of each link of a photovoltaic(PV) power station with the PV virtual synchronous generator (PV-VSG) are first conducted, and then the influence of the grid-connected PV power station with the PV-VSG on the low-frequency oscillation of power system and its interaction mechanism with the multi-machine system are qualitatively obtained based on the small signal analysis method and prony analysis method from two dimensions of frequency domain and time domain, respectively. The analysis and simulation show that the PV power station based on VSG technology affects the dynamic characteristics of the system by changing the electromagnetic torque of each synchronous generator. Unreasonable operating conditions and parameter settings will aggravate the phenomenon of low-frequency oscillation of the system. Before the grid connection of PV power station, the operating parameters shall be reasonably set to ensure their safe and stable grid connection. [ABSTRACT FROM AUTHOR]

The power system industry is one of the pioneers in implementing machine learning (ML) methods which have acquired a lot of attention across various facets of contemporary life. Low-frequency oscillation (LFO) is purportedly a non-threatened but slowly poisoning concern with electrical power networks that, if not adequately addressed in a reasonable timeframe, could appear as the cause of a total network failure. The function of a well-known member of the ML family, the adaptive neuro-fuzzy inference system (ANFIS), is proposed in this paper for optimizing LFO damping in real-time in the power system networks. It adopts two power system networks, one in which the synchronous machine is equipped solely with a power system stabilizer (PSS). In the second one, PSS relates to a second-generation flexible alternating current transmission system (FACTS) device named the unified power flow controller (UPFC). The well-known genetic algorithm (GA) supports the proposed ML algorithm in generating the dataset and training them well. The designed approach is examined using various statistical performance measures and well-recognized stability performance measures, such as the minimal damping ratio, eigenvalue, and time-domain simulation. The article also includes comparing and discussing the results from the reference works to make inferences on the viability of the proposed GA-tuned ANFIS technique for improving real-time power system stability. [ABSTRACT FROM AUTHOR]

The timely discovery of low-frequency oscillations in power systems and accurate identification of their modal parameters is critical in numerous applications. Therefore, we investigated the feasibility of using multi-channel signals and established a relative theory. An algorithm based on the underdetermined blind source separation (UBSS) algorithm was proposed using this theory. First, the energy ratio function was used to determine the fault occurrence time. Then, the Bayesian information criterion was used to estimate the number of fault sources, and the boundary conditions were set to determine the number of fault sources. Next, the UBSS algorithm was used to analyze raw data, extract individual components that characterize faults, and subsequently measure low-frequency oscillation modal parameters through the Hilbert transform. Finally, the fast independent component analysis (FastICA) algorithm was used to separate noise signal from raw data. This separation considerably reduced noise disturbance and ensured the stability of the proposed method. Model simulation was conducted in MATLAB and experimental measurement revealed that the proposed method effectively reduced noise disturbance and could be applied to conditions with considerable disturbance. [ABSTRACT FROM AUTHOR]

The sea-gale process (SGP) is a significant and disastrous weather event for the marine industry. However, the sub-seasonal predictability of SGP remains unclear. In this study, we investigate the influence of low-frequency oscillation on SGP in the Yangtze River estuary from November to April, and its implications for sub-seasonal prediction. We noted that SGPs have a close relationship with the 10~30 day low-frequency component of the 10-m wind speed in the Yangtze River estuary, and typically occur during the peak phase of the low-frequency oscillation. The 10~30 day low-frequency oscillation of 10-m wind was found to be linked to the eastward propagation of extratropical Rossby waves from the North Atlantic across Europe to East Asia. This Rossby wave leads to the low-frequency oscillation of the Siberian high pressure and Japan Sea low pressure, which is indicative of the 10~30 day low-frequency oscillations of the 10-m wind speed in the Yangtze River Estuary. A sea-gale process index (SGPI) was constructed based on the low-frequency oscillation of the Siberian high and the Japan Sea low in order to predict SGPs at the sub-seasonal time scale. Hindcast and real-time forecasts showed that 2/3 of SGPs can be predicted with a leading time of 10~30 days, and that good sub-seasonal predictions of SGPs are connected with strong low-frequency oscillations at the initial forecast time. Therefore, SGPI can be adopted for the sub-seasonal prediction of SGPs in the Yangtze River Estuary. [ABSTRACT FROM AUTHOR]

The low-frequency oscillation (LFO) problem of photovoltaic (PV) grid-connected systems has been a critical concern for safe operation, whereas the impact of dc-side components of PV plants are always ignored and single-stage PV plant is used. This paper performs a comprehensive analysis of the LFOs in the two-stage PV grid-connected system. The complete small-signal model of the two-stage PV system is built. On this basis, the LFO modes and high-frequency oscillation (HFO) modes are calculated and related participating components are determined. Then, the impact of key parameters on the LFO characteristics is investigated with the root locus analysis. The theoretical analysis is verified through PSCAD/EMTDC simulations.

