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Coordinated Damping Control Design for DFIG-Based Wind Generation Considering Power Output Variation Huazhang Huang and C.Y.Chung,Senior Member,IEEE

Abstract—To alleviate the impacts of stochastic wind generation on stability performance,this paper proposes a novel control de-sign method for coordination and synthesis of damping controllers for conventional synchronous generators(SG)and double fed induction generators(DFIG)-based wind generation in multi-ma-chine power systems.A probabilistic model of wind generation under Weibull distribution of wind speed isfirst introduced.Based on this model,an extended probabilistic small signal stability anal-ysis(SSSA)incorporating wind power generation is proposed for handling probability density function(PDF)of its power output. The optimization problem for tuning of damping controllers is then formulated,considering the cumulative distribution function (CDF)of the real part and damping ratio of eigenvalues obtained by the proposed probabilistic SSSA as stability constraints.Par-ticle swarm optimization(PSO)is used to solve the optimization problem and to determine parameters of damping controllers. The effectiveness of the proposed method is demonstrated on the modified New England power system with multi-wind farms through probabilistic SSSA and transient stability analysis,and it is compared with conventional deterministic methods.Accuracy of the proposed probabilistic SSSA is also validated by Monte Carlo simulations(MCS).

Index Terms—Double fed induction generator,particle swarm optimization,power system stabilizer,probabilistic small signal stability analysis.

I.I NTRODUCTION

W ORLDWIDE capacity of wind power is increasing rapidly and large scale wind farms(WF)are increas-ingly being connected with power networks.Fixed speed induction generators(FSIG)have been used in WFs set up earlier,but this kind of wind generator(WG)lacks control-lability to support the power network and also absorbs large amounts of reactive power from power systems during op-erations[1].Lately,double fed induction generators(DFIG) are being used,which are able to provide some support to networks,like voltage profile and damping control[2].In-stalling power system stabilizer(PSS)at DFIG-based wind

Manuscript received July05,2011;revised October19,2011and January 15,2012;accepted March01,2012.Date of publication April03,2012;date of current version October17,2012.This work was supported by Research Grants Council of Hong Kong(PolyU5154/08E)and the Department of Electrical En-gineering of The Hong Kong Polytechnic University.Paper no.TPWRS-00626-2011.

The authors are with the Computational Intelligence Applications Research Laboratory(CIARLab),Department of Electrical Engineering,The Hong Kong Polytechnic University,Hong Kong(e-mail:eehz.huang@connect.polyu.hk; eecychun@.hk).

Color versions of one or more of thefigures in this paper are available online at .

Digital Object Identifier10.1109/TPWRS.2012.2190110generation facilities has been proven to contribute to system’s dynamic and transient stability[3].The robust control theory and intelligent algorithms have been applied to design PSS for DFIG.Reference[4]applied the method of eigenstructure to assign new eigenvalues to the closed-loop system of DFIG with PSS and to improve system performance.Reference[5] developed a control scheme for DFIG with rotor side converter to damp inter-area oscillation.Reference[6]applies bacterial foraging technique to realize coordinated tuning of damping and PI controllers in the original control system for DFIG,in order to enhance damping of oscillation modes.

However,wind energy is a kind of stochastic energy[7],im-plying that the output of WF varies in a certain range due to unstable wind characteristic.Therefore,the operating point of the power system changes from time to time because of integra-tion of wind power.Deterministic small signal stability analysis (SSSA)[8]cannot provide adequate security information and so it is necessary to consider the impact of variation of WF output in SSSA.The probabilistic theory has been successfully applied to select parameters of PSS,considering a large range of oper-ating conditions[9]–[11].Through representing nodal voltage and nodal injection by normal distribution,comprising their ex-pectations and covariance values,probabilistic SSSA can obtain the range of variation of system eigenvalues.Power output of WF is a mixed random variable,which is continuous between values of zero and the rated power,but discrete at values of zero and rated power.Therefore,probabilistic SSSA has been further extended in this paper for handling this kind of distributed vari-ables.

With application of DFIG equipped with PSS,every PSS may affect all electro-mechanical oscillation modes to some extent. Sequential addition of new stabilizers disturbs previously as-signed eigenvalues and that may cause destabilization due to lack of coordination,especially in multi-machine systems[12]. Coordinated methods used in power oscillation damping con-trollers have been researched[13]–[17].Decentralized modal control(DMC)algorithms have been used to simultaneously se-lect parameters forfixed parameter PSS[13]or adaptive PSS [14].Coordination problem of additional damping controllers for FACTS devices with PSS can be dealt with an optimiza-tion-based tuning algorithm[15].

In the problem of PSS design,a parameter usually partici-pates in more than one oscillation mode,so it is difficult to de-fine the specified gradient information for the parameters during the process of optimization.Genetic algorithms(GA)have been widely used as optimization tools since they require an objective function’s value only,not its gradient information,and hence they are easily implemented.GA has been applied in[16]and

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