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The shift from traditional fossil fuel-based power systems to renewable energy sources heightens the importance of frequency regulation. The lack of inertia in this new generation increases the risk of low-frequency oscillatory events, a significant concern in power systems stability. To mitigate these stability problems, it is crucial to study the effectiveness of damping controllers. This paper delves into the analysis of three damping controllers: the power system stabilizers (PSS) installed in synchronous generators, and two Power Oscillation Damping (POD) controllers, one with active power modulation (POD-P) and the other with reactive power modulation (POD-Q), typically installed in environments with high renewable penetration.The main objective is to critically evaluate the comparative advantages of PSS, POD-P, and POD-Q controllers in local and inter-area oscillations by exploring their flexibility and performance under various initial conditions and oscillatory scenarios. The proper choice of damping controllers will ensure the stability of the grid in future scenarios of high renewable production, thus allowing the definition of future technology needs. This research is of utmost importance as it aims to dampen different oscillations by employing uniform control parameters in the PSS, POD-P, and POD-Q controllers. Five scenarios are defined on a system based on the IEEE 39 Bus New England System model and simulated by DIgSILENT PowerFactory. The results are analyzed methodically per scenario, facilitating a comparative evaluation of the controllers and reaching promising conclusions.

With the expansion of power grid scale and the increase of power components, the maintenance methods of power system become more and more complex. It is difficult to evaluate the low-frequency oscillation risk of power grid under massive maintenance only by traditional methods. To solve this problem, a risk prediction method of low-frequency oscillation in maintenance power network based on long short term memory (LSTM) neural network was proposed. Firstly, the unified coding method of power system maintenance mode was proposed, so that the computer can quickly and accurately identify the operation state of power grid under various maintenance modes. Then, based on the historical data measured in real time by phasor measurement unit (PMU), the number of low-frequency oscillation of power grid under different maintenance modes was predicted by using LSTM neural network, so as to evaluate the risk of low-frequency oscillation of power grid under maintenance. Finally, a regional power grid in central China was taken as an example to verify the accuracy and rapidity of the proposed method.

Low-frequency oscillations (LFO) are generated in interconnected electric networks because of the weak tie lines between the parts of the networks. Such oscillations have been a significant challenge for engineers that may lead to system instability if appropriate measures are not taken. This article proposes two new metaheuristic algorithms, the jellyfish search algorithm (JSA) and the tunicate swarm algorithm (TSA), to design the power system stabilizers (PSS) for single machine infinite bus (SMIB) and multimachine power system (MPS) networks. The proposed method uses the JSA and TSA to dampen out the LFOs by modifying the vital parameters of lead-lag type conventional PSS (CPSS). A damping ratio-based objective function improves both models' system damping. These methods are tested on an SMIB system and two distinct MPS networks exposed to the three-phase fault under various loading conditions. The effectiveness of the suggested approach has been studied by comparing the system eigenvalues and minimum damping ratio (MDR) produced from JSA and TSA-tuned PSS and the CPSS. In addition, time domain simulation results are compared, demonstrating that the new approach outperforms the standard techniques, such as particle swarm optimization (PSO) and backtracking search algorithm (BSA). In the SMIB system, MDR produced by JSA and TSA-based PSS is 2.55 times higher than that of CPSS. Similarly, in comparison to PSO and BSA-based PSS, JSA, and TSA-tuned PSS offer >1.4 times greater MDR in the Two Area Four Machine network and up to 8.4 times larger MDR for the IEEE-39 Bus network. Furthermore, the efficacy of the suggested JSA and TSA approaches' prediction capacity is validated by satisfying the values of statistical performance metrics.

In this paper, the damping of low-frequency oscillations (LFOs) in a power system containing Static VAR Compensator (SVC) is investigated based on Multiple-Model Linear Optimal Control (MMLOC) Strategy. The performance of MMLOC is enhanced using Polynomial Combination Algorithm (PCA). A linear optimal controller (LOC) generates the optimal control signal with linearization the nonlinear state equations of the system and solving the Riccati equation. One LOC generates synchronized control signals for the synchronous generator excitation system as well as SVC. The LOC is assigned to generate each model’s control signal. The final control signal is made by interpolating the LOC output signals obtained from each model using PCA. Considering a three-phase symmetrical fault on a near bus to the generator, the proposed control strategy is evaluated. This strategy not only maintains stability but also reduces LFO effectively. Furthermore, steady state error of rotor speed and rotor angle tend to zero favorably. Simulations are done for single- and multi-machine power systems via a MATLAB m-code.

