Broadband Oscillations Research Articles

Research on Broadband Oscillation Suppression Strategy in Power System Based on Genetic Algorithm

This examination presents an original Broadband Oscillation Concealment Procedure in Power Systems utilizing a Genetic Algorithm (GA). The philosophy’s suitability is deliberately assessed through comprehensive examinations, including affiliation investigation, strength appraisal, and near investigations with elective optimization algorithms. Results show that the GA-based approach displays predominant affiliation, appearing at a health worth of 0.05 after 100 ages, beating Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Simulated Annealing (SA). Strength examination features the versatility of the proposed procedure, with a standard wellbeing worth of 0.08 ± 0.02 under changing power framework conditions. Similar investigation against related work reveals the procedure’s advantage, showing its genuine breaking point with regards to helpful broadband oscillation concealment. The GA-based philosophy changes speedy mixing and computational capacity, with an ordinary execution season of 120 seconds. The examination contributes important pieces of information into power framework strength, offering a good answer for mitigating broadband oscillations in various working situations.

Analysis and suppression of offshore wind power broadband oscillation based on HVDC transmission technology

Analysis and suppression of offshore wind power broadband oscillation based on HVDC transmission technology

Next-Generation MPPT: neural network-driven optimization for superior solar performance

This paper presents a novel smart Maximum Power Point Tracking (MPPT) method based on a Neural Network Controller (NNC) to enhance solar power efficiency and mitigate significant oscillations. Traditional MPPT techniques, including perturbation and observation, fixed and variable incremental conductance methods, and fractional open circuit voltage, often suffer from slow response to sudden environmental changes (temperature and irradiation), inaccurate tracking, lack of prediction abilities, and complex structures. These drawbacks lead to power loss, reduced effectiveness of photovoltaic (PV) systems and raised broadband oscillations. To address these issues, we propose an intelligent MPPT strategy utilizing NNC. The NNC inputs are the error and derived error (E&ΔE) between the reference and actual inputs, with the duty cycle (D) as the target output. The proposed algorithm demonstrates an efficiency of approximately 0.75% compared to 0.63% for the P&O method. Simulation and experimental validation results confirm the NNC strategy's effectiveness, robustness, and efficiency, providing a thorough system analysis.

Environmentally stable all‐fiber femtosecond laser for industrial application based on a SESAM mode‐locked ytterbium‐doped laser

AbstractWe demonstrate an environmentally stable femtosecond laser for industrial application based on all polarization‐maintaining Yb‐doped laser and experimentally explore the effect of the net cavity dispersion (NCD) on output characteristics. The oscillator emits pulses with 5.1 ps and a 23 nm spectral bandwidth, then the pulse is compressed to 88 fs. The instabilities over 120 h gives 0.32% relative root mean square noise, indicating high stability of the pulse laser. With effective regulation of NCD, we obtained the maximum spectral bandwidth of 27 nm. Such broadband oscillator with compact all‐fiber configurations provide extremely high stability should be very attractive for long‐term industrial application.

A New Method for the Analysis of Broadband Oscillation Mode of New Energy Stations

The accurate identification of the broadband oscillation mode is the premise of solving the resonance risk of new energy stations. Reviewing the traditional Prony algorithm, the problems of the high model order and poor noise immunity in broadband oscillation mode are identified. The accuracy and running time of the Variational mode decomposition (VMD) is a symmetric trade-off problem. An improved strategy based on VMD is proposed. Firstly, the optimal value of the number of modes and penalty factors obtained by a particle swarm optimization algorithm is input into VMD to decompose the signal into multiple modes. Then, combined with the energy threshold method, the denoising and signal reconstruction of each mode component after decomposition are carried out. Finally, the Prony algorithm is used to identify the oscillation mode of the original signal and the reconstructed signal, respectively. The Signal-to-noise ratio (SNR) and model order are compared and analyzed. Through the analysis of the example and simulation data, it is shown that the proposed method effectively solves the problem of poor engineering adaptability of the traditional Prony algorithm. It also can accurately obtain the time-domain characteristics of broadband oscillation, which has a promising future in the engineering application.

