C-Vine Pair Copula Based Wind Power Correlation Modelling in Probabilistic Small Signal Stability Analysis

The increasing integration of wind power generation brings more uncertainty into the power system. Since the correlation may have a notable influence on the power system,the output powers of wind farms are generally considered as correlated random variables in uncertainty analysis. In this paper, the C-vine pair copula theory is introduced to describe the complicated dependence of multidimensional wind power injection, and samples obeying this dependence structure are generated. Monte Carlo simulation is performed to analyze the small signal stability of a test system. The probabilistic stability under different correlation models and different operating conditions scenarios is investigated. The results indicate that the probabilistic small signal stability analysis adopting pair copula model is more accurate and stable than other dependence models under different conditions.

Small signal stability analysis of a synchronized control-based microgrid under multiple operating conditions

In this paper,a synchronized control strategy of double fed induction generator that can provide reserve capability and primary frequency support for microgrid is firstly developed.The microgrid based small signal stability performance is investigated under multiple operating conditions.The effect of three categories of key controller parameters on dominant eigenvalues is studied by sensitivity analysis,including:1)active power drooping coefficient;2)reactive power drooping coefficient;3)parameters of outer loop excitation current control.Finally,some constructive suggestions on how to tune controller parameters to improve microgrid’s small signal stability performance are discussed.

Dynamics and Small Signal Stability Analysis of PMSG-based Wind Farm with an MMC-HVDC System

The permanent magnet synchronous generator (PMSG)-based wind farm with a modular multilevel converter (MMC) based HVDC system exhibits various oscillations and can experience dynamic instability due to the interactions between different controllers of the wind farm and MMC stations, which have not been properly examined in the existing literatures. This paper presents a dynamic modeling approach for small signal stability analysis of PMSG-based wind farms with a MMC- HVDC system. The small signal model of the study system is validated by the comprehensive electromagnetic transient (EMT) simulations in PSCAD/EMTDC. Then the eigenvalue approach and participation factors analysis are utilized to comprehensively evaluate the impact of different controllers, system’s parameters and the circulating current suppressing controller (CCSC) on the small signal stability of the entire system. From eigenvalue analysis, it is revealed that as the output active power of the wind farm increases within the rated range, the overall system will exhibit a sub-synchronous oscillation (SSO) instability mode, an extremely weak damping mode, and a low frequency oscillation instability mode. From participation factors analysis, it is observed that the SSO mode and weak damping mode are primarily related to the internal dynamics of the MMC, which can be suppressed or improved by CCSC. It is determined that the low frequency oscillation mode is primarily caused by the interactions between the phase locked loop (PLL) control of the wind farm and the voltage and frequency (V-F) control of the MMC station. The analysis also depicts that the larger proportional gain value of the V-F control of the MMC station and smaller PLL bandwidth of the wind farm can enhance the small signal stability of the entire system.

Small signal stability analysis of power systems with high penetration of wind power

The integration of large amount of wind power into a power system imposes a new challenge for the secure and economic operation of the system.It is necessary to investigate the impacts of wind power generation on the dynamic behavior of the power system concerned.This paper investigates the impacts of large amount of wind power on small signal stability and the corresponding control strategies to mitigate the negative effects.The concepts of different types of wind turbine generators(WTGs)and the principles of the grid-connected structures of wind power generation systems are first briefly introduced.Then,the state-of-the-art of the studies on the impacts of WTGs on small signal stability as well as potential problems to be studied are clarified.Finally,the control strategies on WTGs to enhance power system damping characteristics are presented.

Small signal stability region of power systems with DFIG in injection space

The modal analysis method is utilized to study the influence of doubly-fed induction generator(DFIG)on electromechanical oscillations.On this basis,the small signal stability region(SSSR)of power systems with DFIG in injection space is evaluated and the corresponding relationship between SSSR boundary and electromechanical oscillations is analyzed.The effects of the locations of DFIG on SSSR are considered.It is found that the boundary of SSSR consists of several smooth surfaces,which can be approximated with hyper-planes in engineering application.With the integration of DFIG,SSSR becomes smaller,thus indicating the deterioration of the small signal stability of the system.The 11-bus system with four generators is used to illustrate the proposed method.

Coordination of PSS and FACTS Damping Controllers to Improve Small Signal Stability of Large-scale Power Systems

This paper presents an approach for designing parameters of power system stabilizer(PSS)and FACTS damping controllers in a large scale practical power system.The objective is maximizing damping ratio of the target mode,and tracking technology(MTT)is used to avoid frequent alternations of target mode in optimization procedures.An improved planted growth simulation algorithm(IPGSA),which has high search efficiency and quick convergence speed,is proposed to optimize controller parameters coordinately.Based on case study of a large-scale power grid,and by using local and interregional low-frequency oscillation modes as target modes,simulation results verify proposed method in this paper.Furthermore,coordination optimization strategy adapted to multi-operating conditions demonstrates that the proposed approach is robust.

A Possible Configuration with Motor-generator Pair for Renewable Energy Integration

High penetration rates of renewable energy will bring stability problems for the future power grid.One of the critical issues is lack of inertia.In this paper,a synchronous motor-generator pair(MGP)system is proposed as a possible solution for renewable energy integration to enhance inertia and improve grid stability.First,feasibility studies of MGP on inertia,damping,efficiency,and cost are presented.Second,an analytical model is established based on its rotor angle relation.An active power control scheme based on voltage phase difference between renewable energy source and grid is then proposed,and state equations of MGP are derived for small signal stability.Next,two experiments are designed and implemented to verify stable operation and active power regulation of the MGP system.A single-machine infinite bus system is tested to investigate small signal stability and frequency response of MGP.The results show that the MGP system has a solid base in physics and is a feasible solution for providing enough inertia and improving small signal performance in the power grid with high penetration of renewable energy.The paper concludes with a discussion on future research directions to gain a better understanding of MGP.

Coordination of PSS and TCSC controller using modified particle swarm optimization algorithm to improve power system dynamic performance

This paper develops a modified optimization procedure for coordination of a power system stabilizer (PSS) and a thyristor controlled series compensator (TCSC) controller to enhance the power system small signal stability.The new approach employs eigenvalue-based and time-domain simulation based objective functions simultaneously to improve the optimization convergence rate.A modified particle swarm optimization (MPSO) algorithm is used as the optimization algorithm.The results of simulations and eigenvalue analysis for a single machine infinite bus (SMIB) system equipped with the proposed PSS and TCSC controllers confirm that the new approach is effective in enhancing the system stability.