Low frequency oscillations in power system with medium-pressure regulating valve of steam turbine occur from time to time， threatening the safe operation of generating units and power system. Three typical low frequency oscillations of power system induced by medium-pressure regulating valve are given. Given the roles of medium-pressure regulating valves in different types of steam turbines， the ways they induce or participate in low frequency oscillations are introduced. It is pointed out that one of the major reasons for low frequency oscillations occurring in deep peaking-shaving units is the reduction of the turbine’s integrated valve position command， resulting in the frequent participation of medium-voltage regulating valves of poor linearity in the power regulation of the units. In view of the current operating environment of thermal power units in China， six specific measures to prevent the medium-pressure valves from participating in low frequency oscillations in power system are given for reference.

With the development of new energy, energy storage, and flexible DC technology, AC/DC hybrid distribution networks have gradually become an important development direction for future distribution networks. The access of a large number of power electronic devices has brought dynamic problems such as low frequency oscillations to the distribution network. In order to deeply study the low frequency oscillation problem on the DC side of AC/DC distribution networks, detailed modeling of key links is conducted such as H-bridge series and isolated bidirectional active bridge structures, three-phase inverters, and three-phase Buck converters in the main valve tower of power electronic transformer. Through time domain simulation, the 4 Hz low frequency oscillation phenomenon on the DC side of the AC/DC distribution network in the actual project is reproduced, and the correctness of the established mathematical model is verified. Based on the established mathematical model, qualitative analysis is conducted on key influencing factors such as power and controller parameters, and the final conclusions are as follows: power level and Buck link voltage loop control parameters affect system stability, the integral coefficient of the current loop in the Buck link affects the oscillation frequency.

In order to study the characteristics of low frequency oscillation of summer precipitation over Qinghai-Xizang Plateau， based on the daily precipitation data of 62 meteorological stations over the Qinghai-Xizang Plateau from 1978 to 2017 and the high-resolution daily reanalysis data of ERA5.This paper adopted the collection of empirical mode decomposition （EEMD）， Lanczos filter and synthesis analysis method.Filter out the years of drought and flood， and analyzed the characteristics of low frequency oscillation， variation of meteorological elements and circulation of precipitation in dry and flood years in summer over the Qinghai-Xizang Plateau.Reveals the drought and flood years， the characteristics of low frequency oscillation period of precipitation in plateau area， the circulation characteristics and low frequency and other transmission characteristics of wind field and vorticity field.The results show that： （1） There is an oscillation period of 10~20 days in summer precipitation over the Qinghai-Xizang Plateau.The period frequency of drought and flood years is different， the oscillation frequency of flood years is obviously higher than that of drought years.In flood years， the significant oscillation is 10~20 days and 30-days oscillation， while in drought years， the oscillation is mainly 10~20 days.（2） In flood years， the low-frequency precipitation phase is strong， the high-altitude low-frequency cyclones control the plateau， the high-altitude divergence， the low-altitude convergence.The water vapor supply from the south of the Bay of Bengal， and the low-frequency disturbance is strong， which is conducive to the occurrence of precipitation， there is an abnormal circulation distribution of low-frequency anticyclone- low-frequency cyclone- low-frequency anticyclone from west to east.On the contrary， in the low frequency precipitation weak phase， the high frequency anticyclone controlled the main body of the plateau， high altitude convergence， low altitude divergence， the warm and wet southerly air is weak， the disturbance is weak， not conducive to the occurrence of precipitation.The distribution of low-frequency anticyclone， low-frequency cyclones and low-frequency anticyclone is not obvious in drought years， and the oscillation intensity is not as strong as that in flood years， and the intensity of low-frequency element field is weak.（3） The transmission of low-frequency fluctuation is different in drought and flood years.In flood years， the high and low plateau is the sink area of low-frequency oscillation， and the meridian is also the convergence area.The precipitation in the oscillation sink area is more frequent， so the precipitation in flood years is more.In the dry years， the low-frequency oscillation propagates upward from the plateau to the upper level， so the low-frequency precipitation occurs less in the dry years.

