Damping Of Low Frequency Oscillations Research Articles

Improvement of low-frequency oscillation damping in power systems using a deep learning technique

Over the last few years, machine learning tools have significantly progressed and attracted extensive applications in many parts of contemporary life. The power sector is one of the leading domains implementing such appealing and effective technologies for diverse applications as a part of the digital transformation of electric networks. A power system's low-frequency oscillation (LFO) is a non-threatening but slow-burning problem that might cause complete network failure unless adequately handled. This article proposes a state-of-the-art procedure of LFO damping in electric power networks via the sine cosine algorithm and deep learning (DL) technique. It uses two networks of power systems, in which the synchronous generator is fitted with a power system stabilizer (PSS) in the case of the first network; in the other, the synchronous machine is conjoined to the PSS that coordinates with a unified power flow controller. The proposal is developed based on the statistical assessment of the analyzed networks to improve the LFO damping via real-time adjustment of PSS parameters/variables. The proposed technique was evaluated using power system stability performance measuring criteria, such as the eigenvalue and minimum damping ratio. In the end, the effectivity of the stability-gaining procedure is also tested by time-domain simulation to implement in real-time. The study also dealt with a comparative investigation and discussion of the findings of some published works to conclude the capability of the proposed DL tool for stability improvement of the system in real-time by removing undesirable LFOs.

AVR-PSS Generator with Fuzzy Logic Controller and Conventional Damping of Low-Frequency Oscillations

AVR-PSS Generator with Fuzzy Logic Controller and Conventional Damping of Low-Frequency Oscillations

Improving the stability and damping of low-frequency oscillations in grid-connected microgrids with synchronous generators

Improving the stability and damping of low-frequency oscillations in grid-connected microgrids with synchronous generators

Distributed Low-Frequency Oscillation Damping in Low-Voltage Islanded Multi-Bus Microgrids With Virtual Synchronous Generators

Distributed Low-Frequency Oscillation Damping in Low-Voltage Islanded Multi-Bus Microgrids With Virtual Synchronous Generators

Influence of water hammer effect on low frequency oscillation of grid-connected hydropower station system

This paper aims to investigate the influence of the water hammer effect on low-frequency oscillations (LFO) in power systems, mainly quantifying and revealing the characteristics of hydraulic damping of LFO. The models of the grid-connected hydropower stations considering the water column elasticity (elastic model) and without considering it (rigid model) are respectively established and used as time domain validation models. The corresponding analytical formulas for the mechanical damping torque coefficients (MDTC) are derived to obtain the system's damping frequency characteristics. Finally, a method for quantifying the nonlinear system's damping is proposed. The results show that due to the effect of the water hammer wave, the system's damping frequency characteristics have changed, and damping peaks and valleys appear. The corresponding frequencies are determined by the frequency of the water hammer wave. The system has a critical oscillation frequency. When the frequency of LFO is below the critical frequency, water column elasticity must be considered. When the frequency of LFO is consistent with the frequency of the water hammer wave, the negative damping reaches its maximum. Finally, the proposed quantitative method was used to clarify the influence of the water hammer effect on the system's damping characteristics while considering nonlinear head loss.

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.

Identification and damping of low-frequency oscillations based on WAMS data and the revisited residue method – part I

The results of low-frequency oscillations identification in the Republic of Kazakhstan power grid by using a Wide Area Measurement System are presented and an algorithm for damping low-frequency oscillations is proposed in this paper. Analysis of weakly damped inter-area low-frequency oscillations revealed a constant mode with a frequency range of 0.3‒0.4 Hz. It was determined that at these low-frequency oscillations, the amplitude of active power fluctuations along the transmission line was 150 MW with a duration of 9 minutes. The modal analysis calculation of the Republic of Kazakhstan power system model in the «DigSilent Power Factory» software shows the dangerous low-frequency oscillation modes having a damping ratio is 2.2 % and an eigenfrequency 0.328 Hz. These oscillation modes identified by the real data and in the developed model indicate the incorrect tuning of power system stabilizer parameters at power plants. It is necessary to retune the power system stabilizer parameters whenever changing the system’s and mode’s configurations. An analysis of existing power system stabilizer tuning methods was performed, and revisited residue method was determined as sufficiently effective. Thus, the developed algorithm for identification and damping of low-frequency oscillation consists of three tasks. The first task is data collection from the Wide Area Measurement System and Supervisory Control and Data Acquisition system and updating the calculation model based on the current status of equipment (generators, transformers, transmission lines, etc.). The second task is the identification of dangerous electromechanical oscillations and modal analysis based on information obtained in real-time. The third task is tuning the power system stabilizer parameters for damping dangerous low-frequency oscillation modes based on the revisited residue method

