Power System Small Signal Stability Research Articles

Coordination of PSSs and SVC Damping Controller to Improve Probabilistic Small-Signal Stability of Power System With Wind Farm Integration

A modified fruit fly optimization algorithm (MFOA) combined with a probabilistic approach are proposed in this paper to coordinate and optimize the parameters of power system stabilizers (PSSs) and static VAR compensator (SVC) damping controller for improving the probabilistic small-signal stability of power systems with large-scale wind generation, taking into consideration the stochastic uncertainty of system operating conditions. It is generally accepted that there is a threat to the stability of power system with penetration of wind farm. In addition, the stochastic fluctuations of wind generation make PSSs tuning more difficult. In this paper, PSSs and SVC damping controller are employed for suppressing local and inter-area low frequency oscillation. In order to eliminate the adverse effect between PSSs and SVC damping controller, the MFOA based on the probabilistic eigenvalue is applied to coordinate and optimize their parameters. The effectiveness of the proposed approach is verified on two test systems.

Wind power converters improving the power system stability

This study analyses the coordinated actions of modern wind power plants for improving the transient and small-signal stability in power systems. Supplementary controls on wind farms are considered, and specific modifications on the controllers are tailored to increase the grid-support services. The proposal is analysed and validated in a practical power system based on the Argentine electrical network. The wind farm supplementary controls use active and reactive power control loops as well as local and remote measurements. Local controls can rapidly respond decelerating the system frequency in the first instants of a fault, consequently reducing the transient angle separations and improving the first-swing stability. On the other hand, remote controls using global information are able to increase the damping of low-frequency inter-area oscillations. Structures combining centralised and decentralised control approaches will become more common in the near future. With this aim, the integration of fast local controls with remote controls is thoroughly studied using non-linear time-domain simulations and eigenvalue analyses. A robustness evaluation is also performed to validate the proposal over a wide range of operating conditions.

Improvement of small-signal stability of power system by controlling doubly fed induction generators of a large-capacity wind farm

AbstractMany wind turbine generations have been installed into power systems around the world, where in recent years doubly fed induction generator (DFIG) attracts a lot of attentions because of its efficiency and controllability. However, the DFIG is connected to the power system through inverters and originally does not have an ability to release the kinetic energy of the rotor or resorb the surplus power of the power system as the kinetic energy. Therefore, it has not been made clear how the DFIGs have an influence on small-signal stability in power systems. In this paper, we propose a control scheme of the DFIG and analyse its effect on the small-signal stability of the power system by eigenvalue calculations and time-domain simulations.

Investigation on Probabilistic Small-Signal Stability of Power Systems as Affected by Offshore Wind Generation

This paper investigates the impact of the complementarity, connection technology and network control strategy of offshore wind generation on the probabilistic small-signal stability of power systems. The cumulant-based theory is firstly applied to assess the variances of both the complementarity of combined wind power and the probabilistic small-signal stability of power systems. These variances are later employed as two indices to explain how the different complementarity levels, connection topologies and DC network control schemes of offshore wind generation affects the probabilistic distribution of critical eigenvalue and thus the probabilistic small-signal stability. In the paper, an example of 16-machine 5-area power system with three grid-connected offshore wind farms is presented. The index of probabilistic small-signal stability is computed and then compared under two complementarity conditions, two typical HVDC transmission systems through which the offshore wind farms are connected, and two DC grid control schemes, respectively. It is demonstrated that complementarity can effectively enhance probabilistic stability and multi-terminal HVDC may have either beneficial or detrimental impact on small-signal stability depending on the control pattern and setting when compared with point-to-point topology.

Stochastic Small-Signal Stability of Power Systems With Wind Power Generation

Wind power has had a significant impact on power system stability due to its stochastic nature. In this paper, the impact of stochastic excitation on power-system small-signal stability is investigated based on stochastic differential equation (SDE) theory. The mechanical power input of an asynchronous wind turbine is considered as a stochastic excitation to the system and the system state equation is formulated based on SDE. The mean stability and mean square stability of such a system are demonstrated, and the steady-state expectation and covariance of the system state variables are obtained by mathematical deduction. The numerical simulations are presented on a two-machine infinite bus system and the IEEE 145-bus test system.