The development of electric power systems determines the growing probability of low-frequency oscillations, which can be reason of system faults. Traditionally, the task of damping low-frequency oscillations is assigned to synchronous generators, by appropriate setting of the automatic voltage regulator parameters. However, as the installed capacity of renewable generation units increases, research aimed to analyse the impact of these generation units on the power oscillations in the electric power system is becoming more relevant. Moreover, an evaluation of the potential of renewables to solve the problems of power oscillation damping seems necessary to expand the operation functions of the these generation units and to increase the stability of the electric power systems. This paper presents an analysis of renewable energy plants, in particular photovoltaic stations, on damping of these power oscillations. Achieving such damping function is possible via upgrading the automatic control system of photovoltaic stations by using a synthetic inertia block and the possibilities of the “underload” mode. Different scenarios, including small disturbances and severe fault condition for strong and weak grids depending on the location and capacity of photovoltaic station were considered. To evaluate the impact of renewable generation unit to the damping properties of electric power system, the transient damping ratio was calculated. The calculation was carried out in accordance with the guidelines in case of three-phase short-circuit for a different penetration level of renewable generation unit, as well as with and without the synthetic inertia block.

The effect of high-pressure detonation products on fuel injection and propagation characteristics of detonation wave has been investigated in the form of ion voltage by varying the equivalence ratio (ER), air mass flux, and operation duration with hydrogen-air mixtures. It has been shown experimentally that the ion voltage decays gradually during the initial stage of rotating detonation wave (RDW). The attenuation of ion voltage is a general phenomenon, and the decay rate of ion voltage and its peak value of the trough state are related to the equivalence ratio and air mass flux. The analysis of interaction between the combustor and hydrogen plenum indicates that the feedback of high-pressure detonation products leads to the attenuation of ion voltage. In addition, the long-duration tests show that the ion voltage will recover to a steady state with the extension of reaction time, when the purgation (products leaving plenums) of detonation products is greater than feedback (products entering plenums) of detonation products in the hydrogen plenum. The recovery of ion voltage starts earlier at the higher equivalence ratio and air mass flux, and the peak value of ion voltage in the steady state also increases with the increase of equivalence ratio and air mass flux. A low frequency oscillation about 10–12 Hz occurs in the RDW at some operation conditions. This low frequency oscillation is related to the interaction between the combustor and hydrogen plenum, and can be eliminated by either increasing the equivalence ratio or decreasing the air mass flux.

Low frequency oscillation is one of the key problem affecting the safe and stable operation of interconnected power system, variational modal decomposition (VMD) was used to extract low-frequency oscillation signals from ambient data, and a method of low-frequency oscillation modal identification for power systems discrete Fourier transform (DFT)-based curve fitting was proposed in this paper. Firstly, the DC component of ambient data signals was filtered by VMD decomposition to extract low-frequency oscillation signals. The number of VMD decomposition was determined by modal correlation coefficient, which improved the timeliness of signal decomposition. Secondly, the auto regressive moving average (ARMA) model of ambient data was established to simulate the generation of data signals. The DFT curve fitting of low-frequency oscillation signal autocorrelation function was used to estimate the Laplace transform coefficient and extract characteristic parameters of electromechanical oscillation. Finally, Simulation data and some measured phasor measurement unit (PMU) data are used to verify the feasibility and effectiveness of the method. The experiment shows that the sampling VMD algorithm and the curve fitting method based on DFT can extract the characteristic parameters of low-frequency oscillation, which effectively improves the real-time performance of electromechanical small interference stability.

Addressing the issue of system stability is a crucial step towards the successful integration of memristive devices in power electronics applications. This paper focuses on fluorescent lamps possessing memristive characteristics and investigates the instability phenomena and mechanisms within a full-bridge inverter with a fluorescent lamp load. Based on the memristive characteristics of fluorescent lamps, this paper establishes the averaged model of the system, whose coefficient matrix is nonlinear, periodic, and time-varying. This study identifies the occurrence of low-frequency oscillations within the system and elucidates the fundamental mechanism underlying the emergence of low-frequency oscillations. Furthermore, this paper establishes the stability boundaries of the system across different parameter planes. The research findings indicate that the low-frequency oscillations within the system are attributed to the occurrence of Hopf bifurcations in a frequency range higher than line frequency but significantly lower than switching frequency. Lastly, the PSpice circuit of the system is designed, and simulation results are provided for validation. This study can offer guidance on parameters and control strategies for ensuring the stable operation of a full-bridge inverter with fluorescent lamps. Moreover, it can facilitate the comprehension of instability mechanisms in systems incorporating memristive devices, thereby offering a foundation for the expansion of memristor applications.

