Design of Wide-Area Damping Controllers for Interarea Oscillations

1136 IEEE TRANSACTIONS ON POWER SYSTEMS, VOL. 23, NO. 3, AUGUST 2008

Design of Wide-Area Damping Controllers forInterarea Oscillations

Yang Zhang, Student Member, IEEE, and Anjan Bose, Fellow, IEEE

Abstract—This paper develops a systematic procedure of de-signing a centralized damping control system for power gridinterarea oscillations putting emphasis on the signal selectionand control system structure assignment. Geometric measures ofcontrollability/observability are used to select the most effectivestabilizing signals and control locations. Line power flows andcurrents are found to be the most effective input signals. The syn-thesis of the controller is defined as a problem of mixed �

output-feedback control with regional pole placement and isresolved by the linear matrix inequality (LMI) approach. A tuningprocess and nonlinear simulations are then used to modify thecontroller parameters to ensure the performance and robustnessof the controller designed with linear techniques. The designprocess is tested on the New England 39-bus ten-machine system.

Index Terms—Damping controller, interarea oscillations, robustcontrol, wide-area control, wide-area measurements.

I. INTRODUCTION

L ARGE power systems typically exhibit multiple domi-nant interarea swing modes on the order of 0.1–1.0 Hz.

This type of oscillations limits the amount of power transfer onthe tie-lines between the regions containing coherent generatorgroups. Today, oscillatory stability control has become more im-portant because these low-frequency interarea oscillations areoften poorly damped with the increase of energy interchangesacross the power grids.

The traditional approach to damp out interarea oscillationsis to install power system stabilizers (PSS) that provide supple-mentary control action through the generator excitation systems.In recent years, supplementary modulation controllers (SMC)are added to FACTS devices to damp the interarea oscillations.These controllers usually use local inputs and cannot always beeffective in easing the problem due to two main shortcomings.First, based on a linearization of the system model in a nom-inal operating point, conventional local controllers designed bythe classical control techniques have their validity restricted toa neighborhood of this point. But power systems constantlyexperience changes in operating conditions due to variationsin generation and load patterns and changes in transmissionnetworks. In addition, some uncertainty is introduced into thepower system model due to inaccurate approximation of the

Manuscript received March 14, 2007; revised July 14, 2007. This work wassupported in part through the Consortium for Electric Reliability TechnologySolutions (CERTS), funded by the Assistant Secretary of Energy Efficiencyand Renewable Energy, Office of Distributed Energy and Electricity Reliability,Transmission Reliability Program of the U.S. Department of Energy under In-teragency Agreement No. DE-AI-99EE35075 with the NSF and in part throughPSerc, an NSF I/UCRC. Paper no. TPWRS-00171-2007.

The authors are with the Washington State University, Pullman, WA 99163USA (e-mail: [email protected]; [email protected]).

Digital Object Identifier 10.1109/TPWRS.2008.926718

power system parameters, neglected high frequency dynamicsand invalid assumptions made in the modeling process. Second,local controllers lack global observation of interarea modes. Ithas been proved that under certain operating conditions an inter-area mode may be controllable from one area and be observablefrom another [1]. In such cases, local controllers are not effec-tive for the damping of that mode.

The recently developed robust control theory and wide-areacontrol system technologies offer a great potential to overcomethe shortcomings of conventional local controllers. Robustcontrol techniques have been applied to design controllers thatformally guarantee the system stability with an acceptableperformance for a wide range of operating conditions [2]–[4].With the technology of phasor measurement units (PMU), syn-chronized dynamic data of power systems can be transferredacross the whole power system [5], [6]. The availability ofwide-area measurements enables the real time detection andcontrol of small signal instability in large scale power systems[7]. Bonneville Power Administration (BPA) developed awide-area control system (WACS) for the transient stabilityand voltage support of their power system [30]. For somespecific grid structures and operating conditions, wide-areacontrol is more efficient than local control in preventing lossof synchronism. References [8] and [9] show that for a studysystem resembling the Hydro-Québec grid, local controls needfrom four to 20 times larger gain than wide-area control toachieve a similar damping effect.