Stability is a primary requirement of the electrical power system for its flawless, secure, and economical operation. Low-frequency oscillations (LFOs), commonly seen in interconnected power systems, initiate the possibility of instability and, therefore, require sophisticated care to deal with. This paper proposes an original approach to tuning the parameters of the power system stabilizer (PSS), which plays a crucial role in the power system networks to dampen unwanted oscillations. The ensemble method combines multiple machine learning techniques and has been used for tuning the PSS parameters in real-time for two PSS-connected power system networks. The first system is a single-machine infinite bus power system, while the second is a unified power flow controller (UPFC) device. The backtracking search algorithm (BSA) based proposed ensemble model is formed by combining three machine learning (ML) techniques, namely the extreme learning machine (ELM), neurogenetic (NG) system, and multi-gene genetic programming (MGGP). To validate the stability of the network, Eigenvalues, well-recognized statistical parameters, and minimum damping ratios were analyzed, besides the time-domain simulation results. Furthermore, results for various loading conditions were prepared to check the robustness of the proposed model. A comparative study of the proposed approach with NG, ELM, MGGP models, and two reference cases along with the conventional method will validate the superiority of the employed ML approach.

The effective suppression of low-frequency grid oscillations by the offshore wind power in a voltage source converter-based HVDC (VSC-HVDC) output system can enhance the operational stability of the overall power system. In most existing studies, low-frequency oscillations are suppressed by controlling active power. However, active regulation can reduce the utilization of new energy sources. Therefore, this report proposes a reactive power suppression strategy based on frequency feedback. First, a mathematical model of the VSC-HVDC system is established to derive the mechanism of reactive power suppression of low-frequency oscillations in the receiving-end converter. Second, DC voltage control and AC-side reactive power control are adopted in the sending-end converter of the VSC-HVDC system, and DC control and AC voltage control are adopted in the receiver station. Finally, the single infinity system is subjected to a simulation analysis using MATLAB/Simulink. The simulation results demonstrate that this strategy can effectively suppress low-frequency oscillations of the grid, while simultaneously reducing the investment cost of reactive power equipment and improving the wind turbine utilization efficiency.

This study performed a comparative analysis of five new meta-heuristic algorithms specifically adopted based on two general classifications; namely, nature-inspired, which includes artificial eco-system optimization (AEO), African vulture optimization algorithm (AVOA), gorilla troop optimization (GTO), and non-nature-inspired or based on mathematical and physics concepts, which includes gradient-based optimization (GBO) and Runge Kutta optimization (RUN) for optimal tuning of multi-machine power system stabilizers (PSSs). To achieve this aim, the algorithms were applied in the PSS design for a multi-machine smart power system. The PSS design was formulated as an optimization problem, and the eigenvalue-based objective function was adopted to improve the damping of electromechanical modes. The expressed objective function helped to determine the stabilizer parameters and enhanced the dynamic performance of the multi-machine power system. The performance of the algorithms in the PSS's design was evaluated using the Western System Coordinating Council (WSCC) multi-machine power test system. The results obtained were compared with each other. When compared to nature-inspired algorithms (AEO, AVOA, and GTO), non-nature-inspired algorithms (GBO and RUN) reduced low-frequency oscillations faster by improving the damping of electromechanical modes and providing a better convergence ratio and statistical performance. [ABSTRACT FROM AUTHOR]

The purpose of this study was to investigate the influence of changes in muscle length on the torque fluctuations and on related oscillations in muscle activity during voluntary isometric contractions of ankle plantar flexor muscles. Eleven healthy individuals were asked to perform voluntary isometric contractions of ankle muscles at five different contraction intensities from 10% to 70% of maximum voluntary isometric contraction (MVIC) and at three different muscle lengths, implemented by changing the ankle joint angle (plantar flexion of 26°-shorter muscle length; plantar flexion of 10°-neutral muscle length; dorsiflexion of 3°-longer muscle length). Surface electromyogram (EMG) signals were recorded from the skin surface over the triceps surae muscles, and rectified-and-smoothed EMG (rsEMG) were estimated to assess the oscillations in muscle activity. The absolute torque fluctuations (quantified by the standard deviation) were significantly higher during moderate-to-high contractions at the longer muscle length. Absolute torque fluctuations were found to be a linear function of torque output regardless of muscle length. In contrast, the relative torque fluctuations (quantified by the coefficient of variation) were higher at the shorter muscle length. However, both absolute and relative oscillations in muscle activities remained relatively consistent at different ankle joint angles for all plantar flexors. These findings suggest that the torque steadiness may be affected by not only muscle activities, but also by muscle length-dependent mechanical properties. This study provides more insights that muscle mechanics should be considered when explaining the steadiness in force output. [ABSTRACT FROM AUTHOR]