The ActiGraph GT9X has been implemented in clinical trials to track physical activity and sleep. Given recent incidental findings from our laboratory, the overall aim of this study was to notify academic and clinical researchers of the idle sleep mode (ISM) and inertial measurement unit (IMU)’s interaction, as well as their subsequent effect on data acquisition. Investigations were undertaken using a hexapod robot to test the X, Y and Z sensing axes of the accelerometers. Seven GT9X were tested at frequencies ranging from 0.5 to 2 Hz. Testing was performed for three sets of setting parameters: Setting Parameter 1 (ISMONIMUON), Setting Parameter 2 (ISMOFFIMUON), Setting Parameter 3 (ISMONIMUOFF). The minimum, maximum and range of outputs were compared between the settings and frequencies. Findings indicated that Setting Parameters 1 and 2 were not significantly different, but both were significantly different from Setting Parameter 3. Upon inspection, it was discovered that the ISM was only active during Setting Parameter 3 testing, despite it being enabled in Setting Parameter 1. Researchers should be aware of this when conducting future research using the GT9X.

The increasing number of low-frequency oscillation events has posed significant challenges to power system stability. It is imperative to accurately identify and properly control generators with poor or negative damping contribution for better oscillation damping. This paper proposes a hybrid energy and mode decomposition-based method for evaluating generators damping in multi-machine power systems. It is derived that the aggregate electric torque can be modeled as the superposition of electric torques in different modes. In each oscillation mode, the electric torque can be decomposed into the damping torque and the synchronizing torque. Moreover, a novel oscillation energy function is developed to evaluate generators' damping effect in each oscillation mode. The result proves that in each oscillation mode, generators with attenuated oscillation energies have negative damping effects. Simulation results in single and multinegative damping generators cases, as well as the comparison with other methods, demonstrate the effectiveness and robustness of the proposed method for damping evaluation.

Low frequency oscillation (LFO) in the electric multiple units (EMUs)-traction network cascade system (ETNCS) can lead to traction blockade and abnormal operation. Using the Chinese CRH3 EMUs as an example, a new LFO suppressing method by applying the energy storage (ES) device on EMUs is proposed in this paper and the ES is connected to the DC-link on board. The equivalent model of the ETNCS is established at first. The critical condition of LFO in the ETNCS is analyzed via impedance ratio criterion and Bode diagram. Then, the proposed on-board bidirectional DC-DC converter integrated with the ES system is controlled via a virtual DC machine (VDCM) strategy, and the VDCM small signal model derivation and the parameter design are carried out. Using the Bode diagram of the impedance ratio, the system stability with the ES device controlled by the proposed VDCM scheme is analyzed again; simulation results verify the effectiveness of the control algorithm to suppress the LFO adaptively. Compared with the traditional PI controller, the system steady-state and dynamic performance can be improved with the proposed method, including decreased overshoot, fluctuation, response time, and increased gain margin of the DC-link voltage.

Using NCEP daily reanalysis and observation data, we analyzed the characteristics of the 2020 Meiyu in Shanghai and evaluated the effectiveness of the extended range forecast which is based on the atmospheric low-frequency characteristics. The results show that (1) the 2020 Meiyu in Shanghai was the most severe one since 2000. (2) The excessive precipitation during Meiyu is caused due to the influence by the cold phase of equatorial central-east Pacific and the anomalously warm SST of the tropical Indian Ocean in summer, the strong and stable anomalous anticyclone in the northwest Pacific Ocean and the abnormally strong water vapor transport from its western turn, and the frequent cold air transfer along the direction of wave-activity flux. (3) The precipitation events in the 2020 Meiyu show obvious quasi-biweekly oscillation characteristics, with all four strong precipitation events corresponding to the peaks of low-frequency precipitation. The extended range precipitation forecast method developed based on the low-frequency characteristics is more accurate in predicting the first strong precipitation event in the 2020 Meiyu season.

