Search

The diffusion of modern electric trains equipped with high-power voltage-source converters has introduced new dynamic interactions with the ac traction power system that may create unexpected low-frequency oscillations (LFOs). This paper presents for the first time a detailed analysis of the operating conditions of electric trains and a traction network, revealing that specific changes in the operating conditions of the train-network system are responsible for the oscillations and may lead to instability. The study is carried out with an analytical dynamic model considering the transient direct current control and focuses on evaluating how the mismatch between the parameters of the controller and the controlled object of the train-network system affects the system dynamics and stability. It is shown that the retuning of controller parameters improves the dynamic performance and the stability of the train-network system, and hence an adaptive mitigation method is proposed to mitigate LFOs adopting a new design of the controller with minimal change and cost to the original system, which provides a simple solution to guide engineering practice in railway traffic. Simulations and experimental results are presented to fully validate the proposed method.

The future Indonesian power grid will have significant REGs, especially in Java Island. Wind and solar photovoltaic (PV) will be the dominating technologies in future Indonesian grid. Although REG can provide clean and sustainable energy, they also cause undesirable effects on system stability due to the uncertainty in their output and different dynamic characteristics. Battery energy storage system (BESS) has been considered as the promising candidate to manage the intermittency and low inertia associated with wind and PV in many future power systems. In addition to the normal functionality, the resilient wide-area power oscillation damping (POD) can be implemented in the BESS to damp the low-frequency oscillation in the system. This research proposes a method to design a resilient wide-area POD in BESS. A grey wolf optimiser (GWO) has been used to synthesise the resilient wide-area POD. The representative dynamic model of Java-Indonesian power system is used to evaluate the performance of the GWO-based resilient wide area POD. From the results, it is evident that the implementation of the proposed controller at BESS successfully damped the critical mode of the system. It is also observed that the proposed controller is robust against the failure of the input signal.

This paper proposes a data-driven adaptive wide-area damping controller (D-WADC) for back-to-back VSC-HVDC to suppress the low frequency oscillation in a large-scale interconnected power system. The proposed D-WADC adopts a dual-loop control structure to make full use of the active and reactive power control of VSC-HVDC to improve the damping of the power system. A data-driven algorithm named the goal representation heuristic dynamic programming is employed to design the proposed D-WADC, which means the design procedure only requires the input and output data rather than the mathematic model of the concerned power system. Thus, the D-WADC can adapt to the change of operating condition through online weight modification. Besides, the adaptive delay compensator (ADC) is added to effectively compensate the stochastic delay involved in the wide-area feedback signal. Case studies are conducted based on the simplified model of a practical power system and the 16-machine system with a back-to-back VSC-HVDC. Both the simulation and hardware-in-loop experiment results verify that the proposed D-WADC can effectively suppress the low-frequency oscillation under a wide range of operating conditions, disturbances, and stochastic communication delays.

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.

The low-frequency dynamics of virtual synchronous machine (VSM) depends on multiple factors. In this study, the oscillation mode of a single VSM is first identified by exploring the evolution of oscillation from synchronous mode to sub-synchronous mode with the variation of structure and parameters. The inter-oscillation modes among multiple VSMs modelled in quasi-state phasor domain are then studied by decomposing into mean motion and relative motion. Inspired by and weak-coupling-based coherency identification, the associated VSM group can be fast identified and used for effective stabilizer location. The approximate eigenvalues can be fast obtained by system decomposition in uniform-damping scenarios or by extended-equal-area-criterion approach in non-uniform-damping scenario. An improved design for lead-lag compensation is proposed to damp both synchronous and sub-synchronous oscillation of VSMs. Effectiveness of the proposed control strategy in grid-connected/islanded mode is verified with real-time simulation.

Wide area control (WAC) is an efficient technique to damp out low frequency oscillation of power system. In this process, the communication delay (constant and random) and multiple data drops in control input signals are major issues. To overcome these problems, in this paper, a wide area predictive control (WAPC) strategy is proposed for power system with lines having thyristor controlled series compensation (TCSC). This method establishes a predictive algorithm that uses variable weighting sequence for an available data window with higher weights to the recent data. Thereby, the proposed method is able to track sudden changes in power system operating conditions satisfactorily. In case of WAPC detects nonavailability of any data in a window, the predicted data for the window are used to fill these gaps. In this way, the proposed approach compensates the data drop(s). The effectiveness of the proposed WAPC is tested for the 39-bus New England system and compared with the local control, WAC, and network predictive control method.

