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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.

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.

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.

Due to power system oscillations induced by complex interconnections, power system stability has been a major concern and will continue to be a major concern in power system operations. For improving power system stability, efforts have been directed toward damping power system oscillations. The small signal stability is the instability that has been influenced by complex interconnections. Small signal stability can be dampened with power system stabilisers (PSS). PSS, on the other hand, have certain disadvantages, such as significant variations in voltage profiles and the potential for leading power factor operations, which may reduce system stability in the face of severe disturbances. In wide multi machine power systems, using only traditional PSS can not be enough to dampen inter-area oscillations and the effect of voltage profile variation. Power electronic devices known as Flexible Alternating Current Transmission System (FACTS) devices, on the other hand, are good at damping inter-area oscillations and can handle voltage variations. As a result, based on computational intelligence techniques, this paper provides a thorough analysis and evaluation of PSS and FACTS power oscillation damping (POD) controllers in reducing low frequency oscillations. The importance of technical paper publications on PSS and FACTS-based controller design, optimum location, and parameter tuning is highlighted. Finally, the potential future research directions for novel PSS and FACTS devices is proposed as a reference for interested researchers.

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.

Electric railway systems (ERSs) have been challenged with harmonic issues since they have emerged. Different forms of harmonic distortions have been reported in various types of ERSs all over the world which are originated by nonlinear features of trains, power electronic based drive converters, and interaction between multiple trains and ERS. The essential purpose of this paper is to study and classify different forms of harmonic phenomena based on the type of operating ERS, the effective factors, origins of creation, destructive effects and compensation methods. It can provide a perfect perspective on the status of harmonic issues of ERS to researchers and engineers. About 70 research publications are classified and listed in the reference for a quick review of researchers and provide a useful background.

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 in the electrical generator connect to power grid is an important problem to control systems, especially in the gas turbine generators with high speed. The oscillation makes affect to life time, finance of operating and effect of energy process. There are many cause of the oscillation in governor speed control of power plants. They use PSS to do damping low frequency oscillation in recently [11], [12], [13], [14], [22], [23]. So PSS usually does process with delay cycle time, therefore it makes effect isn’t good result. This paper presents a method using linear in the gas turbine generator, which connects to power grid. By observe affect action of local oscillation of the power, study finds key point of oscillation time. From that, we take out decision to do prediction of damping in system and supply signal in to PSS to reduce damaging of this oscillation. Simulation results explain difference action of the system with linear observer and system without linear observer.

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.

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.

Blood-oxygen-level dependent (BOLD) signals are widely used in functional magnetic resonance imaging (fMRI) as a proxy measure of brain activation. However, because these signals are blood-related, they are also influenced by other physiological processes. This is especially true in resting state fMRI, during which no experimental stimulation occurs. Previous studies have found that the amplitude of resting state BOLD is closely related to regional vascular density. In this study, we investigated how some of the temporal fluctuations of the BOLD signal also possibly relate to regional vascular density. We began by identifying the blood-bound systemic low-frequency oscillation (sLFO). We then assessed the distribution of all voxels based on their correlations with this sLFO. We found that sLFO signals are widely present in resting state BOLD signals and that the proportion of these sLFOs in each voxel correlates with different tissue types, which vary significantly in underlying vascular density. These results deepen our understanding of the BOLD signal and suggest new imaging biomarkers based on fMRI data, such as amplitude of low-frequency fluctuation (ALFF) and sLFO, a combination of both, for assessing vascular density.

With the expansion of interconnected power grid, the phenomenon of low frequency oscillation appears unavoidably. In this paper, the existing oscillation mode identifying methods are analyzed from the viewpoint of calculation speed, criterion, calculation accuracy, etc. The applicability of two methods, Prony and ESPRIT are compared mainly. Based on the above research, we put forward a new idea of monitoring power system low frequency oscillation based on WAMS.

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.

U radu su prikazani pokazatelji i metode analize vjerojatnosti stabilnosti oscilacija niske frekvencije međusobno povezane energetske rešetke i daje se analiza slučaja temeljena na stvarnoj uzajamno povezanoj energetskoj rešetki. Kako je poznata probabilistička distribucija raznih nesigurnih čimbenika energetske rešetke, koristi se metoda procjene dvije točke (two-point-estimation) u izračunu vjerojatnosti oscilacija niske frekvencije izazvanih tim nesigurnim čimbenicima zasnovana na metodi izračuna malih perturbacija. Teorija procjene rizika koristi se u analizi stanja nestabilnosti niskofrekventnih oscilacija energetskog sustava izazvanih višestrukim smetnjama, a zatim se daju troškovi upravljanja i mogućnost oscilacija niske frekvencije energetske rešetke. Troškovi između rizika koje su preuzele kompanije i povećanih troškova prijenosa dobiveni su opsežnom analizom vjerojatnosti malih smetnji i velikih smetnji, što može potaknuti operatore rešetke da poduzmu ekonomske i sigurnosne mjere., The indicators and methods of the probabilistic stability analysis of interconnected power grid’s low frequency oscillation are put forward in this paper, and the case study based on the real interconnected power grid is investigated. As the probabilistic distribution of various uncertain factors of power grid is known, the method of two-point-estimation is adopted to calculate the probabilities of low-frequency oscillation caused by these uncertain factors based on small perturbation calculation method. The theory of risk assessment is used to analyse the instability condition of power system’s low frequency oscillation caused by multiple disturbances, and then the control cost and the risk of low frequency oscillation of power grid are given. The expenses between the risks the power grid companies have taken and the costs the transmission capacity has increased are obtained through comprehensive probability analysis of small disturbance and large disturbance, which can give insights for grid operators to address the economy and security issues.

This paper presents an adaptive wide-area damping controller (WADC) based on generalized predictive control (GPC) and model identification for damping the inter-area low frequency oscillations in large-scale inter-connected power system. A recursive least-squares algorithm (RLSA) with a varying forgetting factor is applied to identify online the reduced-order linearlized model which contains dominant inter-area low frequency oscillations. Based on this linearlized model, the generalized predictive control scheme considering control output constraints is employed to obtain the optimal control signal in each sampling interval. Case studies are undertaken on a two-area fourmachine power system and the New England 10-machine 39-bus power system, respectively. Simulation results show that the proposed adaptive WADC not only can damp the inter-area oscillations effectively under a wide range of operation conditions and different disturbances, but also has better robustness against to the time delay existing in the remote signals. The comparison studies with the conventional lead-lag WADC are also provided.