With the rapid development and wide range application of AC/DC distribution network,its stability has also become the focus. The low-frequency oscillation at the DC side in the commissioning stage of an AC/DC distribution network project is analyzed. Based on the small signal modeling,the eigenvalue analysis method is used to analyze the influence laws of short circuit ratio (SCR),power level and control parameters on low-frequency oscillation. Next,the measures of changing controller parameters and adding additional controllers to suppress oscillation are proposed. The theoretical analysis and simulation test show that weak grid affects the stability of voltage source converter (VSC). Low frequency oscillation occurs when the 375 V DC side power increases to exceed the rated power. The integral coefficient of the Buck converter current inner loop proportional integral (PI) controller does not affect the stability of the system,but it affects the oscillation frequency after the oscillation occurs. If the proportional coefficient of the voltage outer loop PI controller is too small or the integral coefficient is too large,the system is unstable. Changing voltage outer loop PI controller parameters of Buck converter and adding additional controller can effectively suppress low-frequency oscillations. The theory and simulation analysis of the actual AC/DC distribution network oscillation influence factors are of reference significance for the commissioning and operation analysis of other AC/DC distribution network projects.

The appropriate design of the power oscillation damping controllers guarantees that distributed energy resources and sustainable smart grids deliver excellent service subjected to big data for planned maintenance of renewable energy. Therefore, the main target of this study is to suppress the low-frequency oscillations due to disruptive faults and heavy load disturbance conditions. The considered power system comprises two interconnected hydroelectric areas with heavy solar energy penetrations, severely impacting the power system stabilizers. When associated with appropriate controllers, FACTs technology such as the static synchronous series compensator provides efficient dampening of the adverse power frequency oscillations. First, a two-area power system with heavy solar energy penetration is implemented. Second, two neuro-based controllers are developed. The first controller is constructed with an optimized particle swarm optimization (PSO) based neural network, while the second is created with the adaptive neuro-fuzzy. An energy management approach is developed to lessen the risky impact of the injected solar energy upon the rotor speed deviations of the synchronous generator. The obtained results are impartially compared with a lead-lag compensator. The obtained results demonstrate that the developed PSO-based neural network controller outperforms the other controllers in terms of execution time and the system performance indices. Solar energy penetrations temporarily influence the electrical power produced by the synchronous generators, which slow down for uncomfortably lengthy intervals for solar energy injection greater than 0.5 pu.

In this paper, a two-stage mode identification algorithm including preprocessing and identification steps is introduced to solve the problems of measuring noise and inaccurate mode identification in the analysis of low-frequency oscillation (LFO) in a wide area measurement systems (WAMSs). S-G filter de-noising is utilized for the preprocessing. An adaptive total least squares-estimation of signal parameters via rotational invariance techniques (TLS-ESPRIT) algorithm with the order setting of the singular value accumulation percentage adjacency increment ratio (SVAPAIR) is utilized for the identifying stage. The S-G filter is used to mitigate the measuring of LFO noise of the system. Furthermore, the SVAPAIR is adopted to achieve an adaptive and precise determination of the LFO order, and then LFO parameters are extracted by the adaptive TLS-ESPRIT algorithm. The proposed algorithm has been tested and verified using the IEEE four-generator two-area system and the actual measured data of the LFO accident in the North American power grid. The simulation and experimental result showed that the proposed algorithm has better adaptability, anti-noise characteristic, and robustness compared to those of the conventional Prony, matrix pencil (MP), and TLS-ESPRIT algorithms.

Affected by the nonlinear time-varying factors due to fault scenarios, protection relaying, and control measures, the dynamic behaviors of a power system may be significantly different from the results of previous methods. In order to analyze the oscillation characteristics of complex power systems more accurately and suppress the low frequency oscillation more effectively, this paper improves the trajectory section eigenvalue method. Firstly, the time response of a system is obtained by numerical simulation in a given fault scenario. Secondly, the algebraic variables are substituted to the differential equations along the trajectory. Thus, the original time-varying differential-algebraic equations are approximated by a set of linear ordinary differential equations, which can be updated along the trajectory. On this basis, this paper proposes a method to extract instantaneous features of the oscillation from the micro perspective. The non-equilibrium points with strong nonlinearity or critical eigenmodes are identified by the proposed method. The simulation test results of the IEEE 3-machine 9-bus system and the New England system illustrate the validity of the proposed method.