Impact of grid connection of large-scale wind farms on power system small-signal angular stability

The grid connection of a large-scale wind farm could change the load flow/configuration of a power system and introduce dynamic interactions with the synchronous generators (SGs), thus affecting system small-signal angular stability. This paper proposes an approach for the separate examination of the impact of those affecting factors, i.e., the change of load flow/configuration and dynamic interactions brought about by the grid connection of the wind farm, on power system small-signal angular stability. Both cases of grid connection of the wind farm, either displacing synchronous generators or being directly added into the power system, are considered. By using the proposed approach, how much the effect of the change of load flow/configuration brought about by the wind farm can be examined, while the degree of impact of the dynamic interaction of the wind farm with the SGs can be investigated separately. Thus, a clearer picture and better understanding of the power system small-signal angular stability as affected by grid connection of the large-scale wind farm can be achieved. An example of the power system with grid connection of a wind farm is presented to demonstrate the proposed approach.

Оценивание запасов статической устойчивости электроэнергетической системы

We propose an algebraic matrix method of reserves estimation of multimachine electric power system small signal stability (asymptotic stability) that allows for multiple calculations of stationary regimes. The method is based determinant obtained by the authors of the degeneracy conditions locally modified Jacobi matrix mathematical model of the power system. Under local changes of the matrix refers to arbitrary changes of its elements in a single row or a single column. Such changes and their location simplifies algebraic conditions singular matrix. These conditions make it possible to significantly reduce the amount of calculations produced, which in turn allows for large orders of the analyzed systems of equations a high degree of efficiency of electric power of multiple mass calculations. The paper summarizes the equivalent conditions of degeneration locally modified Jacobi matrix obtained by the technique of zero divisors.

Global oscillation mode analysis using phasor measurement units-based real data

Abstract This study employs the Hilbert–Huang transform (HHT), the wavelet transform (WLT) and the fast Fourier transform (FFT) to analyze the inter-area (global) oscillation characteristics of Western Japan 60 Hz power system. The data are collected from a network of distributed phasor measurement units (PMUs) through a national project called Campus wide area monitoring system (Campus WAMS). In the present paper the Campus WAMS is introduced, and then the recorded phase difference data are analyzed using WLT, FFT and HHT methods, respectively. A comprehensive comparison is performed, and it is demonstrated that HHT offers more flexibility in terms of detailed profile and enough description, which can be beneficial for power system small signal stability analysts following estimation of system low-frequency oscillation. The results could be useful for on-line tuning of power system stabilizers.

Impact of Large-Scale Wind Power Integration on Small Signal Stability Based on Stability Region Boundary

Up until now, study results on the impact of large-scale wind power integration on small signal stability have often been in conflict. Sometimes, the conclusions are even completely opposite, making people unable to agree on which is right. The reason behind this phenomenon is that most of these studies are based on a certain grid and typical working conditions, so conclusions are reached by comparing changes in oscillation mode, one by one. This study method lacks a broader perspective, and often reflects only a part of the grid conditions. However, the small signal stability region boundary describes the critical operating range of power system small signal stability as a whole, making possible an overall evaluation of the system from a more macro perspective. Thus it is more suitable for analysis of the impact of large-scale wind power integration on small signal stability. Based on the above, using the model of wind farm integration to the single-machine infinite bus power system, this paper studies the impact of wind power integration scale and the coupling strength with synchronous generator on small signal stability through the comparison of the stability region boundaries, thus providing a new method and support for analyzing the impact of wind power integration on small signal stability.

Effect of Prime Mover Governor Parameters on Low Frequency Oscillation

The mechanism of power system low frequency oscillation was discussed in this paper. The coupling model between turbine governor system of plant and power system was established in MATLAB. The possibility of power system low frequency oscillation induced by unit-grid coupling was researched in detail. The simulation results indicate that power system low frequency oscillation will occur under disturbance, if a high derivative gain is used in PID controllers of hydraulic turbine governing system and partial derivative of turbine power output with respect to head varies with load. As for steam turbine, the PID parameters of governor system have important effect on small-signal stability of power system when the damp of power system is not very strong. The power oscillations caused by disturbance is decreased with the use of PID controller in governing system, whereas power oscillation is increased with the use of PI controller.