Damping of low-frequency oscillation using renewable generation units

Nowadays there is a significant increase the number of generation units based on renewable energy sources in electric power systems, the main goal of which is to ensure global access to affordable, reliable, sustainable and modern sources of energy. However, as the penetration level of renewable generation units increases, there are power oscillations easily occur, which create biggest challenges for the power system stability. In particular, the dominant modes of modern generation units, connected to the main grid via a voltage source converter, are in the range of higher frequencies than electromechanical oscillations. Consequently, the chance of occurrence of low-frequency oscillations increases, the parameters and the trajectory of which will differ from power oscillations in power system without renewables. The results of the analysis of low-frequency oscillation parameters in part of Eastern Siberia power system and evaluation of impact of renewable generation unit on power oscillations are presented in this article. The results were obtained by the Hybrid real time simulator based on the combination of analog, physical and digital modeling levels. The developed scheme of part of Eastern Siberia power system and simulation results were verified by SCADA system. The difference between the results of simulation and SCADA system did not exceed 1%. It indicates the adequacy of the Hybrid real time simulator and the developed scheme of power system. Based on the evaluation of the parameters of power oscillations and the calculation of the degree of damping of the transient process, it can be noted that the oscillatory stability of the power system is improved: damping time decreases, the damping ratio increases with increasing of renewables penetration level.

Revamped Sine Cosine Algorithm Centered Optimization of System Stabilizers and Oscillation Dampers for Wind Penetrated Power System

The mapping of damping ratios and damping factors by Sine-Cosine Algorithm (SCA) is significant in the analysis of low frequency oscillations generated in an integrated network having multiple conventional and renewable energy sources. Multiple random models with unknown search spaces and uncertain conditions and constraints, which incorporate the fluctuation of solutions towards or outwards at the initial stage for solving real-time problems can be analyzed by a revamped sine-cosine algorithm (RSCA) model. In this paper, the SCA has been revamped to explore the stability threshold for a stable system under dynamic nonlinear operating conditions. It is achieved with the infusion of suitable mathematical functions for optimizing the parameters of Power System Stabilizers (PSSs) and Doubly Fed Induction Generator (DFIG) system-based oscillation dampers to enhance the Small Signal Stability of power systems through effective damping of low-frequency oscillations (LFOs). These LFOs weaken the effective power generation and demand management cycle in conventional power systems when the system faces conditions like intermittent renewable energy sources, overloading conditions, impulsive faults etc. The small-signal and transient stability studies for various disturbances and different operating conditions are investigated, and the performance of the proposed RSCA for optimized parameter tuning of system stabilizers and oscillation dampers are analyzed on the modified benchmarking systems with wind generators using MATLAB Ⓡ simulations. The efficiency and robustness of the proposed algorithm has been verified under selective critical operating conditions, line outages, and load uncertainties to prove that the low frequency modes are damped with an elevated positive damping ratio and rapid settling time with reduced oscillations. The application of system stabilizers and oscillation dampers optimized through the proposed RSCA shows a reduced settling time in the LFOs created and improved damping ratio of 0.22 for an increase in 20% loading and 50% of wind power generation in the case study of Two Area Four Machine System.

Damping Torque Analysis of the PMSG-Based WT with Supplementary Damping Control for Mitigating Interarea Oscillations

This study presents a comprehensive analysis of the impact that a supplementary damping controller of the permanent magnet synchronous generator (PMSG)-based wind turbine (WT) has on low-frequency oscillation (LFO) damping. A reduced mathematical model of an interarea system is first established. Then, an auxiliary damping controller is designed using the PMSG active power control loop, enabling the WT to actively support the interarea LFO mitigation. Based on this, the damping torque analysis (DTA) method is applied to explore the contribution of the PMSG-based WT with an auxiliary damping controller to LFO damping enhancement, whose analytical expressions of the damping torque coefficients reveal the impacts of the control parameters and the operation conditions on the system damping characteristics. It is evident that the installation location of the wind power plant (WPP) plays a leading role in determining whether the damping provided by the PMSG controller is positive or negative. Also, the contribution of damping from the PMSG can be improved by tuning the droop coefficient of the PMSG controller properly. The results indicate that the proposed damping control is always helpful in improving the system damping when the wind power penetration increases. Accordingly, analytical conclusions can serve as guidelines for the control design. Case studies of a two-area test system integrated with a PMSG-based wind farm have been conducted to verify the theoretical analysis.

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.

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%.