Identification of Intensive Oscillation Parameters of Power System Based on CS-CNN-GRU Network

Broadband oscillations caused by power electronic devices contain a large number of high harmonics and interharmonics, and the frequencies of these harmonic/interharmonic components are likely to be very close. In order to improve the accuracy of dense oscillation parameter identification, this paper proposes a cyclic gate unit-convolutional neural network (CNN-GRU) dense oscillation parameter identification method optimized by the cuckoo search algorithm (CS). The Cuckoo search algorithm combined with the cross-entropy function realizes the automatic acquisition of the parameters of the CNN-GRU network and improves the adaptive ability of the model. The analysis of the measured data shows that the method in this paper has high accuracy in identifying the dense oscillation parameters of dense frequency harmonics, interharmonics, and neighboring fundamental interharmonic pairs, etc., and the computational speed is also improved compared with the traditional deep learning network.

Research of cooperative multi-stability composite energy collection with multi-frequency and broadband oscillation

Research of cooperative multi-stability composite energy collection with multi-frequency and broadband oscillation

An Intelligent Location Method for Power System Oscillation Sources Based on a Digital Twin

Aiming at the difficult problem of broadband oscillation localization in power systems, the intelligent localization method of an oscillation source based on a digital twin is proposed, and the oscillation source localization system is thus constructed. Firstly, a digital twin-based oscillation source localization method and its system architecture are proposed. Furthermore, an intelligent positioning method of the oscillation source, based on data-driven and mechanism fusion, is proposed. It includes three steps: oscillation signal preprocessing, oscillation modal analysis and oscillation source localization. For the oscillation signal preprocessing, the generative adversarial imputation network is used to repair the missing samples, and the super-resolution technique is used to realize the super-resolution measurement of broadband oscillation. In the oscillation modal analysis, the spectrum of the oscillation signal is extracted using the fast Fourier transform. To accurately locate the oscillation source, branch potential energy is used as the input to the data-driven model, such as LSTM and CNN. Finally, an oscillation source localization system is developed based on the digital twin workshop CloudPSS-XStudio, which can locate the oscillation source quickly and accurately.

Adaptive Band-Pass Filter and VMD-Esprit Based Multi-Mode Monitoring Method for Broadband Electromagnetic Oscillation in “Double High” Power Systems

With the development of new power systems with high proportions of renewable energy and high proportions of power electronics equipment, the influence of broadband electromagnetic oscillations in power systems is becoming more and more significant. In order to better grasp the dynamic characteristics of broadband oscillations, a new adaptive band-pass filter and VMD-Esprit based multi-modal monitoring method is proposed for broadband electromagnetic oscillation in “double high” power systems. First, based on the mode frequency and amplitude information provided by FFT mode detection, the proposed adaptive band-pass filter adaptively sets the center frequency, bandwidth, and other parameters and extracts or separates the voltage/current signal in each frequency band. Second, the filtered signals are corrected and compensated, and then the VMD modal decomposition of each frequency band signal is combined with Esprit for parameter identification so as to obtain the waveform and parameter information of each mode. Finally, the separation, correction, and parameter identification of multi-mode broadband oscillation waveforms are carried out. The experimental results show that frequency division processing can reduce the computation and improve real-time performance. In the processing of signals in the frequency band, the center frequency, bandwidth, and other parameters can be adjusted adaptively under different conditions of single-mode composition or multi-mode composition, which improves the accuracy of VMD decomposition and increases the flexibility of signal processing. Meanwhile, it overcomes the defects such as the inaccuracy of traditional mode recognition, which provides a new idea for broadband electromagnetic oscillation analysis.

Geodetic residual time series: A combined series by minimization of their internal noise level

