Search Results (29)

The peculiarity of the functioning of modern electric power systems, caused by the presence of renewable energy sources, flexible control devices based on power electronics, and the reduction of the reserve of the transmission capacity of the electric network, increases the relevance of identifying and damping low-frequency oscillations (LFOs) of the electrical mode. This paper presents a comparative analysis of methods for estimating the parameters of low-frequency oscillations. Their applicability limits are shown as well as their peculiarity associated with low adaptability, and time costs in assessing the parameters of the electrical mode with low-frequency oscillations are revealed. A method for the accelerated evaluation of low-frequency oscillation parameters is proposed, the delay of which is ¼ of the oscillation cycle. The method was tested on both synthetic and physical signals. In the first case, the source of data was a four-machine mathematical model of a power system. In the second case, signals of transient processes occurring in a real power system were used as physical data. The accuracy of the proposed method was obtained by calculating the difference between the original and reconstructed signals. As a result, calculated error values were obtained, describing the accuracy and efficiency of the proposed method. The proposed algorithm for estimating LFO parameters displayed an error value not exceeding 0.8% for both synthetic and physical data. Full article

The integration of inverter-based resources (IBRs) is reshaping power grid operation by reducing system inertia, which impacts small-signal rotor angle stability and increases low-frequency oscillations (LFOs). While power-electronics-based flexible AC transmission systems (FACTSs) have been the primary solution, the shift of IBR control toward grid forming (GFM) is changing this approach. GFM control inherently provides inertia and affects small-signal stability, but implementing power oscillation damping (POD) algorithms in these inverters presents challenges, particularly regarding active-power-based ones (POD-P). Although various POD-P solutions are emerging for GFM inverters, few studies have evaluated their impact on the GFM device itself and their inherent capabilities, such as inertia and damping. This paper proposes that any design methodology should consider, besides the impact of POD controls on the grid, their effect on the properties of GFM devices. It introduces a theoretical framework using the network frequency perturbation (NFP) approach to assess this impact. Additionally, a simple POD-P control method is proposed for GFM controllers, with simplicity as its key advantage. The desired damping effect, along with the absence of impact on other frequency components, is verified through NFP analysis. The theoretical findings are experimentally validated with test bench results. Full article

Low-frequency oscillation (LFO) poses significant challenges to the dynamic performance of hydropower unit regulation systems (HURS) in hydropower units sharing a tailwater system. Previous methods have struggled to effectively suppress LFO, due to limitations in governor parameter optimization strategies. To address this issue, this paper proposes a governor parameter optimization strategy based on the crayfish optimization algorithm (COA). Considering the actual water diversion layout (WDL) of a HURS, a comprehensive mathematical model of the WDL is constructed and, combined with models of the governor, turbine, and generator, an overall HURS model for the shared tailwater system is derived. By utilizing the efficient optimization performance of the COA, the optimal PID parameters for the HURS controller are quickly obtained, providing robust support for PID parameter tuning. Simulation results showed that the proposed strategy effectively suppressed LFOs and significantly enhanced the dynamic performance of the HURS under grid-connected conditions. Specifically, compared to before optimization, the optimized system reduced the oscillation amplitude by at least 30% and improved the stabilization time by at least 25%. Additionally, the impact of the power grid system parameters on oscillations was studied, providing guidance for the optimization and tuning of specific system parameters. Full article

In this paper, a Takagi–Sugeno fuzzy parallel distributed compensation control (TS-PDCC) is proposed for low-frequency oscillation (LFO) suppression in wind energy-penetrated power systems. Firstly, the fuzzy C-mean algorithm (FCMA) is applied to cluster the daily average wind speed of the wind farm, and the obtained wind speed clustering center is used as the premise variable of TS-PDCC, which increases the freedom of parameter setting of the TS fuzzy model and is closer to the actual working environment. Secondly, based on the TS fuzzy model, the TS-PDCC is designed to adjust the active power output of the wind turbine for LFO suppression. To facilitate the computation of controller parameters, the stability conditions are transformed into a set of Linear Matrix Inequalities (LMIs) via the Schur complement. Subsequently, a Lyapunov function is designed to verify the stability of the wind energy-penetrated power system and obtain the parameter ranges. Simulation cases are conducted to verify the validity and superior performance of the proposed TS-PDCC under different operating conditions. Full article