The low-frequency oscillation (LFO) between traction network and electric locomotives is a typical phenomenon in high-speed railway and will result in traction blockade accidents. To analyze the respective contribution of traction network and electric locomotives to LFO and reflect the interaction between them clearly, an RLC circuit model is proposed in this paper. First, the negative incremental resistor and capacitance characteristic of electric locomotives is analyzed. Then, the RLC circuit model is built based on single-input single-output (SISO) supersynchronous and subsynchronous impedance. By analyzing the equivalent impedance parameters and resonance of the RLC circuit, the respective contribution of network and locomotives to LFO and system stability is studied. Furthermore, the influential factors of LFO, both grid parameters and locomotives parameters, are investigated. Finally, the analysis results are verified by simulation and experiments based on RT-LAB. Compared with multiple-input multiple-output (MIMO) impedance model, the proposed RLC circuit model can not only explain the LFO phenomena in high-speed railway intuitively and clearly but also simplify the calculation procedure.

The coordination of flexible AC transmission systems (FACTS) with power system stabilizers (PSS) can significantly enhance the overall network stability by damping out the low-frequency oscillations (LFO). This paper proposes a multi-gene genetic programming (MGGP) approach to optimize PSS parameters coordinated with unified power flow controller (UPFC) to enhance power system stability by damping out LFO. The obtained results (minimum damping ratio, eigenvalues and time domain simulations) of the proposed MGGP approach are compared with the results of the conventional fixed gain model, the single-gene genetic programming (SGGP) approach and the referenced work to inquire the efficacy of the proposed approach for various operating conditions of the considered electric network. Besides, the acceptable values of standard statistical performance measures in estimating UPFC-PSS parameters provide confidence on the evolved MGGP models. Furthermore, the proposed approach requires a minimal time (∼less than a cycle) to estimate the key parameters that signal the real-time application of the proposed technique.

A plane-radial rotating detonation engine (RDE) was tested to identify the impact of different injection conditions on the propagation mode and parameters of rotating detonation wave (RDW). Changing the mass flow rate and equivalence ratio, various propagation modes were obtained in experiments: one-wave mode, two-wave mode, three-wave mode and unstable propagation mode. The operating ranges of various propagation modes were acquired. Results indicate that, in this structure, under the condition of stoichiometric ratio, when mass flow rate is less than 122 g/s, the RDE operates in unstable mode, and the RDW propagation velocity is less than 1500 m/s at Ф102 mm. Low frequency oscillation occurs in unstable mode, and the oscillation frequency is approximately 300 Hz. When mass flow rate is greater than 122 g/s, with the increase of mass flow rate, the propagating mode is transformed from one-wave mode to two-wave mode, and then changes into three-wave mode. The propagation velocity in one-wave mode is higher than that in other modes, and varies from 1785 to 1900 m/s. The velocities in two-wave and three-wave mode have little difference, and vary from 1547 m/s to 1650 m/s in two-wave mode, and from 1525 m/s to 1578 m/s in three-wave mode. The mass flow rate has only a slight effect on the RDW propagation velocity, but a large effect on the pressure peak under the same mode. Furthermore, the variation of equivalence ratio will alter the propagation mode, and the RDE operating range of equivalence ratio widens as the mass flow rate increases.

Grid-voltage feedforward control is widely used in grid-tied converters. The reported studies show that the grid-voltage feedforward may reduce the system stability margin, and may lead to oscillation problem in renewable power generation system. This study revisits the effect of voltage feedforward control on system stability and especially focuses on low frequency oscillation with impedance-based method. The low frequency oscillation usually happens in industry around 100 Hz and shows frequency coupling characteristics. A converter equivalent impedance which includes the effects of voltage feedforward and also covers the frequency coupling introduced by phase locked loop (PLL) is established. Based on the built impedance, the effect on oscillation mechanism with voltage feedforward and PLL is revealed. The results show that the voltage feedforward could increase the system stability margin and may be employed to improve the system stability. Then how to design an optimal proportional voltage feedforward control is demonstrated. Experimental results verify the theoretical analysis and the design of the proportional grid-voltage feedforward control.