Sub-seasonal variability in meridional activity of Western Pacific subtropical high (WPSH) exerts important influences on anomalous weather and climate in East Asian monsoon region. By using a sub-seasonal meridional index of the WPSH, the characteristics and atmospheric evolutions in association with the sub-seasonal meridional activity of the WPSH during boreal late summer are investigated. The meridional activity of the WPSH exhibits distinctive low frequency oscillation (LFO), with two dominant periods of 10–30 days and 40–50 days. The 10–30 days LFO is influenced by wave trains in mid-high latitudes and convection propagating from tropic. For the northward advance of the WPSH, in the high latitudes, teleconnection wave train originating from Atlantic Ocean propagates eastward, then the negative potential vortex anomalies enhance the high-level divergence in Northeast Asia. In the mid-latitudes, the 10–30 days low frequency wave train from North America propagates westward and influences the pressure field along the East Asia coast, whose energy is gained from the westerly jet through barotropic process. In the tropic, on time scale of 10–30 days, anomalous convections over the equatorial western Pacific propagate northwestward and trigger cyclone-anticyclone circulation anomalies along the East Asia coast, which in turn affect the meridional position of the WPSH. The 40–50 days LFO of meridional activity of WPSH is closely related to the convection anomalies under the interaction between Madden-Julian Oscillation (MJO) and monsoon intra-seasonal oscillation (MISO). The tropical MJO propagates eastward from the equatorial Indian Ocean to West Pacific and then propagates northward, in accompany with the northeastward propagation of anomalous convection teleconnection covering the tropical Indian Ocean-North Indian Peninsula-Northwest Pacific, resulting in the anomalous anti-cyclonic circulation over Northwest Pacific, which contributes to the northward advance of the WPSH. For the southward retreat of the WPSH, the contrary is the case in 10–30 days atmospheric LFO while relatively weaker 40–50 days atmospheric LFO does less contribution to the southward retreat of the WPSH.

Low frequency oscillations in large power systems may result in system instability under large disturbances. Power system stabilisers (PSS) play an effective role in damping these low frequency oscillations by injecting a modulating signal in the excitation loop of a synchronous machine. A new metaheuristic optimisation algorithm termed the sine cosine algorithm (SCA) was proposed for optimising PSS controller parameters to obtain an optimal solution with the damping ratio as an objective function. The SCA technique was examined on a single machine infinite bus (SMIB) system under distinct loading situations and matched with a moth flame optimisation technique and evolutionary programming to design a robust controller of PSS. The simulation was accomplished using a linearised mathematical model of the SMIB. The performance of a designed lead lag-controller of PSS was demonstrated using eigenvalue analysis with simulations, showing promising results. The dynamic performance was validated with respect to the damping ratio, the eigenvalue’s location in the s-plane and rotor angle deviation response to demonstrate system stability.

The low frequency oscillation is a serious threat to security and stability of a power grid. How to locate the disturbance source accurately is an important issue to low frequency oscillation disposal. Existing methods have poor adaptability to the low frequency oscillation with time-varying steady-state points because of the limitations in the location criterion derivation. A disturbance source location method on a low frequency oscillation with good generality is presented in the paper. Firstly, the reasons why the steady-state points are time-varying on a low frequency oscillation are analyzed. Then, based on the energy function construction form, the branch transmission energy is decomposed into state energy, reciprocating energy and dissipation energy by mathematical derivation. The flow direction of the dissipation energy shows the source and destination of the disturbance energy, and the specific location of a disturbance source can be identified according to its flow direction. Meanwhile, to meet the needs of energy calculation, a recognition method on the electrical quantities steady-state points is also presented by using the cubic spline interpolation. Simulation results show the correctness of the derivation and analysis on energy structure in the paper, and the disturbance source can be located accurately according to the dissipation energy.

Large-scale centralized new energy sending system is a unique form of power grid in China. Due to the high proportion of new energy sources and low tolerance to high-voltage direct current(HVDC) fault disturbance, there are prominent problems in the coordination between source and power network. The major potential risks, such as large voltage fluctuation, large frequency fluctuation and low frequency oscillation were analyzed. It was pointed out that the key problems of modeling include the auxiliary control of excitation system, generator protection concerned with network and generator speed control with dynamic system. The simulation evaluation process and precautions of the source network coordination in large-scale centralized new energy sending system were also proposed, which could be a reference for the actual simulation evaluation operation.