Effective damping of local low frequency oscillations in power systems integrated with bulk PV generation

High penetration of renewable sources into conventional power systems results in reduction of system inertia and noticeable low-frequency oscillations (LFOs) in the rotor speed of synchronous generators. In this paper, we propose effective damping of LFOs by incorporating a supplementary damping controller with a photovoltaic (PV) generating station, where the parameters of this controller are coordinated optimally with those of a power system stabilizer (PSS). The proposed method is applied to damp local electromechanical modes by studying a system comprising a synchronous generator and a PV station connected to an infinite bus. The PV station is modeled following the instructions of the Western Electricity Coordinating Council. The problem is modeled as an optimization problem, where the damping ratio of the electromechanical modes is designed as the objective function. Constraints including upper and lower limits of decision parameters and damping ratio of other modes are considered by imposing penalties on the objective function. Different optimization algorithms are used to pursue the optimal design, such as political, improved gray wolves and equilibrium optimizers. The results validate the effectiveness of the proposed controller with PSS in damping local modes of oscillations.

A minimal architecture neuro adaptive predictive control scheme for power system stabilizer

The ever-increasing size and complexity of the present-day power systems puts a higher demand on the power system stabilizer for low-frequency oscillation damping. Alternate design methods of the conventional power system stabilizer or control structures to replace it, proposed over many decades, have not been widely adopted for practical use due to the impediments like non-linear and complex structure, and lack of fast adjustments. This paper proposes an improved neuro-adaptive control scheme, based on online system identification and simultaneous control, to replace conventional power system stabilizer. A simple, linear neural identifier, with a few adjustable connection weights, is used which ensures minimal computational burden and fast learning capability. The parameters of the controller, designed using optimal control with one-sample-ahead output prediction, are related to the identifier parameters. An adaptive learning rate, derived using Lyapunov stability theorems, guarantees stability of convergence of the learning algorithm as well as an optimal speed of convergence. Improved oscillation-damping performance over a wide range of operating conditions, in comparison with a well-designed conventional power system stabilizer and some other alternative controllers reported in literature, has been validated through simulation studies carried out on two different power systems. It is demonstrated that a simple linear neural identifier, which approximates a local linear model of a system, by adjustment of its parameters online, is faithfully able to track the varying dynamics of the system. Hence, it is not always appropriate to use complex structures and non-linear activation functions in neural network-based adaptive control applications which may pose difficulties in the implementation of these controllers. Also, the proposed control scheme is model-free, easier to implement and needs local measurements only.

A coordinated strategy for multi-machine power system stability

Owing to the fast growth of the energy demand, the current power system may reach the marginal operating design resulting in unfavourable frequency/voltages conditions, the timeframe of stability and unexpected faults. Therefore, it is necessary to use all capacity without any additional development costs and having a secure and safe system. Hereby, this study addresses a novel coordination strategy for improving low-frequency oscillations in multi-machine models under various operating conditions. To achieve this goal, the proposed solution is divided into three main parts, the first part presents eigenvalues and time-domain analyzes to extract the unstable modes for a nonlinear model of multi-machine to capture a real-world problem. The second part proposes two controllers based on fuzzy theory and thyristor controlled series compensator (TCSC) with power oscillation damper (POD) structure to reach considerable damping of low-frequency oscillations. Since an uncoordinated design between two controllers in the power system aggravated instability, therefore, the last part proposes a modified virus colony search (VCS) to optimally adjust the decision variables with two conflicting objectives based on time and frequency domains. To demonstrate the proposed coordinated strategy, the well-known two-area and four-machine test system have been selected and the obtained results are compared in several loading conditions such as ±20 load changing, with other available controllers through several analysing indices. According to numerical results, the proposed design can improve the statical indices such as integral of time multiplied absolute value of the error (ITAE) and figure of demerit (FD) about 12 and 11%, respectively. Also, the eigenvalues can be collected between the damping ratio 0.2 and real part -1.0.

A new model of connected renewable resource with power system and damping of low frequency oscillations by a new coordinated stabilizer based on modified multi-objective optimization algorithm

This study was an attempted to present an organized structure of double-fed induction generator wind power plant with power oscillation damper (POD) in operational way and adjustable error-driven stabilizer to increase low-band oscillation reacted to their impacts in the energy system in state of charging. A novel non-linear stabilizer is suggested in the current research to compensate for the drawback of traditional stabilizers in monitoring the oscillation conditions which are internal and consequently to achieve better results in a greater range of disorders. Actually, the applied stabilizer is elastic and error-driven. Adjusting parameters of the suggested method properly plays a vital role in its efficiency. Consequently, the parameters set serve as an optimization problem which is solved by an algorithm of virus colony search (VCS) with several objectives time-domain and complex-domain. The reason behind using this algorithm is to make sure that solutions are not entrapped in local optima under the condition that the grid undergoes optimizing a great number of variables. The developed probabilistic method in frequency-domain chooses just the most favorable positions under the condition of providing the whole generators with stabilizer due to decreasing the initial expense. Lastly, a novel improved virus colony search algorithm with several objectives is implemented to provide solution for optimum adjusting of suggested stabilizer and power oscillation damper variables which serve as an optimization problem with several objectives. Confirming the efficiency of the planned method was conducted via concurrent use of eigenvalue analysis and time domain non-linear modeling in terms of various functioning states. The low frequency oscillations (LFOs) could be damped in the optimal way and as a result the stability performance of the case study system would develop meaningfully.