This article presents a scheme using singular value decomposition (SVD) combined group search optimizer (GSO) algorithm to estimate the parameters of low frequency oscillation (LFO) in power grids....

Aiming at the phenomenon of traction blockades due to the low-frequency oscillation (LFO) in electrified railways, a control strategy of electric multiple units (EMUs) traction line-side converter (LSC), based on the extended state observer (ESO) sliding mode control (SMC) is proposed in this paper. First, the mathematical model of EMUs LSC in the d-q frame is deduced. Then, the principles and design processes of the proposed control strategy are analyzed in detail, including the combination of the outer loop voltage sliding mode with ESO and the control law of the inner loop. Moreover, the simulation model of doubly redundant LSC of EMUs is built in MATLAB/Simulink. The simulation results are compared with the traditional linear proportional integral (PI) control and the basic SMC. It is shown that the proposed ESO + SMC control strategy has better dynamic and static characteristics. Finally, the simulation model of multiple EMUs connected to vehicle-grid coupling systems is built, and an integrated dSPACE semi-physical experimental platform consisting of eight EMUs and an equivalent traction network is constructed to further verify the suppressing effect of LFO. The experimental results show that, the proposed ESO + SMC can effectively suppress the LFO.

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.

Aiming at the high-frequency resonance (HFR) and low-frequency oscillation (LFO) phenomena in high-speed railways, a comprehensive suppression method named voltage constant transient active oscillation compensation (VCT-AOC) is proposed. This method is optimized on the basis of AOC, and the adjustment time is shortened by the VCT suppression measure. When serious HFR happens, the system can be quickly restored and stabilized by completely removing the network voltage oscillation in the control part, thereby avoiding the transient overvoltage and overcurrent damage to the system. According to the characteristics of AOC and VCT, the VCT-AOC comprehensive suppression method is proposed, and the specific implementation scheme of this method is given. This paper established the train-network impedance model with AOC and VCT suppression methods. The Generalized Nyquist Analysis (GNA) method and the dominant pole analysis method are used to analyze the effect of VCT and AOC on the system. Finally, the effectiveness of suppression methods is verified by simulations and experiments.

The dynamic stability of ultra-high voltage alternating current (UHVAC) transmission system with large-scale power bases has not been clearly discussed before. This paper studies the low frequency oscillation (LFO) characteristic of UHVAC system through complex torque coefficient method (CTCM) and finds out the reasons why UHVAC system is more vulnerable to LFO problem. It is pointed out that the bulk capacity and long distance make UHVAC system’s damping torque coefficient much smaller than conventional system’s, which lets UHVAC system’s operation point closer to the safety edge and decreases system’s dynamic stability. The comparisons between UHVAC system and conventional system in practical multi-machine systems further validate the theoretical analysis. Finally, the suggestions for UHVAC systems are given based on the analysis in the view of dynamic stability.

In this paper, the adaptive filtering based on LMS algorithm is applied to the recognition of low-frequency oscillation mode. The step factor is improved based on Sinh function to accelerate the convergence speed of the algorithm while ensuring a low steady-state error, and the robustness of the algorithm in identification is improved by combining the maximum correlation entropy rule. The effectiveness of the algorithm for low-frequency oscillation mode identification is verified by simulation of the 10-machine 39-node New-England power system.

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.

Undamped low frequency oscillations (LFOs) may lead to system collapse. LFOs is closed to the small-signal stability, and traditionally analyzed using model-based method. New measurement-based identification methods are presented in the last decades based on phasor measurement units (PMUs). In this paper, the drawbacks of the model-based techniques for the LFOs analysis are investigated. Firstly, a three-area test system is modified in two configurations: string and ring for LFOs analysis purposes. The modified system has three local area modes and two interarea modes. The impacts of the load changes and topology changes on the electromechanical eigenvalues, observability, controllability, and modal shape are investigated. The results show that electromechanical oscillation modes are highly affected by the load and topologies. The damping controller based on model-based algorithm may inject negative damping if the topology of the system is changed. The system is modeled in differential-algebraic equation set (DAEs) and conducted in MATLAB/Coding environment.