This study aims to assess the hydrological effects of polar motion calculated from different combinations of geophysical excitations at decadal, seasonal, and non-seasonal periods. The geodetic residuals GAO, being a difference between observed geodetic excitation function of polar motion Geodetic Angular Momentum (GAM) and atmospheric (Atmospheric Angular Momentum—AAM) plus oceanic excitation functions (Oceanic Angular Momentum—OAM), are compared. Estimating hydrological effects on Earth’s rotation differs significantly, especially when using various oceanic models. Up to now, studies of geophysical excitations of polar motion containing AAM, OAM, and hydrological angular momentum (HAM) have not achieved entire agreement between geophysical (sum of AAM, OAM, and HAM obtained from the models) and geodetic excitation. Many geophysical models of the atmosphere, oceans, and land hydrology can be used to compute polar motion excitation. However, these models are very complex and still have uncertainties in the process descriptions, parametrization, and forcing. This work aims to show differences between various GAO solutions calculated from different mass and motion terms of various AAM and OAM models. Justifying to use one combination of GAO to estimate geodetic residuals is comparing those time series to hydrological excitations computed from Gravity Recovery and Climate Experiment (GRACE) data and the Land Surface Discharge Model (LSDM) model. Especially the quality of each geodetic residual time series is determined by estimating their noise level using a generalized formulation of the “three-cornered hat method” (3CH). This study presents a combined series of geodetic residuals GAO in polar motion (PM), wherein the internal noise level is shortened to a minimum by using the 3CH method. The combined GAO time series are compared with results obtained from the GRACE/GRACE Follow-On (GRACE-FO) solution provided by International Combination Service for Time variable Gravity Fields (COST-G) and the single solution elaborated by the Center for Space Research (CSR) and from the HAM LSDM hydrological model. The results show that higher consistency between GAO and HAM excitations can be achieved by minimizing the internal noise level in the GAO combined excitation series using the 3CH method, especially for the overall broadband and seasonal oscillations. For seasonal spectral bands, an agreement between combined GAO and the best-correlated series of GRACE CSR achieve correlations as high as 0.97 and 0.83 for the χ1 and χ2 equatorial components of PM excitation, respectively. This study’s combined geodetic residual time series slightly improved consistency between observed geodetic polar motion excitations and geophysical ones.

Oscillation characteristics and trajectory stability region analysis method of hierarchical control microgrids

To address the broadband oscillation problem caused by isomerized power electronic devices in microgrids, an oscillation characteristic and stability region analysis method was proposed for hierarchical control structure microgrids based on the dynamic time-varying fast and slow scale analysis method. From the perspective of control, the controller was combined with the main circuit, and a nonlinear dynamic model of the microgrid hierarchical control grid-connected inverter was established. Then, the dynamic time-varying fast and slow scale analysis method was used to obtain the Hopf bifurcation oscillation trajectory. Furthermore, and combining with three-dimensional and Hopf bifurcation, considering the correlation between the main circuit parameters and controller parameters as the starting point, the trajectory instability region analysis method is proposed. Finally, the instability mechanism of the hierarchical control structure microgrid is revealed using the above methods. These methods provide a theoretical basis for the correct selection of the main circuit structure parameters and controller parameters of the microgrid.

Large-Scale Renewable Energy Transmission by HVDC: Challenges and Proposals

Renewable energy transmission by high-voltage direct current (HVDC) has attracted increasing attention for the development and utilization of large-scale renewable energy under the Carbon Peak and Carbon Neutrality Strategy in China. High-penetration power electronic systems have gradually formed at the sending end of HVDC transmission. The operation of such systems has undergone profound changes compared with traditional power systems dominated by synchronous generators. New stability issues, such as broadband oscillation and transient over-voltage, have emerged, causing tripping accidents in large-scale renewable energy plants. The analysis methods and design principles of traditional power systems are no longer suitable for HPPESs. In this paper, the mechanisms of broadband oscillation and transient over-voltage are revealed, and analytical methods are proposed for HPPESs, including small-signal impedance analysis and electromagnetic transient simulation. Validation of the theoretical research has been accomplished through its application in several practical projects in north, northwest, and northeast region of China. Finally, suggestions for the construction and operation of the future renewable-energy-dominated power system are put forward.

Research on oscillation characteristics of wind farm sending system based on participation factor

The MMC-HVDC transmission system of wind farms has a very broad application prospect, but there is gradually growing major concern that the system is prone to broadband oscillation. And the mechanism of oscillation also remains to be clarified. In this article, based on the basic principle of eigenvalue analysis, the theoretical calculation equation of the quantitative evaluation index of the participation factor is deduced. The small-signal model of the MMC-HVDC transmission system for a wind farm is established. Combining with the case of 200 wind turbines connected to the grid, the eigenvalue analysis method is used to obtain the dominant oscillation mode of the system. The participation factors of 11 oscillation modes of the system are calculated to further analyze the relationship between the oscillation modes and the state variables in the MMC-HVDC transmission system of the wind farms. And the correlation between the participation factors of each oscillation mode, wind farm, and the MMC system is investigated, which laid a foundation for the formulation of broadband oscillation suppression strategies.

