Frequency Oscillations In Power Systems Research Articles

A Clustering-Based Approach for Estimation of Low Frequency Oscillations in Power Systems

This paper presents a clustering technique to rank the dominant modes of low frequency oscillations in power systems under model order uncertainty of the signal. The rotational invariance property of the signal subspace is utilized to obtain the modes of oscillations. Rotational invariance of the signal under multiple shifts is considered to obtain the preliminary estimates of the modes. Subsequently, the modes are clustered to obtain the dominant modes that belong to the signal subspace. A signal subspace participation index (SSPI) is used to rank the modes according to their dominance in signal subspace. Thereafter, the convex combination of the preliminary modes, estimated from the multiple shifts of the signal subspace, is used to obtain the final mode estimates. The simulation results are presented for signal generated using the modes obtained from a two-area system. Additionally, the methodology is also tested on field data obtained from the PMU installed at a generating station in India.

Unified Smith predictor based H wide-area damping controller to improve the control resiliency to communication failure

Inter-area low frequency oscillation in power system is one of the major problems for bulk power transmission through weak tie lines. Use of wide-area signal is more effective than the local area signal in damping out the inter-area oscillations. Wide area measurement system &#x0028 WAMS &#x0029 is convenient to transmit the wide area signal through the communication channel to the remote location. Communication failure is one of the disastrous phenomena in a communication channel. In this paper, a dual input single output &#x0028 DISO &#x0029 H&#x221E controller is designed to build the control resiliency by employing two highest observability ranking wide area signals with respect to the critical damping inter-area mode. The proposed controller can provide sufficient damping to the system and also the system remains stabilized if one of the wide-area signals is lost. The time delay is an unwanted phenomenon that degrades the performance of the controllers. The unified Smith predictor approach is used to design a H&#x221E controller to handle the time delay. Kundur&#x02BC s two-area and IEEE-39 bus test systems are considered to verify the effectiveness of the proposed controller. From the simulation results, it is verified that, the proposed controller provides excellent damping performance at normal communication and improves the controller resiliency to counteract the communication failure.

Sparse learning of network-reduced models for locating low frequency oscillations in power systems

With increasing penetration intermittent renewable energy and the interactions between different power sources in an interconnected system, low frequency oscillations may occur and potentially threaten the security of power systems if the grid cannot support adequate damping. Locating sources of low frequency oscillations is of great importance, which needs finding the mechanism of the damping of low frequency oscillations for interpretation. The difficulty of this problem lies in the fact that the parameters associated with the power system model can range from slightly uncertain to entirely unknown. Therefore, we firstly focus on identifying the network-reduced model to characterize low frequency oscillation, and then utilizing Hamilton analysis to reveal mechanism of oscillation. Accordingly, the problem of locating low frequency oscillation is equivalent to identify equivalent negative damping coefficient. In this paper, we propose a novel data-driven method that estimates equivalent damping coefficients and topological parameters of the network-reduced model simultaneously. More specifically, the proposed method utilizes the sparse representation to select the most dominant nonlinear terms from a set of dictionary functions, which finally balances the data fitness and achieves dynamics learning. We validate and evaluate the proposed method on IEEE 9-bus test system and IEEE 39-bus test system. The results demonstrate the effectiveness of the proposed method in achieving dynamics learning and locating sources of low frequency oscillations from measurement data.

Frequency Oscillation Analysis of Power System With Multiple Governor Deadbands

In recent years, the ultra-low frequency oscillation of power system is one of the most concerned frequency stability problem. The governor deadband are considered as one of the main influences. However, the existing methods can only deal with single deadband segment. As for a multi-machine system with multiple deadband segments, it lacks the analysis method for frequency oscillation. To solve this problem, this paper first define the extended description function applied to nonlinear composite system according to the principle of traditional description function method. The extended description function can quantify the relationship of input and output of a system with multiple nonlinear segments. Then, based on the uniform frequency model of multiple governors, the turbines and governors of hydro and thermal power units with different deadband widths are equivalent to one extended description function. The locus of minus reciprocal of the extended description function with oscillation amplitude and the Nyquist curve of the generator are plotted on the complex plane for the analysis of system stability. Next, the critical oscillation amplitude of disturbance to trigger the system frequency oscillation is calculated according to the point of intersection of both curves. Finally, the simulation results show that the critical oscillation amplitude can reflect the stability of system. The change of deadband width is positively correlated with the critical oscillation amplitude. The appropriate setting of deadband and configuration of hydro-thermal generation are effective measures to suppress the ultra-low frequency oscillation while retain the ability of frequency regulation.