Due to that VSG (virtual synchronous generator) simulates the operation characteristics of SG (synchronous generator), similar stability issue that is common in traditional power system may also exist in VSG grid-connected system. In this paper, the low frequency oscillation of VSG is studied, with the influence of reactive power control and dq-axis voltage control considered especially. Firstly, a small signal model of VSG with voltage/current double closed loop control and active/reactive power control is developed. Based on the model, the low frequency oscillation of VSG is explored. It is identified that the low frequency oscillation mode is dominated by virtual rotor motion, which is similar as that in SG. Further, participation factor analysis and parameter sensitivity analysis reveal that the reactive power loop and dq-axis voltage control have much influence on the damping of the low frequency oscillation. Finally, simulated results are presented to verify the analytical results.

In recent years, more and more attention has been paid to the safe and stable operation of electrified railway, especially to the vehicle-network coupling stability, which focuses on the phenomena of high frequency resonance (HFR) and low frequency oscillation (LFO), which has become the research hotspot. Firstly, this paper studies the impedance model of the traction network and the train power system, and proposes the AF-RCS impedance model of the vehicle-network. Based on this model, from the perspective of grid-side converter control strategy, AOC inhibition measures are proposed to solve the instability of vehicle-network coupling caused by insufficient system damping. Furthermore, VCT inhibition measures were proposed to quickly reduce the damage of HFR to the system. Finally, the VCT-AOC comprehensive suppression strategy was proposed, which improved the damping ratio and enhanced the stability of the system while rapidly protecting the system. The effectiveness of the method is verified by simulation and experiment.

The measurement of harmonics is one of the key tasks in modern power systems, performed basically for power quality assessment, verification of planning levels compliance, immunity and compatibility purposes, and so on. Especially at medium voltage (MV) and high voltage (HV) levels, harmonics are always measured through voltage and current transformers (VTs and CTs), which very often are inductive. Recent articles show that inductive VTs and CTs, due to the intrinsic iron core nonlinearity, can introduce errors up to some percent in harmonic measurements. This article aims to investigate in-depth this phenomenon by analyzing how the accuracy of harmonic measurements performed through an inductive MV VT is affected by the presence subharmonics in its input voltage. Subharmonics are spectral components having frequencies lower than the power frequency, that is 50 Hz for European countries. Some theoretical considerations are carried out and the performances of two different inductive MV VTs are tested in various operating conditions. Experimental results show that subharmonics can worsen the harmonic measurements done through inductive VTs up to some tens of percent.

Low frequency oscillation is an important attribute of human brain activity, and the amplitude of low frequency fluctuation (ALFF) is an effective method to reflect the characteristics of low frequency oscillation, which has been widely used in the treatment of brain diseases and other fields. However, due to the low accuracy of the current analysis methods for low frequency signal extraction of ALFF, we propose the Fourier-based synchrosqueezing transform (FSST), which is often used in the field of signal processing to extract the ALFF of the low frequency power spectrum of the whole-time dimension. The low frequency characteristics of the extracted signal are compared with those of FSST and fast Fourier transform (FFT) through the resting-state data. It is clear that the signal extracted by FSST has more low frequency characteristics, which is significantly different from FFT.

Shock response spectrum (SRS), calculated according to shock loading signal, is the primary metric for assessing the shock resistance ability of shipborne equipment. Nevertheless, the measured shock acceleration signal contains a trend term error that severely distorts the low frequency of the SRS. The accuracy of present correction methods cannot be assured due to a lack of reference. A discrete wavelet transform (DWT) and low-frequency oscillator combination method is proposed for correcting shock signals in this paper. The optimal wavelet parameters can be selected according to a low-frequency spectrum baseline fitted by the measured relative displacement to reject low-frequency trend term errors. Shock machine test results show that the average difference between the low-frequency spectrum baseline and uncorrected SRS is reduced from 89.8% to 3.2%, while the SRS slope rolled off to 5.8 dB/oct after imposing the proposed correction. The corrected SRS can faithfully show the actual shock loading characteristics of shipborne equipment in shock tests.

