Power System Low Frequency Oscillation Research Articles

Sources of Low-Frequency Oscillations in Power Systems, Their Localization and Damping

Sources of Low-Frequency Oscillations in Power Systems, Their Localization and Damping

STABILISATEUR DE SYSTÈME D'ALIMENTATION ROBUSTE BASÉ SUR UN CONTRÔLE H∞ STRUCTURÉ POUR LA STABILITÉ D'UN SYSTÈME MULTI-MACHINE

A robust design of power system stabilizers (PSSs) using H∞ output feedback control has been introduced in this work. To facilitate the implementation of the designed PSSs, the proposed technique employs the H∞ to tune the fixed-structure conventional lead-lag PSS parameters of the multi-machine system. These PSSs are used to improve the damping of the local and inter-area low-frequency oscillations in power systems under different operating conditions. The proposed control is tested on a multi-machine system, which is a three-machine nine-bus system. A comparative simulation study shows a significant enhancement and good performance of the proposed design compared to an IEEE conventional power system stabilizer.

The impact of supplementary active power control of wind turbine on power system low frequency oscillations

The impact of supplementary active power control of wind turbine on power system low frequency oscillations

Model order estimation for low-frequency oscillations in power systems by an advanced K-mean clustering approach

Model order estimation for low-frequency oscillations in power systems by an advanced K-mean clustering approach

Optimal fractional SSSC auxiliary controller for power system low frequency oscillations damping improvement

This work presents a new controller design to improve inter-area low frequency electromechanical oscillations (LFEOs) damping and enhance the overall stability of the electrical network. The control strategy used the static synchronous series compensator (SSSC) based flexible AC transmission systems (FACTS) series-type device mainly performed for power flow and voltage regulation. Then, a fractional order proportional integral derivative (FOPID) is introduced as an auxiliary controller for the SSSC using the difference of rotor speed deviations of generators as input signal to improve the oscillations damping. Moreover, genetic algorithm (GA) is applied to seek for optimum controller gains. The proposed control approach is examined on two-area four-machine (2A4M) test system. The FOPID performance is compared with the integer order proportional integral derivative (PID). Obtained results show that the proposed SSSC-based FOPID controller achieves high performance for enhancement of inter-area low frequency oscillations damping.

Low Frequency Oscillation Suppression Strategy in New Power System Based on Virtual Synchronous Generator

With the blend of massive new energy into power network systems, the inertia and damping features of new power systems are reduced, which is prone to cause low-frequency oscillations (LFO) in the power systems. Virtual synchronous generators (VSG) have received widespread attention by simulating the external characteristics of synchronous generators (SG) to enhance the inertia of new power systems and help suppress low-frequency oscillations. By analyzing the mathematical model of VSG, the control links of each part of VSG are established, the traditional reactive power-voltage (Q-V) of VSG is improved, and the formulas of active voltage control and reactive power control droop coefficient are deduced.Finally, a simulation model of VSG is created by MATLAB/Simulink platform, and new methods for suppressing LFO in power systems are compared and analyzed. The correctness of the formula and the improvement effect of reactive power and voltage control are verified.

Improving power system low-frequency oscillations damping based on multiple-model optimal control strategy using polynomial combination algorithm

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

Analysis of the Influence of Grid-Connected Photovoltaic Power Stations with Virtual Inertia on Low-Frequency Oscillation of Power System Based on Small Signal and Prony Analysis Methods

With the virtual synchronous generator (VSG) technology gradually becoming an emerging technology for new energy consumption, its introduction has solved the problems of weak support and weak anti-interference of traditional new energy stations. However, the practice shows that the grid-connected characteristics of VSG limit its large-scale utilization, and there is little research on the interaction between VSG and a multi-machine system. In this paper, small signal models and time domain simulation models of each link of a photovoltaic(PV) power station with the PV virtual synchronous generator (PV-VSG) are first conducted, and then the influence of the grid-connected PV power station with the PV-VSG on the low-frequency oscillation of power system and its interaction mechanism with the multi-machine system are qualitatively obtained based on the small signal analysis method and prony analysis method from two dimensions of frequency domain and time domain, respectively. The analysis and simulation show that the PV power station based on VSG technology affects the dynamic characteristics of the system by changing the electromagnetic torque of each synchronous generator. Unreasonable operating conditions and parameter settings will aggravate the phenomenon of low-frequency oscillation of the system. Before the grid connection of PV power station, the operating parameters shall be reasonably set to ensure their safe and stable grid connection.