An Adaptive Matrix Pencil Algorithm Based-Wavelet Soft-Threshold Denoising for Analysis of Low Frequency Oscillation in Power Systems

One of the main reasons that affecting the stability of power systems is low frequency oscillation (LFO). The existence of noise influences the accuracy of LFO mode identification extracted from wide-area measurement system (WAMS). The wavelet threshold de-noising is widely used in signal processing. In this paper, wavelet soft threshold is illustrated to attenuate the noise of LFO signal, the optimal wavelet basis and decomposition level for de-noising LFO signal with noise are obtained and verified by experiments. Following the signal de-noising, an improved Matrix Pencil (MP) algorithm is used for mode identification of LFO. This improvement particularly lies in the ratio of adjacent singular entropy increment difference (RASEID) designed as an adaptive order determination method in the MP algorithm proposed in the paper. RASEID not only makes the MP algorithm adaptive, but also enhances the stability of the order determination in the mode identification process. The proposed method ensures the accuracy of mode identification with lower sensitivity to noise interference. Finally, the validity of the proposed method is verified by three cases studies. The first study is on the analysis of synthetic signal typically performed in many literatures. The second study is to identify the mode of active power LFO signal which is generated by IEEE four-generator and two-area system given with disturbance on RT-LAB experimental platform. The third study is the oscillation analysis of the actual LFO data in the North American power grid. The results validate the feasibility of the proposed method for mode identification of noisy LFO.

Relay Protection Simulation and Testing of Online Setting Value Modification Based on RTDS

Analyzing the feasibility of modifying setting values on the condition of the running line without exiting the protection function is of great importance for 110 kV substations. A system-level test of settings modification is proposed to verify that the values are correctly modified during the process and the protection function is still in effect. A cyber-physical automatic test bed using a real-time digital simulator (RTDS) is developed for relay protection to modify settings online, which distinctly improves work efficiency. Based on actual power grid parameters, a full-process closed-loop RTDS automatic control system is applied for performance testing when setting groups are changed. The experiments are focused on blocking time tests, setting groups switch and coverage tests, DC power supply intermittent tests, unwanted operations in setting value, changing load and protection starting tests, short-circuit fault tests and power system frequency oscillation tests. The results of the trial indicate that the automatic test bed is an effective technology for checking and verifying the reliability of modifying setting values online. In addition, 36 line protection devices from 12 relay protection manufacturers are tested. The reliability of each test item is analyzed and the relay performance is evaluated using a comprehensive method. The test bed provides reliable technical support for the design, engineering, commissioning and substation operation of online setting modification.

Model order estimation methods for low frequency oscillations in power systems

Estimation of low frequency oscillation modes is important for taking remedial actions to ensure the small signal stability of the power system. This paper proposes three approaches to estimate the model order of low frequency oscillations using ringdown data from Phasor Measurement Units. The first approach uses a sequential cumulative sum test on the eigenvalues of the autocorrelation matrix of the signal data to estimate the model order. The second approach estimates the model order based on the eigenvalue contribution in the trace of the autocorrelation matrix. The third algorithm uses sum of squares of the eigenvalues to estimate the model order. All the methods are compared to ascertain their efficacy in estimating the model. The algorithms are tested on oscillation data obtained for WSCC 9 bus system simulated on RTDS and the field data from a generating station in India.

Wide Area Predictive Control of Power System Considering Communication Delay and Data Drops

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.

Impact of plug-in hybrid electric vehicles on power system with high wind power penetration

The rising energy independence and environmental concerns are key drivers in the growing popularity of plug-in hybrid electric vehicles (PHEVs). Because of the intermittent nature of the renewable energy sources, this may cause a high-frequency oscillation of the power system. From another aspect, all the PHEVs have in common the batteries, which provide the storage capability that can be effectively harnessed when the vehicles are integrated into the grid. Such a storage capability can effectively integrate wind power into the grid and all indicators signalize that the PHEVs are the most promising technology of the future transportation system. In this paper, different case studies are applied on one area power system to show the effect of the high wind energy penetration on the power system frequency and how the PHEVs can play an effective role in mitigating the power system frequency oscillation and supporting the more penetration of the wind energy into smarter electrical grids. In addition, an advanced controller has been designed to improve the frequency response and to compensate the delay of the system. The designed controller is a genetic algorithm (GA) based PID (proportional-integral-derivative) controller, it has been proposed for tuning optimized PID parameters. The results show that the controller has played an effective role in decreasing the response overshoot and settling time when used with the PHEVs. The used variable load, the thermal power plant parameters, and the wind turbine parameters are the same for the five case studies.