Many researchers achieved good results by applyingwide-area measurements and robust control techniques to thedesign of wide-area control system for power system oscilla-tions damping. One promising approach is to design wide-areameasurements based controllers that provide control actionsthrough generator excitation systems supplemental to the ac-tion of local PSSs. In [10], a remote feedback controller (RFC)design methodology using PMU measurements is described.Reference [11] proposes a design of supervisor PSS (SPSS)that exchanges information with local PSSs to improve powersystems oscillatory stability. Reference [12] proposes a decen-tralized/hierarchical structure for a wide-area control system.Wide-area signals based PSSs are used to provide dampingadditional to the local ones.

In this paper we develop a systematic design procedure ofwide-area damping control systems by combining stabilizingsignal selection and LMI based robust control design together,with particular attention to several issues. One such issue is theselection of input stabilizing signals. The number of input sig-nals and the effect of different types of signals on control perfor-mance are important design considerations. For example, gen-erator speed deviations have often been used as controller in-

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ZHANG AND BOSE: DESIGN OF WIDE-AREA DAMPING CONTROLLERS FOR INTERAREA OSCILLATIONS 1137

puts but these are not easily obtained and need to be synchro-nized, which often increases time delays. Our results show thata comparison of different inputs can lead to a smaller numberof simpler inputs that provide the same control performance.The method of geometric measures of controllability and ob-servability introduced by Hamdan [13] is used to select the mosteffective stabilizing signals and control locations.

In the literature, while single objective synthesis techniqueslike optimization are often used for robust controller de-sign [2]–[4], [11], [15], multiobjective synthesis is seldom ap-plied in the design of wide-area damping controllers for powersystem oscillations. Multiobjective synthesis has several advan-tages over single objective synthesis as discussed in part IV. Thedesign method proposed in this paper for a wide-area dampingcontroller (WADC) to provide damping signals simultaneouslyto automatic voltage regulators (AVRs) of several selected gen-erators in addition to their local PSS control signals, is a multi-objective synthesis, a mix of time- and frequency- domain spec-ifications ranging from and performance to regionalpole placement constraints.

The resulting WADC controller is a robust multiple-input-multiple-output (MIMO) controller. Because linear techniquesare used in designing this controller, it should be further tunedand its performance and robustness should be tested on atest-bed that represents the realistic power system with all itsnonlinearities, preferably the same type of simulation programsthat are used to study the dynamics of power systems. In ourdesign process, nonlinear simulations are conducted using theTransient Security Assessment Tool (TSAT) [26] to test theefficacy of the designed WADC, which is modeled as a TSATUser-Defined Model (UDM).

This paper is structured as follows: Section II presents thearchitecture of the proposed wide-area damping control system;Section III presents techniques used in the selection of stabi-lizing signals and location of control devices; Section IV brieflydiscusses the mixed output feedback control withregional pole placements in the LMI framework; Section Vdescribes the general procedure of the design of wide-areadamping controller; Section VI gives one numerical exampleand Section VII presents the conclusions.

II. WIDE-AREA DAMPING CONTROLLER STRUCTURE

The decentralized structure and the centralized structure arethe most often used approaches for the design of damping con-troller. Based on local measurements, the first approach does notneed additional telecommunication equipment. But, decentral-ized/local control alone may not be enough to meet the dampingneeds of the future electrical networks, which are highly inter-connected and stressed [9]. In contrast, centralized wide-areadamping control provides more efficient solutions due to theavailability of large amount of system wide dynamic data andbetter observation of interarea modes. Wide-area controls in-clude any control that requires some communication link to ei-ther gather the input or to send out the control signal [14]. Itis found that if remote signals are applied to the controller, thesystem dynamic performance can be enhanced with respect tointerarea oscillations [1], [10]. Even though additional telecom-munication equipment is needed for the realization of such a

Fig. 1. General structure of wide-area damping control system.

centralized wide-area damping control system, it still turns outto be more cost-effective than installing new control devices.