For pulse train (PT) controlled switching converter, when it operates in continuous conduction mode (CCM) and discontinuous conduction mode (DCM), there exist disadvantages of low frequency oscillation and narrow load range, respectively. To avoid these disadvantages of PT controlled switching converter in CCM and DCM, a PT controlled boost converter operating in pseudo continuous conduction mode (PCCM) is taken as the research object in this paper, its working principle has been analyzed in detail. Based on the analysis of output voltage ripple during one switching cycle, the combination of high- and low-power control pulses in a repetition cycle is analyzed and the expression of output voltage ripple is derived for different load conditions. Finally, simulation and experiment are performed to verify the correctness of the control pulse combinations and the output voltage ripple analysis. Results show that compared with DCM and CCM boost converters, the PT controlled PCCM boost converter not only has wider load range, but also can suppress low frequency oscillation.

Advances in functional magnetic resonance imaging (fMRI) acquisition have improved signal to noise to the point where the physiology of the subject is the dominant noise source in resting state fMRI data (rsfMRI). Among these systemic, non-neuronal physiological signals, respiration and to some degree cardiac fluctuations can be removed through modeling, or in the case of newer, faster acquisitions such as simultaneous multislice acquisition, simple spectral filtering. However, significant low frequency physiological oscillation (∼0.01–0.15 Hz) remains in the signal. This is problematic, as it is the precise frequency band occupied by the neuronally modulated hemodynamic responses used to study brain connectivity, precluding its removal by spectral filtering. The source of this signal, and its method of production and propagation in the body, have not been conclusively determined. Here, we summarize the defining characteristics of the systemic low frequency noise signal, and review some current theories about the signal source and the evidence supporting them. The strength and distribution of the systemic LFO signal make characterizing and removing it essential for accurate quantification, especially for resting state connectivity, when no stimulation can be compared with the signal. Widespread correlated non-neuronal signals obscure and distort the more localized patterns of neuronal correlations between interacting brain regions; they may even cause apparent connectivity between regions with no neuronal interaction. Here, we discuss a simple method we have developed to parse the global, moving, blood-borne signal from the stationary, neuronal connectivity signals, substantially reducing the negative correlations that result from global signal regression. Finally, we will discuss some of the uses to which the moving systemic low frequency oscillation can be put if we consider it a “signal” carrying information, rather than simply “noise” complicating the interpretation of resting state connectivity. Properly utilizing this signal may offer insights into subtle hemodynamic alterations that can be used as early indicators of circulatory dysfunction in a number of neuropsychiatric conditions, such as prodromal stroke, moyamoya, and Alzheimer’s disease.

This paper presents a measurement-based solution for low frequency oscillation (LFO) analysis in both real time monitoring and off-line case study. An online LFO property discrimination method is developed first, which alternately uses empirical mode decomposition (EMD)/Hilbert transform (HT) and square calculation to process the measurement data. The method magnifies the variation trend of oscillating variables to accurately discriminate the property of the oscillation. Subsequently, an oscillation source locating method for the forced oscillation (FO) and a strongly correlated generator identification method for the weak damping oscillation (WDO) are proposed. Finally, numerical study results on a test system of the isolated Changdu grid in Tibet validate the proposed methods.

The low frequency oscillation characteristics of East China Power Grid after commissioning of the first ultra-high voltage alternating current (UHVAC) project-the Huai-Hu UHVAC project are studied. Several low frequency oscillation cases occurred in East China Power Grid in the past few years are reviewed and summarized. Based on the analysis of the different typical operation modes, the main low frequency oscillation modes in East China Power Grid in the early stages of development of ultra-high voltage (UHV) are summarized, and the impacts of the significant power grid maintenance on low frequency oscillation characteristics are analyzed. Besides, the oscillation mode of UHV generators to East China Power Grid is researched, and the importance of the power system stabilizator (PSS) is emphasized. Furthermore, the comparative analysis between the time domain and the frequency domain is carried out, and the influences of the governing system on low frequency oscillation characteristics are revealed. Finally, both the focus and the direction of low frequency oscillation research are presented.