Application of Underdetermined Blind Source Separation Algorithm on the Low-Frequency Oscillation in Power Systems

The timely discovery of low-frequency oscillations in power systems and accurate identification of their modal parameters is critical in numerous applications. Therefore, we investigated the feasibility of using multi-channel signals and established a relative theory. An algorithm based on the underdetermined blind source separation (UBSS) algorithm was proposed using this theory. First, the energy ratio function was used to determine the fault occurrence time. Then, the Bayesian information criterion was used to estimate the number of fault sources, and the boundary conditions were set to determine the number of fault sources. Next, the UBSS algorithm was used to analyze raw data, extract individual components that characterize faults, and subsequently measure low-frequency oscillation modal parameters through the Hilbert transform. Finally, the fast independent component analysis (FastICA) algorithm was used to separate noise signal from raw data. This separation considerably reduced noise disturbance and ensured the stability of the proposed method. Model simulation was conducted in MATLAB and experimental measurement revealed that the proposed method effectively reduced noise disturbance and could be applied to conditions with considerable disturbance.

Statistical Method of Low Frequency Oscillations Analysis in Power Systems Based on Phasor Measurements

This study aims to develop and test a new accelerated method for analyzing low-frequency oscillations in power systems using phasor measurements. The proposed method is based on the use of mathematical statistics methods that do not require significant computing power and have high reliability. Changes in the structure of power generation and integration of control devices based on power electronics cause low-frequency oscillations of power system operation parameters that present a threat. These changes result in a reduction in the total inertia of power systems with the subsequent impact on the operation of automatic voltage regulators and power system stabilizers, the purpose of which is to damp low-frequency oscillations. We conduct a careful review of the existing methods for low-frequency oscillations analysis in power systems to identify the gaps in the literature and design a new method to address the issues. The proposed method is tested on real-life data that was obtained during a disturbance with a transient event. Estimation of the low-frequency oscillation parameters was carried out, and the potential threat posed by these phenomena was examined. The implementation of the proposed algorithm for analyzing low-frequency oscillations is done using the Matlab programming language. Evaluation of the proposed algorithm is performed on physical data obtained during real transient processes occurring at large power plants.

Damping of Low-Frequency Oscillations in a Power System, Based on Multiple-Model Optimal Control Strategy

This paper proposes a new control strategy based on multimodel linear optimization control (MMLOC) to damp power system low-frequency oscillations (LFO) faster. The multimodel control strategy is used to anticipate synchronous generator dynamic behavior and linear optimization control for generating a control signal uncomplicatedly. The third-order model of synchronous machine is considered for each of the models. The probability of each model’s validity is evaluated from the difference between model outputs and the same actual power system outputs via the Bayesian approach. To improve the postfault dynamics of the case study power system, which contains a static VAR compensator, a linear optimal controller (LOC) is designed. The 8th order model of the machines is used in simulations to represent the plant as accurately as possible.

Modal Identification of Low-Frequency Oscillations in Power Systems Based on Improved Variational Modal Decomposition and Sparse Time-Domain Method

Power systems have an increasing demand for operational condition monitoring and safety control aspects. Low-frequency oscillation mode identification is one of the keys to maintain the safe and stable operation of power systems. To address the problems of low accuracy and poor anti-interference of the current low-frequency oscillation mode identification method for power systems, a low-frequency oscillation mode feature identification method combining the adaptive variational modal decomposition and sparse time-domain method is proposed. Firstly, the grey wolf optimization algorithm (GWO) is used to find the optimal number of eigenmodes and penalty factor parameters of the variational modal decomposition (VMD). And the improved method (GWVMD) is used to decompose the measured signal with low-frequency oscillations and then reconstruct the signal to achieve a noise reduction. Next, the processed signal is used as a new input for the identification of the oscillation modes and their parameters using the sparse time-domain method (STD). Finally, the effectiveness of the method is verified by the actual low-frequency oscillation signal identification in the Hengshan power plant and numerical signal simulation experiments. The results show that the proposed method outperforms the conventional methods such as Prony, ITD, and HHT in terms of modal discrimination. Meanwhile, the overall reduction in the frequency error is 34, 44, and 21%, and the overall reduction in the damping error is 37, 41, and 18%, compared with the recently proposed methods such as the EFEMD-HT, RDT-ERA, and TLS-ESPRIT. The effectiveness of the methods in suppressing the modal confusion and noise immunity is demonstrated.