Low frequency oscillation (LFO) is one of the major concerns for reliable operation of the power system. This LFO occurs due to the failure of the rotor to supply sufficient damping torque to compensate the imbalance between mechanical input and electrical output. Hence, in this paper, we adopt a third generation flexible AC transmission system (FACTS) device named generalized unified power flow controller (GUPFC) based damping controller in order to investigate its effect for mitigating LFO for an single machine infinite bus (SMIB) system. To find an effective damping controller-optimizer pair, we integrate proportional–integral (PI) or lead–lag as a controller and grey wolf optimizer (GWO), differential evolution (DE), particle swarm optimization (PSO), whale optimization algorithm (WOA), and chaotic whale optimization algorithm (CWOA) as an optimizer. Later, we investigate the performances for the above mentioned controller-optimizer pairs through time domain simulation, eigenvalue analysis, nyquist stability test, and quantitative analysis. Moreover, we carry out two non-parametric statistical tests named as one sample Kolmogorov–Smirnov (KS) test and paired sample t − t e s t to identify statistical distribution as well as uniqueness of our optimization algorithms. Our analyses reveal that the GWO tuned lead–lag controller surpasses all other controller-optimizer combinations.

Optimized damping ratio of power system can effectively suppress the system low frequency oscillation. An improved gravity search algorithm is proposed for coordination and optimization the parameters of the power system stabilizer based on the standard gravity search algorithm. This algorithm introduces the black hole concept and devour operation to increase the search speed and convergence accuracy of the algorithm, balance the global search ability and local exploitation ability of the optimization algorithm, and improve its overall optimization performance. In addition, the eigenvalue and mechanical and electrical oscillating mode characteristics working on various operating conditions of the system are optimized as objective functions to ensure the adaptability and robustness of the coordinated optimization strategy. Finally, the suggested method is executed on the classical WSCC three-generator nine-bus system for confirming its efficacy. The results show that the damping characteristics of the power system have been optimized and power system low frequency oscillation has been effectively suppressed.

El Nino, the major large-scale driver of the Indian summer monsoon (ISM), being a trans-oceanic phenomenon, is nonlinearly related to ISM. The mechanistic exploration of this nonlinearity and its quantification in the energy exchange perspective has been demonstrated in this chapter. Considering El Nino as a low frequency oscillation having a time period of 12–18 months, the mechanism of El Nino—monsoon nonlinear relation is explored by quantifying this nonlinearity in terms of interscale transfer of kinetic energy through the process of nonlinear triad interactions in the frequency domain. The study illustrates that the variability of ISM rainfall is strongly dictated by the contrasting nonlinear interactions of El Nino with high and low frequency dominant monsoon modes and are examined for two opposite relationships between El Nino and ISM. This work has paved a way to propel further research in the space of nonlinearities through scale interaction mechanisms between these two large-scale phenomenon.

Due to enduring nature, low frequency oscillation (LFO) modes are most critical modes in a power system. Therefore, these modes should be identified to design proper control mechanism. In this article, wide-area power system stabilizer (WAPSS) is designed to dampout the low frequency inter-area mode. First using detailed model of power system, linear state-space model is obtained at a stable equilibrium point. Then critical inter-area mode is identified amongst all low frequency oscillation modes using small-signal stability analysis. Furthermore, based on highest geometric measures of joint controllability and observability, control loop is selected. Phase compensation and gain of WAPSS are determined by classical residue method and eigenvalue sensitivity method respectively. The proposed method of WAPSS design is tested on 4-machine 11-machine power system and comparatively complex New England-New York 16-machine 68-bus power system. Results obtained on MATLAB/SIMULINK® platform shows the satisfactory damping performances with WAPSS for small disturbances.

In recent years, machine learning (ML) tools have gained tremendous momentum and received wide-spread attention in different segments of modern-day life. As part of digital transformation, the power system industry is one of the pioneers in adopting such attractive and efficient tools for various applications. Apparently, a nonthreatening, but slow-burning issue of the electric power systems is the low-frequency oscillations (LFO), which, if not dealt with appropriately and on time, could result in complete network failure. This paper addresses the role of a prominent ML family member, particle swarm optimization (PSO) tuned adaptive neuro-fuzzy inference system (ANFIS) for real-time enhancement of LFO damping in electric power system networks. It adopts and models two power system networks where in the first network, the synchronous machine is equipped with only a power system stabilizer (PSS), and in the other, the PSS of the synchronous machine is coordinated with the unified power flow controller (UPFC), a second-generation flexible alternating current transmission system (FACTS) device. Then, it develops the proposed ML approach to enhance LFO damping for both adopted networks based on the customary practices of statistical judgment. The performance measuring metrics of power system stability, including the minimum damping ratio (MDR), eigenvalue, and time-domain simulation, were used to analyze the developed approach. Moreover, the paper presents a comparative analysis and discussion with the referenced works&rsquo, achieved results to conclude the proposed PSO-ANFIS technique&rsquo, s ability to enhance power system stability in real-time by damping out the unwanted LFO.