Unsteady flow analysis regarding stall flow and rotating cavitation in the first-stage of a multistage LNG cryogenic submerged pump

In this paper, the evolution of vortex structure and energy conversion process under the coupling of stall and cavitation flow (CSC) in the first-stage of a multistage LNG cryogenic submerged pump are numerically studied in detail, using a time-scale-driven hybrid URANS/LES turbulence model and a mushy interfacial dynamics cavitation model. The flow instability diagnostic parameter, PVS, is then established combining the first and second laws of thermodynamics. Further, the dynamic behaviors under CSC are analyzed by Liutex method and the fluctuations of vortex intensity are investigated in time-frequency domain. Results show that compared with the oscillation process of the pump head, PVS is more intuitive to depict the stall state. It is treated as light and deep stall as PVS drops to 0.2 and 0.15, while PVS is further reduced and finally locks at about 0.12. For the above conditions, vortices at the inlet section involves high-frequency cavity-shedding vortex and low-frequency impact vortex. The middle separation region absorbs the upstream shedding vortex and transports the separation vortex downstream, whereas vortices with the highest intensity locates at the outlet diffusion section in the helical shape. Among the vortex-vortex interaction, broadband oscillations get more significant under CSC.

Data-Driven Mode Identification Method for Broad-Band Oscillation of Interconnected Power System

The paper presents research on mode identification of broad-band oscillation in interconnected power system. A data-driven mode identification (DDMI) method for broad-band oscillation signals is proposed creatively in this paper. Firstly, piecewise aggregation approximation algorithm is improved to achieve effective dimension reduction of oscillation data. Combined with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${k}$ </tex-math></inline-formula> -Shape clustering algorithm, oscillation database is established with historical data, real-time data and simulation data. Then, oscillation mode identification models corresponding to different data categories can be obtained based on random forest algorithm, which can realize fast and automatic matching between broad-band oscillation data and oscillation mode parameters. Finally, the identification results of two simulation oscillation cases and an actual oscillation case show that proposed method can accurately identify the oscillation mode parameters from broad-band oscillation signals and has higher accuracy compared with other methods.

Cyclotron Resonance Maser With Zigzag Quasi-Optical Transmission Line: Concept and Modeling

A microwave system in the form of a quasi-optical (QO) transmission line is proposed as an interaction circuit of an amplifier or an oscillator based on the cyclotron resonance maser (CRM) instability. The circuit consists of periodically spaced along the horizontal <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${z}$ </tex-math></inline-formula> -axis focusing mirrors, which transport the Gaussian wave beam along a zigzag path with vertical and inclined segments. A beam of electrons having sufficiently high perpendicular velocities is guided by a static B-field along the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${z}$ </tex-math></inline-formula> -axis so that the e-beam periodically crosses the wave beam. The CRM instability occurs in regions where an electromagnetic wave having a Bz-component, as in a gyrotron, propagates strictly across the e-beam resulting in the interaction with minimal sensitivity to particle velocity spread. Three-dimensional Particle-In-Cell (3-D PIC) simulations demonstrate the attractiveness of this “zigzag” CRM for the implementation of relatively broadband amplifiers or oscillators with unique (more than an octave bandwidth) frequency tunability at wavelengths of 1–2 mm.

SWCNTs/PEDOT:PSS-Modified Microelectrode Arrays for Dual-Mode Detection of Electrophysiological Signals and Dopamine Concentration in the Striatum under Isoflurane Anesthesia.

Accurate detection of the degree of isoflurane anesthesia during a surgery is important to avoid the risk of overdose isoflurane anesthesia timely. To address this challenge, a four-shank implantable microelectrode array (MEA) was fabricated for the synchronous real-time detection of dual-mode signals [electrophysiological signal and dopamine (DA) concentration] in rat striatum. The SWCNTs/PEDOT:PSS nanocomposites were modified onto the MEAs, which significantly improved the electrical and electrochemical performances of the MEAs. The electrical performance of the modified MEAs with a low impedance (16.20 ± 1.68 kΩ) and a small phase delay (-27.76 ± 0.82°) enabled the MEAs to detect spike firing with a high signal-to-noise ratio (> 3). The electrochemical performance of the modified MEAs with a low oxidation potential (160 mV), a low detection limit (10 nM), high sensitivity (217 pA/μM), and a wide linear range (10 nM-72 μM) met the specific requirements for DA detection in vivo. The anesthetic effect of isoflurane was mediated by inhibiting the spike firing of D2_SPNs (spiny projection neurons expressing the D2-type DA receptor) and the broadband oscillation rhythm of the local field potential (LFP). Therefore, the spike firing rate of D2_SPNs and the power of LFP could reflect the degree of isoflurane anesthesia together. During the isoflurane anesthesia-induced death procedure, we found that electrophysiological activities and DA release were strongly inhibited, and changes in the DA concentration provided more details regarding this procedure. The dual-mode recording MEA provided a detection method for the degree of isoflurane anesthesia and a prediction method for fatal overdose isoflurane anesthesia.