In most power systems, local oscillation modes are often welldamped due to the installation of local PSSs, while interareamodes are often lightly damped because the control inputs usedby those PSSs are local signals and often lack good observa-tion of some significant interarea modes. This suggests that awide-area controller using wide-area measurements as its inputsto create control signals supplement to local PSSs may help todamp interarea oscillations out. A centralized controller struc-ture is thus proposed and shown in Fig. 1.

In the proposed wide-area damping control system, selectedstabilizing signals are measured by PMUs and sent to the con-troller through dedicated communication links. The wide-areadamping controller calculates modulation signals and sendsthem to the selected generator exciters.

Normally, all the local PSSs are still conventional controllersdesigned by classical methods. In this design, they are modeledin the open loop state-space representation, on which the designof the WADC is based. The whole damping system includestwo levels. The first level is fully decentralized and consists ofconventional PSSs. The second level is centralized and providessupplemental damping actions in addition to the first level forthe lightly damped interarea oscillations.

III. SELECTION OF MEASUREMENTS AND CONTROL LOCATIONS

Wide-area control is desirable for interarea oscillationdamping mainly because it provides better observability andcontrollability and thus better damping effects of those modes.This benefit partly comes from the availability of system-widedynamic information contained in remote stabilizing signals.In the selection of stabilizing signals and control locations, itis desirable to use as few measurements and control devices aspossible to achieve satisfactory damping effects. This effort isworthwhile from an economic viewpoint because less measure-ment and control points mean less cost for communication linksand/or controllers. Furthermore, less control loops are involved,


so that the interaction between loops can be reduced. Accordingto the findings of this research, only a few measurements andcontrol points are needed to achieve acceptable damping fortroublesome interarea modes under the proposed centralizednetwork configurations.

The most often used method to select locations and stabilizingsignals for PSSs and FACTS devices is controllability/observ-ability analysis [16], [17]. This method is derived from modalcontrol theory of linear time-invariant system and calculatesresidue-based measures of modal controllability/observability.The limit of residue-based measures is that they are only validfor the signals of the same type. This approach suffers a scalingproblem when comparing the strength of signals of a widelydiffering physical significance, such as power flow in a tie-line(MW), bus frequency (Hz), shaft speed (rad/s), and angle shift(deg.) [12]. To overcome this shortcoming, the method used in[27], geometric measures of modal controllability/observability,is also used in this research to evaluate the comparative strengthof a signal or the performance of a controller with respect to agiven mode.

After linearization around a given operating condition andelimination of algebraic variables, the state-space model of thestudied system can be written as

(1)

(2)

where is the state vector and the measured outputvector; is the input vector whose entries are controlsignals sent out by WADC; , andare state, input and output matrices, respectively.

Suppose matrix has distinct eigenvaluesand the corresponding matrices of right and left

eigenvectors, respectively, and . The geometric measures ofcontrollability and observability associatedwith the mode are

(3)

(4)

with the th column of input matrix (corresponding tothe th input) and the th row of output matrix (corre-sponding to the th output). and are the modulus andEuclidean norm of , respectively; is the geometricalangle between the input vector and the th left eigenvector,while is the geometrical angle between the outputvector and the th right eigenvector.

The joint controllability/observability measure is defined by

(5)

In the proposed design procedure, only a few measurementswith the highest observability of interarea modes are selectedas stabilizing signals and only a few generators with the highestcontrollability of those modes are chosen as control locations.

Fig. 2. Multiobjective damping controller synthesis configuration.