Probabilistic tuning of Power System Stabilizers considering the wind farm generation uncertainty

The increasing use of wind farms and the uncertainties in their generation levels have led to new challenges in system dynamic behaviors and Small Signal Stability (SSS). This paper proposes a probabilistic method to investigate the impact of the wind farm generation uncertainty on power system SSS, based on the Monte Carlo simulation. The proposed method is stochastic in contrast to conventional deterministic methods, which only analyze the system dynamic behaviors in one operating point. It determines several operating points, based on wind farm generation levels and calculates the Probability Density Function (PDF) of critical eigenvalues. Then, Genetic Algorithm (GA) is used to optimize the Power System Stabilizers (PSS) parameters. A case study is carried out on the IEEE 16-machine system to demonstrate the effectiveness and validity of the proposed algorithms. The results of probabilistic stability analysis are compared with those of deterministic analysis. It is shown that variation of the wind farm generation levels can cause the instability, even though the system is stable according to the deterministic analysis. Also, the time domain simulation results show how such tunings can effectively improve the SSS performance under the wind farm generation uncertainties.

Improvement on probabilistic small-signal stability of power system with large-scale wind farm integration

This paper studies probabilistic small-signal stability of power systems with wind farm integration, considering the stochastic uncertainty of system operating conditions. The distribution function of the real-part of system eigenvalue is computed by the method of probabilistic eigenvalue analysis. For improving probabilistic small-signal stability, PSS is adopted. A method for optimizing PSS based on participation factor and center frequency method is proposed. In order to evaluate the above proposed methods, the procedure is applied to a test system. The simulation results show that the stochastic variation of wind generation can induce a higher probability of system instability when compared with one that has no wind generation. With eigenvalues distributing in a wider range, it becomes difficult for PSS tuning. By applying the proposed optimized PSSs approach, probabilistic stability of system can be significantly improved.

Application of an improved BHESS-BR method to the small signal stability analysis of power systems

The BHESS-BR method, which consists of BHESS reduction and BR iteration, has been used in the complete eigenvalue analysis for power system small signal stability. Despite more efficient than the QR method, the BHESS-BR method has its numerical stability degrading significantly as the matrix order grows. In order to solve this issue, this paper presents an improved BHESS-BR method to analyze the power system small signal stability. For improving accuracy, orthogonal similarity transformations are taken to perform column eliminations in both BHESS reduction and BR iteration. Furthermore, a new multiplier tolerance criterion is derived to improve both accuracy and convergence by means of restricting the 2-norm condition number of similarity transformation matrix. To accelerate the computing speed, row eliminations in the BR iteration are refined so that the occurrences of row spikes are prevented. Test results of three standard systems and three practical systems with up to 4720 state variables demonstrate that the improved BHESS-BR method is more accurate and robust than the original BHESS-BR method for the complete eigenvalue analysis of small signal stability in power systems. Because the improvements belong to the scope of algebraic eigenvalue problem, the proposed method can well benefit the small signal stability analysis and offers a new choice for other eigenvalue problems in power systems. Copyright © 2014 John Wiley & Sons, Ltd.

Effects of Wind Generation Uncertainty and Volatility on Power System Small Signal Stability

This paper discusses the impacts of large scale grid-connected wind farm equipped with permanent magnet synchronous generator (PMSG) on power system small signal stability (SSS) incorporating wind generation uncertainty and volatility. Firstly, a practical simplified PMSG model with rotor-flux-oriented control strategy applied is derived. In modeling PMSG generator side converter, the generator-voltage-oriented control strategy is utilized to implement the decoupled control of active and reactive power output. In modeling PMSG grid side converter, the grid-voltage-oriented control strategy is applied to realize the control of DC link voltage and the reactive power regulation. Based on the Weibull distribution of wind speed, the Monte Carlo simulation technique based is carried out on the IEEE 16-generator-68-bus test system as benchmark to study the impacts of wind generation uncertainty and volatility on small signal stability. Finally, some preliminary conclusions and comments are given.