Damping of Low-Frequency Oscillations via Active Disturbance Rejection Control

Linear active disturbance rejection control (LADRC) is applied as power system stabilizer (PSS) in power systems to damp the low-frequency oscillations. A tuning method for second-order LADRC is proposed specifically for damping the low-frequency oscillations. The tuning method is based on its own structure (zeros and poles) and the oscillation frequencies that need to be damped, thus it is independent of system models and not restricted to single-machine-infinite-bus (SMIB) systems. Moreover, a method to analyze the robustness is proposed for SMIB systems using the structured singular value method. Simulation studies on a SMIB system and two multi-machine power systems show that LADRC is easy to tune and can achieve good performance in damping both the local modes and the inter-area modes, thus it has great potential in power system stability control.

Coordinated control among PSS, WTG and BESS for improving Small-Signal Stability

Abstract The goal towards attaining a sustainable future has led to the rapid increase in the integration of converter control based generators (CCBGs). The low inertia response characteristics of CCBGs and the weak tie lines in interconnected systems pose a huge threat to Small-Signal Stability (SSS). Adequate damping of low-frequency oscillations (LFO) is pivotal in ensuring the maximum power transfer through the critical transmission corridors. These operational issues become more serious with the significant reduction in system inertia as a result of the high penetration of CCBGs. Therefore, appropriate control techniques are an absolute requirement for preventing LFOs from limiting the penetration of CCBGs in interconnected networks. This may also eventually lead to revisions in grid codes mandating CCBGs to provide auxiliary damping control. But, the progressive addition of multiple damping controllers for specific target modes can lead to the drifting of eigenvalues (EVs) associated with other electromechanical modes (EMs) in the system. This is due to the adverse interactions between multiple damping controllers in the uncoordinated control approach and may result in deteriorating SSS. Therefore, this paper proposes a simultaneous coordinated control among Battery Energy Storage System (BESS), Wind Turbine Generators (WTG) and Power System Stabilizer (PSS) for enhancing SSS in networks with high wind penetration by considering both inter-area (IA) and local modes. The performance of the proposed coordinated control is corroborated using IEEE 68 bus system for multiple operating scenarios for which the critical modes in the system have the lowest damping index (DI). The effectiveness of modulating the active power, reactive power and simultaneous modulation of both active and reactive power injected by BESS along with a dual-channel Optimized WTG Damping Controller (DOWDC) and PSS is evaluated. The impact of the different coordinated control strategies on voltage dynamics is also investigated. The simulation results validate the better performance of the proposed coordinated control over uncoordinated control approaches.

IMPACT OF GENERIC AND MULTIBAND POWER SYSTEM STABLIZER (PSS) ON ELECTRIC POWER SYSTEM STABILITY

Sustained power system oscillation has become a serious problem for power system operation and control nowadays. Oscillations cause safety problems in electric power equipment and limit the transmission capacity of long-distance power transmission. Oscillations can reach an amount that can compromise the stable operation of the synchronous generator and the power system in general. One way to suppress oscillations is to use a stabilizer of the power system as an integral part of the excitation systems of generators. The task of the power oscillation stabilizer is to produce a torque damping component of the electromagnetic torque through the excitation systems. This paper reveals the impacts of Generic and Multiband power system stabilizers (PSS) to enhance the damping of low frequency oscillations in a two machine power system. The impact of the Multiband PSS was seen to be better that of Generic PSS on the two machine power system in Matlab Simulink. KEY WORD : Power, Stability, Simulation, Oscillations, Faults. DOI: 10.7176/CEIS/12-2-04 Publication date: April 30 th 2021

Designing optimal power system stabilizer for synchronous generator with and without damper windings

This paper aims at effective damping of low-frequency oscillations (LFO) associated with synchronous generators (SG). LFO are excited by system disturbances as sudden change on the load, switching events, and malfunction of the turbine controller. Poor damping of LFO affects the stability of the generation system, in severe cases may result in instability and damage to prime-movers. The negative effect of the automatic voltage regulator (AVR) is studied for SG without and with damper windings on the damping of oscillations. Minimizing the LFO is achieved by incorporating the power system stabilizer (PSS), which adds an additional control signal to AVR. Effective design of PSS to maximize the damping torque while maintaining the stability of SG variables. The problem is modelled as an optimization problem, the damping ratio of the mechanical modes is the objective function. The single-pole placement technique and the recently developed political optimizer are picked to determine the perfect PI parameters for PSS. The satisfactory performance of the proposed PSS is appraised by testing it against mechanical power disturbances. The obtained mathematical analytical expression makes it possible to determine easily the eigenvalues and step response for the speed and electromagnetic torque for SG in MATLAB environment.