IV. MIXED OUTPUT-FEEDBACK CONTROL WITH

REGIONAL POLE PLACEMENTS VIA LMI OPTIMIZATION

Robust control techniques were introduced into power systemdamping controller design in the last decade to handle mod-eling errors and uncertainties. The most often used approachis the single objective synthesis, in which all control require-ments are weighted and formulated in a single objective. It iswell known that each robust method is mainly useful to capturea set of special specifications [20]. control maintains goodrobust performance in presence of model uncertainties. But itis mainly concerned with frequency-domain performance anddoes not guarantee good transient behaviors for the closed-loopsystem. control gives more suitable performance on systemtransient behavior and is often applied to meet performancespecifications and impulsive disturbance rejection while guar-anteeing closed-loop stability. In many practical applications,the trade-off between conflicting requirements has to be madeso that a single norm can represent all design requirements. Inthis case, minimizing this performance index is not very effec-tive because the resulting controller is often conservative and theachievable closed-loop performance is limited. What is more,the selection of weighting functions to meet the trade-off be-tween conflicting requirements is hard and time consuming [25].To overcome these limitations of a single objective synthesistechnique, the multiobjective synthesis technique, which can in-corporate various design specifications easily, is naturally con-sidered. In our design process, the mixed output-feed-back control with regional pole placement is applied to designa wide-area damping controller.

A. Multiobjective Damping Controller Synthesis Formulation

The configuration of the multiobjective damping controllersynthesis is shown in Fig. 2. The output channel is associ-ated with the performance and the channel is associ-ated with performance. is a low-pass filter in theperformance channel for output disturbance rejection. isa high-pass filter or some small constant in performancechannel that is used to reduce the control effort. is ahigh-pass filter in the performance channel to ensure ro-bustness against model uncertainties.

Good design specifications ensure high-performance and easyimplementation of designed controllers. In the single objective

synthesisapproach, the performanceisusedtoevaluateall design specifications like disturbance rejection, robustnessand control effort. In contrast, in this multiobjective synthesisapproach, the performance is only used to measure robust-ness against dynamic uncertainty. The performance is used to


Fig. 3. LMI region for pole placement.

measure control effort and output disturbance rejection becausecontrol gives more suitable performance on system transient

behavior and control cost can be more realistically captured bythe norm [18]. Since our aim is to damp out interarea oscilla-tions, the center-of-inertia (COI) differences between areas areselected as controlled output associated with performance.

Pole-placement constraint is added to the multiobjective con-trol problem shown in Fig. 2 to ensure good transient responseof the closed-loop system. This problem can be formulated inthe LMI framework.

B. LMI-Based Mixed Output-Feedback Control WithRegional Pole Placements

The multiobjective optimization problem discussedabove is solved by LMI techniques. It has been shown in [22]that LMI provides a natural framework to formulate the mul-tiobjective control problems without additional conservatism.LMI offers more flexibility for combining several constraints onthe closed-loop system or objectives in a numerically tractablemanner. The resulting controllers do not in general suffer fromthe problem of pole-zero cancellation [21]. Reference [20]gives a detailed description of an LMI approach to such acomplex problem of mixed output-feedback controlwith regional pole placement.

Good transient response can be achieved by placing allclosed-loop poles in a prescribed region in the left half plane.Pole constraints are also useful to avoid fast dynamics andhigh-frequency gain in the controller, which in turn facilitateits digital implementation. Excessively large controller gainsshould be avoided because they could lead to controller outputsaturation and a poor large disturbance response of the system.To avoid large feedback gains, the system poles should not beshifted too far into the left half plane. Restricting the real partsof the closed loop poles to be greater than a suitable negativenumber inhibits such excessive shifting [23]. One LMI regionfor all pole placement objectives discussed above is shown inFig. 3. When the closed-loop poles are in this region, it ensuresminimum damping ratio , minimum rate of decayand acceptable controller gains.