Power System Stability Improvement of FACTS Controller and PSS Design: A Time-Delay Approach

The existence of low-frequency oscillations in power systems is the cause of power angle instability, limiting the transmission of maximum tie-line power. One of the effective ways to improve the stability limits is by installing a power system stabilizer and supplementary excitation control to augment with an automatic voltage regulator (AVR) supplemental feedback stabilizing signal. This paper proposes a new strategy for simultaneously tuning the power system stabilizer (PSS) and FACTS controller, considering time delays. The design of the proposed controller is modeled as an optimization problem, and the parameters of the controller are optimized through the grasshopper optimization algorithm (GOA). The suggested controller’s efficacy is evaluated for both single-machine infinite bus systems and multi-machine power systems under various disturbances. It also investigated the performance of the proposed controller with variations in signal transmission delays. The results obtained from GOA optimized proposed controller are compared with those obtained from the differential evolution algorithm, genetic algorithm, and whale optimization algorithm. In this context, the proposed GOA optimized controller reduced the objective function value by 16.32%, 14.56%, and 13.72%, respectively, in the SMIB system and 1.41%, 9.98%, and 13.31%, respectively, for the multi-machine system compared with the recently published WOA, and the well-established GA and DE. Further, the proposed controller is found to be stable and effectively increases stability even under small disturbances.

A New Adaptive Switching Control Method for the Complex Operating Condition of the Grid-Connected Power System

Due to the increase in wind power accessing power system in recent years, the low-frequency oscillation of power system is more complicated. Therefore, a new adaptive switching control method combined with a nonlinear system is proposed for the complex operating conditions of the grid-connected power system. Firstly, this method decomposes the low-frequency oscillation control problem of the power system into two parts, which are the linear system control and the nonlinear system control. Then, in the linear system control part, the iterative identification method is used to control this part. In the nonlinear system control part, the nonlinear term is decomposed into a combination of the previous beating measurable and the nonlinear estimation increment. Secondly, the nonlinear system is divided into three different operating conditions by the nonlinear estimation increment. Thus, four different adaptive controllers are obtained. Then, the designed controller is switched according to the controlled object with four controllers by the switching function, which not only ensures the stability of the closed-loop system, but also improves the control performance of the controller under different operating conditions. Finally, the feasibility and effectiveness of this method are verified, and the controller can fit the control efficiency of the real power system well.

Design of Coordinated PSS and SVC Damping Stabilizer for Low Frequency Oscillations Enhancement

This paper presents the application of PSS with based damping controller FACTS device and describes a coordinated tuning of parameters. The FACTS device considered here is Static Var Compensator (SVC). The method proposed to optimize the controller parameters is Particle Swarm Optimization (PSO) algorithm. The Single Machine Infinite Bus (SMIB) with PSS and SVC-based damping controller is selected as a case study system. In order to evaluate the effectiveness of these controllers, eigenvalues analysis and nonlinear simulation of this system are carried out under different loading conditions. The simulation results shows that PSS coordinated with SVC based stabilizer have outstanding fast damping of low frequency power system oscillations.

Linear quadratic regulator design via metaheuristics applied to the damping of low-frequency oscillations in power systems

This paper proposes the application of control by state feedback using the linear quadratic regulator (LQR) optimized by metaheuristics to damp low-frequency electromechanical oscillations in electrical power systems. The current sensitivity model was used to represent the single machine infinite bus (SMIB) system in the time domain. The weighting matrices of the LQR were adjusted using four different algorithms: (i) the genetic algorithm, (ii) the differential evolution algorithm, (iii) the particle swarm optimization algorithm, and (iv) the gray wolf optimization (GWO) algorithm. In the cases considered, disturbances were applied to the electrical power system and, then, performances comparisons associated with each metaheuristic were statistically analyzed, in which the number of iterations, error, and time to achieve convergence of each algorithm were compared. From the results, it was possible to conclude that the algorithms were efficient in adjusting the weighting matrices of the LQR, providing additional damping to the poles of interest of the system. It was also possible to conclude that the GWO algorithm presented the best performance, accrediting it as a powerful tool in the study of small-signal stability for the analyzed case.