Power low-frequency oscillation is a complex dynamic behavior of the power system, which is related to the safe and stable operation of the power grid. This paper studies the mechanism of the unit’s low-frequency oscillation during a frequency modulation action of the unit. It is pointed out that during a frequency modulation action, when the projection of the mechanical torque vector of the unit on the axis of the speed offset is positive, it means that the mechanical torque characteristic is negative damping. If the negative damping component is too large and exceeds the positive damping component after power system stabilizer compensation, the unit will show negative damping characteristics as a whole, which will cause adjustment power oscillation. Based on the historical data of the synchronous phasor measurement unit in the low-frequency oscillation event of the coal-fired unit, it is judged that the low-frequency oscillation is a forced oscillation caused by the primary frequency modulation of the unit. Through mechanism analysis, the unit coordinated control system exits, the digtal electric hydraulic control system is put into the closed loop mode of the power loop, and the logic setting of the primary frequency modulation command switching is unreasonable, resulting in a substantial increase in valve position output commands. It is equivalent to that the forward open loop gain of the speed channel is too large, which causes the negative damping component of the mechanical torque to be too large, which causes the regulation oscillation. Through simulation demonstration, it is determined that during the primary frequency modulation, the unreasonable logic setting and parameter setting of the primary frequency modulation control loop are the main reasons for the low frequency oscillation of the coal-fired unit power. Finally, the main measures to eliminate the unit oscillation caused by the primary frequency regulation of the unit and the suggestions for stable operation of the unit are put forward.

Power system stabilizer (PSS) is used to generate excitation system auxiliary control signals which can suppress low frequency oscillation in power system. It has the ability of self-learning and parameter online tuning, which is a development trend of smart grid PSS controller in the future. This paper presents a design method of power system stabilizer based on reinforcement learning. Q-learning algorithm is one of reinforcement learning, and is used to PSS as the additional control. The simulation results show that the PSS based on Q-learning can effectively improve the ability of suppressing low frequency oscillation in power system, and the robustness of the system is significantly enhanced.

For traditional Multivariate Empirical Mode Decomposition method (MEMD) in the processing of multichannel measurement information, there is a data imbalance between the measurement channel and data correlation caused by the large error of dominant oscillation mode identification result, and the mode mixing phenomenon has not been effectively eliminated. This paper proposes a novel MEMD method based on Adaptive Projection (APIT - MEMD) for dominant oscillation mode identification method of power system. APIT-MEMD is first used to decompose the multi-channel measurement information containing oscillation information and accurately isolate the Intrinsic Mode Functions (IMF) signals containing the IMF in each measurement channel. Then, the Teager energy criterion is used to select IMF signals that can represent the dominant oscillation mode. Furthermore, the Hilbert-Huang Transform (HHT) is used to estimate the frequency and damping ratio of the dominant oscillation modes in each IMF. Finally, the proposed method is applied to the IEEE-68 bus system for method analysis and verification.

The accuracy of oscillation mode information become an essential reference to large-scale dynamics power system with a high proportion integration of converters. However, the difference in the data trend of the measurement unit will affect the recognition accuracy of the oscillation. To address this problem, this paper first proposes a Dynamic Ensemble Intrinsic Time-Scale Decomposition (DEITD) to remove the data trend. It improves the fitting effect of trends by optimizing the modal aliasing and number of decomposition. Next, the Yule-Walker based Auto Regressive Moving Average (ARMA) technique is utilized to estimate the low frequency oscillation modes. Multiple experiments on simulation and actual signals manifest that the proposed framework has better performance and is more real-time than some conventional methods, which can be used as the control signal of the converter-based fast frequency reserve to enhance the system stability.