V. WIDE-AREA DAMPING CONTROLLER DESIGN PROCEDURE

In this research, the design of wide-area damping controllersfor interarea oscillations includes the following steps:

1) System model and small signal analysis: The full-ordernonlinear model of the studied system is calculated using

Matlab [19]. All generators are represented by detailedmodels, i.e., the two-axis model with exciter, governorand conventional PSS with two lead-lag compensationblocks. The nonlinear model is linearized around a chosenoperating point. Then, small signal analysis is conductedwith this linear model to get the frequencies, shapes anddamping ratios of critical interarea modes.

2) Selection of measurements and control device locations:Measurements that can be easily obtained and synchro-nized and have the highest observability of critical inter-area modes are good candidates for input signals. Geo-metric measures of modal controllability/observability in-troduced in Section III are used to evaluate the comparativestrength of candidate signals and the performance of con-trollers at different locations with respect to a given inter-area mode. The most often used input signals are voltagemagnitudes, voltage phase angle, line power or current, fre-quency and generator rotor speeds.

3) Linear model reduction: The controller obtained by theLMI approach is of full order, that is, the same size as thedesign model including weighting functions. A middle sizesystem usually has several hundreds of states. To design acontroller with such a high order model is neither practicalnor necessary. Therefore, model reduction is often appliedto obtain a lower order model for controller design. Thereduced order model should be assured to have the sameglobal characteristics as the original system [24]. In this re-search, the balanced model reduction via the Schur methodprovided by the robust control toolbox in Matlab [19] isused for the model reduction task.

4) Controller synthesis: An LMI approach to the mixedoutput-feedback control with regional pole

placement is applied to design a wide-area dampingcontroller for interarea oscillations. The designed con-troller should meet the requirements of robust stability,robust performance and acceptable transient response.Sometimes the order of the obtained controller still needsto be reduced for easy implementation. In this case, thebalanced model reduction is applied again.

5) Closed-loop verification and nonlinear time domain sim-ulation: The performance of the controller is evaluated inthe closed-loop system with the full-order linear model byusing Matlab. The controller is then tuned and its perfor-mance in the actual nonlinear power system is evaluated bytime domain simulation using TSAT. The robustness of thedesigned controller is verified for different operating con-ditions and fault scenarios.

VI. RESULTS OF CASE STUDIES

A wide-area damping controller is designed for the New Eng-land 39-bus ten-machine system, which is shown in Fig. 4. De-tailed model descriptions and all parameters including networkdata and dynamic data for the generators, excitation systems,PSSs can be found in [28]. Some modifications have been madeto create a simple system modal structure so that the controllerdesign procedure can be illustrated more clearly. The systemis stressed by increasing the load and generation level. In thisdesign, the conventional PSSs are tuned for local modes first


Fig. 4. The 39-bus ten-machine test system.

TABLE ICLASSIFICATION OF ELECTROMECHANICAL OSCILLATION MODES

by the method used in [1]. The wide-area controller is then de-signed for the interarea modes.

• Full-order model and small signal analysis: All generatorsare represented by the detailed model except generator 1,which is an equivalent unit. The model is linearized arounda nominal operating point. Small signal analysis showsthat this system has several local and interarea modes withdamping ratios less than 10%. The classification of theselightly damped modes is shown in Table I. Modes 4 to 8are local ones. Even though their damping ratios are low,they will not last beyond 10 s because of their relativelylarge frequencies. It is not necessary to provide supple-mental damping to these modes.