This study aims to develop and test a new accelerated method for analyzing low-frequency oscillations in power systems using phasor measurements. The proposed method is based on the use of mathematical statistics methods that do not require significant computing power and have high reliability. Changes in the structure of power generation and integration of control devices based on power electronics cause low-frequency oscillations of power system operation parameters that present a threat. These changes result in a reduction in the total inertia of power systems with the subsequent impact on the operation of automatic voltage regulators and power system stabilizers, the purpose of which is to damp low-frequency oscillations. We conduct a careful review of the existing methods for low-frequency oscillations analysis in power systems to identify the gaps in the literature and design a new method to address the issues. The proposed method is tested on real-life data that was obtained during a disturbance with a transient event. Estimation of the low-frequency oscillation parameters was carried out, and the potential threat posed by these phenomena was examined. The implementation of the proposed algorithm for analyzing low-frequency oscillations is done using the Matlab programming language. Evaluation of the proposed algorithm is performed on physical data obtained during real transient processes occurring at large power plants. [ABSTRACT FROM AUTHOR]

Ensuring the efficiency of the use of nutrients of grain, protein, vitamin and mineral feeds in the composition of complete feed mixtures in animal husbandry and crop production, as well as the corresponding reduction in the cost of manufacturing of these products, is the relevance of the presented research and prospects for their development. Therefore, the purpose of the study is to substantiate the effective regime parameters for the preparation of premixes of feed mixtures based on the assessment of the energy parameters of the vibration mixing process. This assessment was carried out by comparing the results of applying vibration, blade, and vibroblade technological operations. Under the conditions of low-frequency vibrations, a decrease in the working resistance of the loosened layer of the mixture is observed, which provided the effect of reducing energy consumption in this process. Therefore, in comparison with conventional vibrating mixers have a higher specific productivity of 5-6 times, provide a reduction in the mixing time by 2-3 times, metal consumption – by 17%, energy consumption – by 30%, capital costs for manufacturing – by 18%, and drive power – by 30-35%, which leads to a reduction in total energy consumption by 3-4 times. As a result, the zone of minimal energy consumption was substantiated, in which the reduction of the resistance of the technological medium allowed radically reducing the friction forces during mixing, while ensuring uniform distribution with the concentration of the components of the mixture required by technological requirements. An increase in the oscillation amplitude is accompanied by a quadratic increase in power consumption, which is conditioned by an increase in energy dissipation in the mass of the mixture in the form of heat. The implementation of reasonable operating mixing modes allowed reducing the energy consumption of the proposed vibro-blade mixing by 2.0-2.5 times compared to conventional blade processing. The practical value of these developments includes the use of vibro-blade working bodies and the vibration-free operation of the drive shaft, which, together with the minimisation of energy consumption for the process, reduces dynamic loads on the support units of the developed mixer. [ABSTRACT FROM AUTHOR]

Low-frequency oscillations (LFO) occur in railway electrification systems due to the incorporation of new trains with switching converters. As a result, the increased harmonic content can cause catenary stability problems under certain conditions. Most of the research published on this topic to date is focused on modelling the event and analysing it using frequency spectrums. However, in recent years, due to the new technologies linked to Big Data (BD) and data mining (DM), a new opportunity to study and detect LFO events by means of machine-learning (ML) methods has emerged. Trains continuously collect data from the most important catenary variables, which offers new resources for analysing this type of event. Therefore, this article presents the design and implementation of a data-driven LFO event detection strategy for AC railway network scenarios. Compared to previous investigations, a new approach to analyse and detect LFO events, based on field data and ML, is presented. To obtain the most appropriate detection approach for the context of this application, on the one hand, this investigation includes a comparison of machine-learning algorithms (support vector machine, logistic regression, random forest, k-nearest neighbours, naïve Bayes) which have been trained with real field data. On the other hand, an analysis of key parameters and features to optimize event detection is also included. Thus, the most significant result of this work is the high metric values of the solution, reaching values above 97% in accuracy and 93% in F-1 score with the random forest algorithm. In addition, the applicability and training of data-driven methods with real field data are demonstrated. This automatic detection strategy can help with speeding up and improving LFO detection tasks that used to be performed manually. Finally, it is worth mentioning that this research has been structured based on the CRISP-DM methodology, established as the de facto approach for industrial DM projects. [ABSTRACT FROM AUTHOR]