Feature Extraction of Low Frequency Oscillation in Power System Using Hilbert-Huang Transform

Power system oscillation is one of the phenomena that can cause problem in power system that can even lead to outage. Using data of phasor sifting in power system available through Phasor Measurement Unit (PMU) implementation, power system oscillations could be observed directly. However, to predict the condition of power system, the recorded phasor data need to be processed to obtain the quantitative measures. In this paper, important parameters are extracted by applying Hilbert Huang Transform (HHT) to phasor signal taken from PMU. The stable and oscillation condition are determined by the parameters that show the increasing power of each frequency over period of time. Validation is conducted by using simulation data that represents characteristic of PMU data.

Mitigation of low frequency oscillations in power systems based on Mamdani fuzzy inference

Several methods have been proposed and implemented to improve the power system stability. Based on the theory of proportional-integral-derivative (PID) excitation control and the composition principle of fuzzy PID controller, a novel PID controller based on Mamdani fuzzy inference (MFPID) is proposed in this paper. The proposed controller realizes the self-adjustment of the excitation controller parameter. Furthermore, the MFPID and power system stabilizer (PSS) subsection switch control strategy (MFPID-PSS) is presented based on the advantages of PSS and MFPID. In MFPID-PSS strategy, by switching the control strategy between MFPID and PSS at appropriate moment, the MFPID-PSS method acquires the overshoot as small as PSS, and at the same time acquires the adjusting time as short as MFPID. The simulation results demonstrate that the MFPID-PSS method improves the power system stability and has better mitigation effect for low frequency oscillations in power systems after disturbances.

Fundamental study of common mode small-signal frequency oscillations in power systems

This paper performs a fundamental study of very low frequency oscillations characterized by a common mode shape at all system busses (same magnitude and phase). Also known as global or frequency control oscillation mode (below 0.1 Hz), it determines frequency response performance according to NERC requirements. When poorly damped, it poses a serious threat to small signal stability in islanded interconnections (e.g., Quebec and Texas) or hydro-dominated low-inertia systems (e.g., Columbia and Ecuador). Building on the classical damping and synchronizing torque concept, an improved understanding of underlying mechanisms behind common oscillation mode apparition and its frequency and damping are achieved through analytical assessment of the impact of turbine-governor types, load voltage sensitivity as well as system inertia. By revisiting frequency stability definition in light of the damping-synchronizing torque concept, the paper in essence uncovers the important yet poorly understood notion of small-signal (oscillatory) frequency stability.

The Demand Response and UPFC Coordinated Frequency Control Strategy

In order to improve the stability of the power system, suppressing the low frequency oscillation of power system is already a problem that every country is eager to solve. Many power workers have done a lot of theoretical research and experimental verification on low-frequency oscillation and have got remarkable achievements. Energy from the Demand Side has been widely used in our daily life, and thousands of demand response loads have been used in frequency control whose controlling effects are quite obvious; meanwhile, because of the development of electrical technology, many smart grid devices can be fully used, and they have improved the stability of power system, which is consistent with the original intention of putting demand response loads into power system. UPFC can improve the system damping, and effectively suppress the low-frequency oscillation of the system as well as improve the stability of the power angle, so if UPFC and demand response are combined, the low frequency oscillation of the power system can be better suppressed.

Optimization of Governor Parameters to Prevent Frequency Oscillations in Power Systems

Negative damping of prime movers is a major cause of sustained frequency oscillations in power systems. Increasing the damping torque of prime movers by adjusting governor parameters is an effective measure to prevent frequency oscillations. The oscillation frequency is volatile and turbine parameters change under loading conditions. To guarantee robustness and adaptability, the governor parameters should be adjusted to ensure sufficient damping torque over the entire range of oscillation frequency and under different turbine parameters. An optimization model of governor parameters is proposed. A constraint of the model is that the damping torque of the prime mover over the entire oscillation frequency range, and under different turbine parameters, must be greater than the threshold. The composite dynamic performance of primary frequency regulation under different loading conditions is the optimization objective. Test results validate the proposed method. The stability of the frequency oscillation mode under different conditions can be guaranteed.

Design Fuzzy Logical Power System Stabilizer to Damp Low Frequency Oscillation of Power System

Design Fuzzy Logical Power System Stabilizer to Damp Low Frequency Oscillation of Power System

Model based PI power system stabilizer design for damping low frequency oscillations in power systems

This paper explores a two-level control strategy by blending local controller with centralized controller for the low frequency oscillations in a power system. The proposed control scheme provides stabilization of local modes using a local controller and minimizes the effect of inter-connection of sub-systems performance through a centralized control. For designing the local controllers in the form of proportional-integral power system stabilizer (PI-PSS), a simple and straight forward frequency domain direct synthesis method is considered that works on use of a suitable reference model which is based on the desired requirements. Several examples both on one machine infinite bus and multi-machine systems taken from the literature are illustrated to show the efficacy of the proposed PI-PSS. The effective damping of the systems is found to be increased remarkably which is reflected in the time-responses; even unstable operation has been stabilized with improved damping after applying the proposed controller. The proposed controllers give remarkable improvement in damping the oscillations in all the illustrations considered here and as for example, the value of damping factor has been increased from 0.0217 to 0.666 in Example 1. The simulation results obtained by the proposed control strategy are favourably compared with some controllers prevalent in the literature.