Application of PTP synchronized PMUs in power system small-signal stability analysis

Application of PTP synchronized PMUs in power system small-signal stability analysis

Effect of Wind Farm on Transient and Small-Signal Stability Based on BPA

Large scale wind farm output variation always deteriorates the system stability. To study this problem, this paper builds the model of power system with the integration of large-scale wind farm based on BPA. The simulation results show that large oscillations of voltage and rotor angle of system will happen, when three-phase short circuit fault occurs on the main line for transmitting wind power. With wind farm output decreasing, the transient stability and small-signal stability of power system will be improved.

New Eigenvalue Method for Power System Stability Analysis

The most widely adopted methodology for the analysis of power system small signal stability relies on the approach in the frequency domain, i.e. to linearize the system equation to obtain a linear model as well as the system matrix of which the eigenvalues can be calculated to determine the system stability. However, we often have high order of system matrix and thus it will be undesirable to calculate and analyze all the system eigenvalues. This paper is to explore the problem of small signal stability for power system and the main purpose is to find out the worst-damped mode of system eigenvalues and thus to alleviate the effort for computing and analyzing all the system eigenvalues. The developed algorithm is to be tested on a sample power system to validate the feasibility of the proposed new eigenvalue calculation method.

Fast Analysis of Power System Stability by Artificial Neural Network

Power system small signal stability concerns the ability of the power system to maintain stability subject to small disturbances. The analysis of small signal stability often has to deal with high-order system matrix due to the large number of generating units so that it is not easy to calculate and analyze the original system matrix and the whole set of eigenvalues. In this paper a new approach is proposed to take advantage of the specific feature of the parallel structure of artificial neural network for calculating the most critical eigenvalue or all eigenvalues of the unstable oscillation mode. The developed algorithm is tested on a sample power system to validate the feasibility of the proposed method for the calculation of the critical eigenvalue.

An Integrated Topology of Hybrid Marine Farm & Wind Farm

Abstract- Renewable energy has been playing an important role to meet power demand and ‘Green Energy’ market is getting bigger platform all over the world in the last few years. In order to meet the increasing demand of electricity and power, integration of renewable energy is getting highest priorities around the world. Wind is one of the most top growing renewable energy resources and it is the most environmental friendly, cost effective and safe among all renewable energy resources available. Another promising form of renewable energy is ocean energy which covers 70 % of the earth. Offshore Wind farm` (OWF) has already become very popular for large scale wind power integration with the onshore grid. Recently, marine current farm (MCF) is also showing good potential to become mainstream energy sources and already successfully commissioned in United Kingdom. An integration of wind and tidal energy represents a new-trend for large electric energy production using offshore wind generators and marine current generators, respectively. This work first focuses on the modeling of fixed speed IG based marine current farm and variable speed DFIG based wind farm. Detailed modeling and control scheme for the proposed system are demonstrated considering some realistic scenarios. The power system small signal stability analysis is also carried out by eigenvalue analysis for marine current generator topology, wind turbine generator topology and integrated topology. The relation between the modes and state variables are discussed in light of modal and sensitivity analyses. The results of theoretical analyses are verified by MATLAB/SIMULINK.

Simplified equivalent models of large-scale wind power and their application on small-signal stability

With the rapid growth of grid-connected wind power penetration level, it is necessary to study the impacts of wind power on power system stability. The small-signal stability of power systems with large-scale wind power is explored using the eigenvalue analysis method. A prototype sample system, the two-synchronous-generator system with a wind farm, is proposed for theoretical analysis. Then, simplified models of wind turbines (WTs) and the corresponding equivalent models of wind farms are analyzed. Three kinds of typical WT models, i.e., squirrel cage induction generator, doubly-fed induction generator, and permanent magnet synchronous generator are used. Furthermore, based on the simplified equivalent models, effects of large-scale wind farms on the electromechanical oscillation modes (EOMs) of synchronous systems are discussed. Simulation results indicate that wind farms of the three kinds of WTs have positive effects on EOMs. However, long transmission lines connecting wind farm to the system may produce negative effects on the small-signal stability of the system.