Analysis of low-frequency oscillation in power system with renewable energy sources

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

Memetic SSA tuned fractional PSS for low frequency power system oscillations

Memetic salp swarm algorithm (MSSA) is proposed in the present work to optimally set the gains of fractional power system stabilizer (FPSS) for damping angular speed variation in power system. The optimization is based on the objective of minimizing variation in rotor angular frequency subject to disturbance which is change in reference voltage applied to generator. A single generator system connected with infinite bus has been experimented in this work for sudden and random variations in reference voltage applied to generator. The power system stabilizer (PSS) is based on fractional lead-lag control actions and MSSA is employed to tune the controller gains. Eigen values are analyzed with proposed control and MSSA has been compared with PSO (Particle swarm optimization) and salp swarm algorithm (SSA). It is observed from system response that MSSA can effectively tune the PSS parameters for oscillation damping subject to critical disturbances like random reference voltage variations.

Mitigation of Low-Frequency Oscillation in Power Systems through Optimal Design of Power System Stabilizer Employing ALO

Low-frequency oscillations are an inevitable phenomenon of a power system. This paper proposes an Ant lion optimization approach to optimize the dual-input power system stabilizer (PSS2B) parameters to enhance the transfer capability of the 400 kV line in the North-West region of the Ethiopian electric network by the damping of low-frequency oscillation. Double-input Power system stabilizers (PSSs) are currently used in power systems to damp out low-frequency oscillations. The gained minimum damping ratio and eigenvalue results of the proposed Ant lion algorithm (ALO) approach are compared with the existing conventional system to get better efficiency at various loading conditions. Additionally, the proposed Ant lion optimization approach requires minimal time to estimate the key parameters of the power oscillation damper (POD). Consequently, the average time taken to optimally size the parameters of the PSS controller was 14.6 s, which is pretty small and indicates real-time implementation of an ALO developed model. The nonlinear equations that represent the system have been linearized and then placed in state-space form in order to study and analyze the dynamic performance of the system by damping out low-frequency oscillation problems. Finally, conventional fixed-gain PSS improves the maximum overshoot by 5.2% and settling time by 51.4%, but the proposed optimally sized PSS employed with the ALO method had improved the maximum overshoot by 16.86% and settling time by 78.7%.

Mayfly Optimization Algorithm Applied to the Design of PSS and SSSC-POD Controllers for Damping Low-Frequency Oscillations in Power Systems

In this paper, it is proposed to apply the mayfly optimization algorithm (MOA) to perform the coordinated and simultaneous tuning of the parameters of supplementary damping controllers, i.e., power system stabilizer (PSS) and power oscillation damping (POD), that actuate together with the automatic voltage regulators of the synchronous generators and the static synchronous series compensator (SSSC), respectively, for damping low-frequency oscillations in power systems. The performance of the MOA is compared with the performances of the genetic algorithm (GA) and particle swarm optimization (PSO) algorithm for solving this problem. The dynamics of the power system is represented using the current sensitivity model, and, because of that, a current injections model is proposed for the SSSC, which uses proportional-integral (PI) controllers and the residues of the current injections at the buses, obtained from the Newton–Raphson method. Tests were carried out using the New England system and the two-area symmetrical system. Both static and dynamic analyses of the operation of the SSSC were performed. To validate the proposed optimization techniques, two sets of tests were conducted: first, with the purpose of verifying the performance of the most effective algorithm for tuning the parameters of PSSs, PI, and POD controllers, and second, with the purpose of performing studies focused on small-signal stability. The results have validated the current injections model for the SSSC, as well as have indicated the superior performance of the MOA for solving the problem, accrediting it as a powerful tool for small-signal stability studies in power systems.