Deep brain stimulation (DBS) surgery of the subthalamic nucleus (STN) under general anesthesia (GA) had been used in Parkinson's disease (PD) patients who are unable tolerate awake surgery. The effect of anesthetics on intraoperative microelectrode recording (MER) remains unclear. Understanding the effect of anesthetics on MER is important in performing STN DBS surgery with general anesthesia. In this study, we retrospectively performed qualitive and quantitative analysis of STN MER in PD patients received STN DBS with controlled desflurane anesthesia or LA and compared their clinical outcome. From January 2005 to March 2006, 19 consecutive PD patients received bilateral STN DBS surgery in Hualien Tzu-Chi hospital under either desflurane GA (n = 10) or LA (n = 9). We used spike analysis (frequency and modified burst index [MBI]) and the Hilbert transform to obtain signal power measurements for background and spikes, and compared the characterizations of intraoperative microelectrode signals between the two groups. Additionally, STN firing pattern characteristics were determined using a combined approach based on the autocorrelogram and power spectral analysis, which was employed to investigate differences in the oscillatory activities between the groups. Clinical outcomes were assessed using the Unified Parkinson's Disease Rating Scale (UPDRS) before and after surgery. The results revealed burst firing was observed in both groups. The firing frequencies were greater in the LA group and MBI was comparable in both groups. Both the background and spikes were of significantly greater power in the LA group. The power spectra of the autocorrelograms were significantly higher in the GA group between 4 and 8 Hz. Clinical outcomes based on the UPDRS were comparable in both groups before and after DBS surgery. Under controlled light desflurane GA, burst features of the neuronal firing patterns are preserved in the STN, but power is reduced. Enhanced low-frequency (4–8 Hz) oscillations in the MERs for the GA group could be a characteristic signature of desflurane's effect on neurons in the STN.

Recently, low-frequency oscillation (LFO) has occurred many times in high-speed railways and has led to traction blockades. Some of the literature has found that the stability of the vehicle-grid coupling system could be improved by optimizing the control strategy of the traction line-side converter (LSC) to some extent. In this paper, a model-based predictive current control (MBPCC) approach based on continuous control set in the dq reference frame for the traction LSC for electric multiple units (EMUs) is proposed. First, the mathematical predictive model of one traction LSC is deduced by discretizing the state equation on the alternating current (AC) side. Then, the optimal control variables are calculated by solving the performance function, which involves the difference between the predicted and reference value of the current, as well as the variations of the control voltage. Finally, combined with bipolar sinusoidal pulse width modulation (SPWM), the whole control algorithm based on MBPCC is formed. The simulation models of EMUs’ dual traction LSCs are built in MATLAB/SIMULINK to verify the superior dynamic and static performance, by comparing them with traditional transient direct current control (TDCC). A whole dSPACE semi-physical platform is established to demonstrate the feasibility and effectiveness of MBPCC in real applications. In addition, the simulations of multi-EMUs accessed in the vehicle-grid coupling system are carried out to verify the suppressing effect on LFO. Finally, to find the impact of external parameters (the equivalent leakage inductance of vehicle transformer, the distance to the power supply, and load resistance) on MBPCC’s performance, the sensitivity analysis of these parameters is performed. Results indicate that these three parameters have a tiny impact on the proposed method but a significant influence on the performance of TDCC. Both oscillation pattern and oscillation peak under TDCC can be easily influenced when these parameters change.

Large-scale wind power interfacing to the power grid has an impact on the stability of the power system. However, with an additional damping controller of the wind generator, new ways for improving system damping and suppressing the low frequency oscillation (LFO) of power systems can be put forward. In this paper, an active-reactive power additional damping controller based on active disturbance rejection control (ADRC) is proposed. In order to improve the precision of the controller, the theory of data driven control is adopted, using the numerical algorithms for subspace state space system identification (N4SID) to obtain the two order model of the ADRC controlled object. Based on the identification model, the ADRC additional damping controller is designed. Taking a 2-area 4-machine system containing the doubly fed induction generator (DFIG) wind farm as an example, it is verified that the active-reactive additional damping controller designed in this paper performs well in suppressing negative-damping LFO and forced power oscillation. When the operation state of the power system changes, it can still restrain the LFO effectively, showing stronger robustness and better effectiveness compared to the traditional proportional–integral–derivative (PID) additional damping controller.

This paper describes a multiple time interval (“multi-interval”) parameter estimation method. The multi-interval parameter estimation method estimates a parameter from a new multi-interval prediction error polynomial that can simultaneously consider multiple time intervals. The root of the multi-interval prediction error polynomial includes the effect on each time interval, and the important mode can be estimated by solving one polynomial for multiple time intervals or signals. The algorithm of the multi-interval parameter estimation method proposed in this paper is applied to the test function and the data measured from a PMU (phasor measurement unit) installed in the KEPCO (Korea Electric Power Corporation) system. The results confirm that the proposed multi-interval parameter estimation method accurately and reliably estimates important parameters.