A frequency up-conversion piezoelectric energy harvester (FUC-PEH) consists of a force amplifier, a piezoelectric stack, a low-frequency oscillator (LFO), and a stop limiter. The force amplifier generates the amplification of stress on the piezoelectric stack. The LFO, comprising a spring and a mass block, impacts the stop limiter during vibration to induce high-frequency oscillations within the piezoelectric stack. In this paper, we represent and simplify the FUC-PEH as a lumped-parameter model based on piezoelectric material constitutive equations and structural dynamic theories. Using the electromechanical analogy, we developed an equivalent circuit model (ECM) of the FUC-PEH. A parametric study was performed to investigate the impact of system parameters, such as spring stiffness and concentrated mass, on the FUC-PEH performance. The collision-induced amplitude truncation (AT) effect enlarges the operation bandwidth. ECM simulations show that low-frequency input excitation is converted into a high-frequency output response, enhancing the energy conversion efficiency. Furthermore, we aimed to improve the FUC-PEH’s performance using a synchronous electric charge extraction (SECE) circuit. Using the ECM approach, we established a system-level model that considers the electromechanical coupling behavior. The simulation results provide insights into the performance of FUC harvesters with SECE circuits and offer valuable design guidance. Full article

Low-frequency oscillation (LFO) of the synchronous generators in power systems by wind power is boring. To improve the robustness of the damping control scheme, this paper applies the sliding mode control (SMC) at the doubly fed induction generator (DFIG), with the parameter of the SMC optimized by the eigen-sensitivity. The originalities lie in, (1) the states strongly associated with the critical modes are newly applied to design the sliding surface, (2) the closed-loop model of the power system with the improved equivalent control is derived to analyze the damping effect on the critical modes and the undesirable effect on the noncritical modes, (3) the gain in the improved equivalent control is optimized to damp the critical and noncritical modes, and (4) the eigenvector sensitivity is improved to derive the second-order eigen- sensitivity to solve the nonlinear optimization. Numerical results show that the proposed model damps the critical modes effectively for different wind speeds, while the undesirable effect on the noncritical modes is avoided. Full article

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

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

The use of the conventional dual closed-loop control strategy by photovoltaic (PV) plants with grid-connected inverters may weaken the damping of a power system, which may aggravate low-frequency oscillations (LFOs). This influence will become more severe as the penetration of PV plants increases. Therefore, it is necessary to incorporate damping controls into PV plants to suppress LFOs. This paper proposed an additional compound damping control (ACDC) system that combines additional damping control (ADC) for the inverter with ADC-based dynamic power compensation control (DPCC), allowing hybrid energy storage systems (HESSs) to suppress LFOs. First, the feasibility of suppressing low-frequency oscillations in PV plants is demonstrated by the torque method and a small signal model. Then, an additional damping controller is added to the active power control link of the PV inverter to enhance the damping abilities of the system. However, given that the damping performance of PV plants with only ADC is limited by the compensated power, PV plants require devices that can rapidly compensate for the damping power. Therefore, we added the HESS to the DC bus and proposed DPCC. Finally, a three-machine nine-node system for a PV plant was modeled and simulated in the PSCAD platform. The simulation results showed that the proposed control strategy could provide effective damping for interarea oscillation. Full article

The interline power flow controller (IPFC) can control the active power and reactive power of different lines in power system. To utilize the flexible control ability of IPFC and increase the damping characteristic of its controller AC system, this paper proposes a low-frequency oscillation (LFO) suppress method through IPFC. The LFO suppress method is designed by adding supplementary signals to the outer current control loop of IPFC. In addition to adding supplementary active power signals, the reactive supplementary signals are also added to related control loop, which is the total control scheme. To obtain the power system’s small signal model, the identification technology based on the PRONY algorithm is used. In addition, the robust control theory is also applied to make the controllers more adaptive. To verify the effectiveness of the proposed method, two controllers including both the active and reactive controllers are designed for in PSCAD software. Furthermore, the simulation results prove the proposed method can reach a better control effect and is also of robustness. Full article