• Selection of measurements and control device locations:The system has three coherent generator groups exceptthe equivalent generator G1. (G2, G3), (G8, G9, G10) and(G4, G5, G6, G7) are nuclei of these groups correspond-ingly. Several kinds of input signals, such as line active

TABLE IIMAXIMUM CONTROLLABILITY AND OBSERVABILITY MEASURE

FOR 39-BUS TEN-MACHINE SYSTEM

powers and currents, generator rotor speeds and voltagephase angle difference, are compared. Table II shows thecontrol locations with maximum controllability and signalswith maximum observability with respect to different inter-area modes. in Table II, is the current magnitude of theline connecting bus and ; is the active power of theline connecting bus and ; is the voltage angle dif-ference between bus and . Reference [29] shows that forhigh stress conditions, current magnitude is a better inputsignal for the modulation of the parallel Pacific HVDC In-tertie to damp Pacific AC Intertie oscillations. It is found inthis research that the active power and current of the sameline have nearly the same observability with respect to aspecific interarea mode. Line active power is selected asthe input signal of the designed controller in this research.According to Table II, G3, G7 and G8 are selected as con-trol locations. The selection of input signals is not very ob-vious. A large number of measurements is undesirable be-cause this will increase possible interaction between con-trol loops and the cost for communication links.is selected as an input signal for the damping of mode 2.Since has good observability for both mode 1 andmode 3, it is also selected as an input signal. As shownin simulations, these two signals are enough. Each tie-linepower contains information of all interarea modes in dif-ferent levels. In fact, itself contains enough infor-mation for all three interarea modes and could be the onlyinput signal for the controller at the cost of a higher gainand a little bit worse but still acceptable damping effects.

• Model reduction: The original linear model order is 88. Itis reduced to a 12th-order model by the method of balancedmodel reduction.

• Controller synthesis: The hinfmix function available inthe LMI Control Toolbox of Matlab [19] was used toperform the necessary computations. Two controllers aredesigned. The first controller C1 has two input signals,

and . The second controller C2 has onlyone input . Both controllers provide control signalsto generator G3, G7 and G8, as shown in Fig. 4. Theorders of two resulting controllers are reduced to 10. Thefrequency response of controller C1 is shown in Fig. 5.In each subplot, the upper curves show the amplitudechange and the lower curves show the phase shift, both asfunctions of frequency. Weighting functions are given by


Fig. 5. Frequency response of controller C1. (a) Frequency response of controlloops from inputs to generator G3. (b) Frequency response of control loops frominputs to generator G7. (c) Frequency response of control loops from inputs togenerator G8.

TABLE IIIIMPROVED DAMPING OF INTERAREA MODES

• Closed-loop verification and nonlinear time domain simu-lation: The resulting reduced-order controllers are first ver-ified by small signal analysis. Table III shows the improveddamping of interarea modes with wide-area damping con-trollers. Fig. 6 shows the impulse response of the rotorspeed deviation of generator 5 without and with the con-trollers. The impulse signal is added to the input mechan-ical torque of generator 5.When implemented in the actual nonlinear system, the con-troller designed with linear techniques may not have asgood performance and robustness as in linear simulationbecause of the loss of some system properties in modellinearization and model reduction. It is necessary to tunethe controller parameters and verify its effectiveness with

Fig. 6. Rotor speed response of generator 5 to impulse disturbance.

Fig. 7. Performance improvement of controller C1 after tuning.

TABLE IVDAMPING RATIOS AND FREQUENCIES OF INTERAREA

MODES FOR DIFFERENT LINE OUTAGES

nonlinear simulations. In our design process, controller pa-rameters like gains, zeros and poles are manually modified(tuned) from observation of the controller performance innonlinear simulations. Fig. 7 shows the performance im-provement of the controller C1 after such tuning. The faultis a three-phase fault on bus 27 for four cycles and thecurves are the transient response of active power in line17–18.The eigen-analysis of the system was carried out fordifferent operating points to verify the robustness of thedesigned controller. Table IV displays the robustness ofthe controller C1 in case of the outage of different heavilyloaded lines. Table V shows the performance of the con-troller C1 for different tie-line flows between the areacontaining generator G4, G5, G6, G7 and the rest of thesystem. The same analysis conducted for the system withcontroller C2 showed that controller C2 also improved thedamping of the interarea modes satisfactorily but not aswell as C1.