On the use of a two-layer model for large-eddy simulations of supersonic boundary layers with separation

The two-layer modeling approach has become one of the most promising and successful methodology for simulating turbulent boundary layers in the past ten years. In the present study, a mixed wall model for large-eddy simulations (LES) of high-speed flows is proposed which combine two approaches; the thin-Boundary Layer Equations (TBLE) model of Kawai and Larsson (1994) and the analytical wall-layer model of Duprat et al. (2011) for streamwise pressure gradients. The new hybrid model has been efficiently implemented into a three-dimensional compressible LES solver and validated against DNS of a spatially-evolving supersonic boundary layer (BL) under moderate and strong pressure gradients, before being employed for the prediction of nozzle flow separations at different flow conditions, ranging from weakly to highly over-expanded regimes. A good agreement is obtained in terms of mean and fluctuating quantities compared to the DNS results. Particularly, the current wall-modeled LES results are found to perfectly match the DNS data of supersonic BL with/out pressure gradient. It is also shown that the model can account for the effect of the large-scale turbulent motions of the outer layer, indicating a good interaction between the inner and the outer part of the wall layer. In terms of simulations costs and improvements of computing power, the obtained results highlight the capability of the current wall-modeling LES strategy in saving a considerable amount of computational time compared to the wall-resolved LES counterpart, allowing to push further the simulations limits. Furthermore, the application of these computationally low-costly LES simulations to nozzle flow separation allows to clearly identify the origin of the shock unsteadiness, and the existence of broadband and energetically-significant low-frequency oscillations (LFO) in the vicinity of the separation region.

STFT Analysis of Broadband Oscillation in VSC-HVDC Connected to Offshore Wind Farms

The transmission technology of offshore windfarms (OWFs) through VSC-HVDC system is developing rapidly. The impact factor of broadband oscillation is complex, it often occurs in VSC-HVDC and direct drive permanent magnet synchronous generator (DDPMSG). In this paper, based on short time fourier transform (STFT), factors that cause broadband oscillation are studied. Firstly, the primary structure of DDPMSG and VSC-HVDC is established. Then the correctness of small signal method (SSM) is verified. Based on eigenvalue analysis, instability caused by controlling parameter is analysed. Finally, time-frequency characteristic of oscillation waveforms in PSCAD is extracted using STFT, asynchronous characteristics of broadband oscillation is verified. It is of guiding significance, for the developing technology of offshore wind farm integrated into grid through VSC-HVDC system.

Modulation of narrowband and broadband gamma connectivity in retinal degeneration mice according to electrical stimulation pulse width

Brain connectivity involves the structural, functional and effective communication between neurons across brain regions and is expressed in neuronal oscillations. Previous research has reported the evidence of two types of gamma oscillations namely the broadband gamma (30 Hz - 90 Hz) and narrowband gamma (55 Hz - 70 Hz) oscillations which have been implicated in excitatory and inhibitory network transmission. There is presently no systematic investigation of the relationship between electrical stimulation pulse width and narrow or broadband gamma oscillations in visual-deficient mice. In the current study, we set out to bridge this gap in knowledge by exploring the modulation of brain connectivity indices in broadband gamma and narrowband gamma oscillations in response to varying electrical stimulation pulse width in retinal degeneration (rd) mice. The results revealed that a low pulse width (0.5 ms/phase) strongly enhances coherence and directional connectivity of broadband and narrowband gamma oscillations in contra visual cortex and contra prefrontal cortex of rd mice. This study serves a crucial role in the design and utilisation of visual prostheses by contributing to the understanding of information transmission between different brain regions under retinal electrical stimulation in visual-deficit population.