Using daily minimum temperature data at 2481 stations provided by the National Meteorological Information Center (China) and the daily reanalysis data from NCEP/NCAR during the period from 1980 to 2019, the effects of atmospheric low frequency oscillations (LFOs) on the regional strong cooling events (RSCEs) in the winter of northern China are investigated, and the extended range forecast signals of the RSCEs are extracted. The results show that: (1) The frequency of RSCEs is higher before the year 2000 and then decreases, but its interannual variability increases. There are 10–20, 20–30 and 30–60 d significant low frequency periods in the regional average minimum temperature in northern China, and the low frequency oscillation with a period of 10–20 d is the most significant. (2) The low frequency key systems affecting RSCEs in the west, middle, and east of northern China are the Ural blocking high and the trough of Lake Balkhash-Baikal (Lake Ba-Bei), the blocking high in the northwest and the low trough in the southeast of Lake Ba-Bei, the Lake Ba-Bei blocking high and the East Asian trough, respectively, and the Siberian High (SH) that expands and moves with the blocking high all the time. The low frequency jets at the upper level are weaker in the north and stronger in the south. (3) The low frequency high potential vorticity (PV) center in the lower stratosphere moves eastward and southward along the 315 K isentropic surface via the north of Lake Ba-Bei, southern Lake Baikal and Northeast China to the Sea of Japan, causing the 2 PVU line to move southward and then the above-mentioned high PV center in the mid-high troposphere to extend vertically. Meanwhile, under the influence of gradually increasing upper level jets and vertical meridional circulation, the high PV column continues to propagate downward to the mid-low troposphere at lower latitudes along the 300–315 K isentropic surfaces, which enhances the low frequency positive vorticity and deepens the key trough. In addition, the convergence in the upper troposphere, the divergence in the lower layer, and the development of descending motion behind the trough lead to the development and southward movement of the SH. (4) At −10 d, the positive and negative low frequency anomalies at 500 hPa geopotential height appearing in the East European Plain and Western Siberian Plain are the extended range forecast signals for RSCEs in the winter of northern China, respectively. Full article

Dynamic interactions between AC railway electrification systems and traction unit power converters can result in low frequency oscillation (LFO) of the contact-line voltage amplitude, which can lead to a power outage of the traction substation and the shutdown of train traffic. Several system parameters can influence the low frequency stability of the railway traction power system, including contact-line length and traction unit parameters such as transformer leakage inductance, DC-link capacitance, control bandwidths and synchronization systems. This paper focuses on the influence of these parameters on the LFO. The methodology is based on a frequency-domain analysis. Nyquist and Bode diagrams are used to determine the stability limit. The validation of the method is performed through the use of time-domain simulations. Full article

This paper proposes adding a controller to the energy storage system (ESS) to enhance their contribution for damping low-frequency oscillation (LFO) in power systems integrated with high penetration of different types of renewable energy sources (RES). For instance, wind turbines and photovoltaic (PV) solar systems. This work proposes superconducting magnetic energy storage (SMES) as an ESS. The proportional–integral–derivative (PID) and fractional-order PID (FOPID) are suggested as supporter controllers with SMES. The PID and FOPID controller’s optimal values will be obtained using particle swarm optimization (PSO) is used as the optimization method. Both local area and inter-area oscillation is considered in this work as a LFO. To investigate the impact of adding the SMES with the proposed controller, a multimachine power system with different integration scenarios and cases is carried out with a PV system and wind turbine. The system responses are presented and discussed to show the superiority of the proposed controller both in the time domain and by eigenvalues analysis. Full article

This paper investigates the impact of doubly-fed induction generator (DFIG) wind farms on system stability in multi-generator power systems with low-frequency oscillations (LFOs). To this end, this paper establishes the interconnection model of the equivalent generators and derives the system state equation. On this basis, an updated system state equation of the new power system with integrated wind power is further derived. Then, according to the updated system state equation, the impact factors that cause changes in the system damping characteristics are presented. The IEEE two-area four-machine power system is used as a simulation model in which the LFOs occur. The simulation results demonstrate that the connection of wind power to the power feeding area (PFA) increases the damping ratio of the dominant mode of inter-area oscillation from −0.0263 to −0.0107, which obviously improves the system stability. Furthermore, the wind power integration into PFA, as the connection distance of the wind power increases, gradually decreases the damping ratio of the dominant mode of the inter-area oscillation to −0.0236, approaching that of no wind power in the system. Meanwhile, with the increase in the wind power output capacity, the damping ratio of the dominant mode of the intra-area and inter-area oscillation increases, and the maximum damping ratios reach 0.1337 and 0.0233, respectively. Full article

Recognition of typical patterns of brain response to external stimuli using near-infrared spectroscopy (fNIRS) may become a gateway to detecting covert consciousness in clinically unresponsive patients. This is the first fNIRS study on the cortical hemodynamic response to favorite music using a frequency domain approach. The aim of this study was to identify a possible marker of cognitive response in healthy subjects by investigating variations in the oscillatory signal of fNIRS in the spectral regions of low-frequency (LFO) and very-low-frequency oscillations (VLFO). The experiment consisted of two periods of exposure to preferred music, preceded and followed by a resting phase. Spectral power in the LFO region increased in all the subjects after the first exposure to music and decreased again in the subsequent resting phase. After the second music exposure, the increase in LFO spectral power was less distinct. Changes in LFO spectral power were more after first music exposure and the repetition-related habituation effect strongly suggest a cerebral origin of the fNIRS signal. Recognition of typical patterns of brain response to specific environmental stimulation is a required step for the concrete validation of a fNIRS-based diagnostic tool. Full article