Hydraulic damping mechanism of low frequency oscillations in power systems: Quantitative analysis using a nonlinear model of hydropower plants

As power systems grow reliant on an increasing mix of intermittent renewables, hydropower units are being called upon to provide more aggressive power-frequency control. This dynamic is enlarging the significance of interaction between hydraulic and electrical subsystems in hydropower plants (HPPs). The influence from HPPs on power system stability is of great importance, especially for hydro-dominant power systems like the Nordic power system and the China Southern Power Grid. This paper aims to quantify and reveal the influencing mechanism of the hydraulic damping of low frequency oscillations in power systems. An equivalent hydraulic turbine damping coefficient is introduced, and a nonlinear HPP model that combines electrical subsystems with a refined hydraulic-mechanical subsystem is established and verified. A novel quantifying methodology is proposed through simulations by two different models based on case studies on a Swedish HPP. Then, the quantification results of the damping coefficient are presented and the influencing mechanism behind is revealed, by studying three representative factors from the hydraulic-mechanical system: the delay in turbine governor systems, governor parameter and penstock length. Observations and discussions of on-site measurements are included to support the analysis. The results show that the damping effect from hydraulic turbines can be considerable. Based on the limited cases in the HPP, the damping coefficient can vary from + 3.0 to −2.3, while previously the contribution has been unclear and normally assumed to be positive. The phase shift in the mechanical power response with respect to the rotational speed deviation is an important reason for the different damping performance. Furthermore, the effect and significance of implementing the damping coefficient on cases with power system stabilizer (PSS) are demonstrated.

Analysis of low frequency oscillations in power system using EMO ESPRIT

Identification of poorly damped low frequency oscillations present in the densely interconnected power system is of paramount importance to maintain its stable operation. Estimation of signal parameters via rotational invariance technique (ESPRIT) is a parametric method used for analysing such signals even under noisy conditions. However, this method requires precise information about the number of modes present in the signal. Hence, this work uses a combination of Exact Model Order (EMO) algorithm and ESPRIT for analysing these low frequency oscillations. The performance of the proposed method is tested using various synthetic signals with different levels of noise and PMU reporting rates. Further, the robustness of the proposed method towards noise resistance is compared with modified Prony, TLS-ESPRIT and ARMA methods. Finally, the proposed method is tested using real time probing test data obtained from Western Electricity Coordinating Council (WECC) network. Results reveal that the proposed method is accurate, precise and outperforms the other methods.

Training qubit neural network with hybrid genetic algorithm and gradient descent for indirect adaptive controller design

Heuristic stochastic optimization techniques such as genetic algorithm perform global search, but they suffer from the problem of slow convergence rate near global optimum. On the other hand deterministic techniques such as gradient descent exhibit a fast convergence rate around global optimum but may get stuck in a local optimum. Motivated by these problems, a hybrid learning algorithm combining genetic algorithm (GA) with gradient descent (GD), called HGAGD, is proposed in this paper. The new algorithm combines the global exploration ability of GA with the accurate local exploitation ability of GD to achieve a faster convergence and also a better accuracy of final solution. The HGAGD is then used to train a qubit neural network (QNN), which is a good candidate for enhancing the computational efficiency of conventional neural networks, for two different applications. Firstly, a benchmark function is chosen to illustrate the potential of the proposed approach in dealing with function approximation problem. Subsequently, the feasibility of the proposed method in designing an indirect adaptive controller for damping of low frequency oscillations in power systems is studied. The results of these studies show that the proposed controller trained by the HGAGD can achieve satisfactory control performance.

A Review on Impacts of Wind-Solar Hybrid Generation System on Low Frequency Oscillation of Power System

Energy crisis and environmental pollution caused by conventional energy power generation make renewable energy such as wind energy and solar energy as new alternative energy sources. The complementarity of wind-solar hybrid generation technology will be the focus of future research. This paper briefly introduce the current situation of the development of wind-solar hybrid generation system, the principle and analysis method of low frequency oscillation in power system are summarized. Including modeling and simulation, system oscillation modes and damping characteristics, and improve the system damping characteristics control strategy, etc. This paper provide a reference for further study of the influence on the characteristics of low frequency oscillation in power grid.