TABLE VDAMPING RATIOS AND FREQUENCIES OF INTERAREA

MODES FOR DIFFERENT POWER FLOWS

Fig. 8. Active power of line 16–17 response to a three-phase fault on bus 16.

To evaluate the performance and robustness of the designedcontrollers in different fault scenarios, nonlinear time do-main simulations are conducted using TSAT. Controlleroutput limits are 10% of the synchronous machine ter-minal voltage.Two types of faults are simulated. The first type is a three-phase short circuit fault applied to buses for four cycles.Several critical buses connected with heavily loaded trans-mission lines were tested. The second type is a three-phaseshort circuit fault applied to transmission lines for fourcycles. The fault was cleared by taking out the faultedline. Several critical heavily loaded transmission lines weretested. The two controllers achieved satisfactory dampingeffects for all of these scenarios. Fig. 8 shows the transientresponse of the active power in line 16–17 to a three-phasefault applied to bus 16. Fig. 9 shows the transient responseof the active power in line 15–16 to a three-phase fault ap-plied to line 16–24. It can be seen that the damping effectof controller C1 is a little better than controller C2. Thisshows the benefit brought by using more measurements,which provide more system dynamic information.

VII. CONCLUSIONS

In this paper, a systematic design procedure for wide-areadamping control systems is described. A centralized structure isproposed for such systems. The comparative strength of candi-date input signals and the performance of output control signalsat different locations with respect to interarea modes are evalu-ated by geometric measures of controllability/observability. Thesynthesis of the robust MIMO controller is defined as a problemof mixed output-feedback control with regional pole

Fig. 9. Active power of line 15–16 response to a three-phase fault on line16–24.

placement and is resolved by the LMI approach. The final stepof the design method is the tuning and testing of this linearlysynthesized controller on full nonlinear simulations to obtainthe desired robustness and control performance. This designmethod was tested on the 39-bus New England system. Fromthe simulation results, the following conclusions can be drawn:

• Geometric measures of controllability/observability are ef-fective in evaluating the comparative strength of candidatestabilizing signals of widely differing types.

• Active powers and current magnitudes on tie-lines are goodchoices for stabilizing signals with respect to critical inter-area oscillation modes.

• For the small size system considered, one stabilizing signalis enough for the input of a WADC. Multiple inputs im-prove the control performance only slightly for such smallsystems but are expected to be necessary for acceptablecontrol performance in large systems.

• Mixed output-feedback control with regionalpole placement can be applied to the wide-area dampingcontroller synthesis with good results which cannot beobtained by using only one of them.

• For a controller designed with linear techniques, a tuningprocess is necessary to ensure its performance in the ac-tual nonlinear systems. Nonlinear simulation using a typ-ical transient stability program like TSAT is required toshow that such a design of a wide-area damping controlleris effective in a practical implementation.

The above results are promising but the results also show thatthe use of linear, continuous methods to design a controller, al-though very powerful, requires considerable tuning, testing andfurther development in the nonlinear, discontinuous real world.As shown in this paper, the testing by nonlinear simulation usinga production grade transient stability program can establish therobustness of the controller design, i.e., the effectiveness of thecontroller over a range of operating conditions. As wide-areacontrollers have to be discontinuous by necessity, the digitalsampling rate and possible communication latency are variablesthat affect performance. Both the design process and the testingshould take these into account. Research is still needed to do soas the present day production grade simulations like TSAT arenot capable of representing such communication variables. In


our future work we intend to do such development of the designcapabilities as well as move the testing to a simulation of largersystems such as the WECC system. These types of design andtesting tools need to be developed before such controllers be-come robust enough for implementation in real systems.

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Yang Zhang (S’05) received the B.Eng. degree from North China ElectricPower University, Baoging, China, in 1997 and the M.Eng. degree from ChinaElectric Power Research Institute (CEPRI), Beijing, China, in 2001. He is nowpursuing the Ph.D. degree at Washington State University, Pullman, WA.

He worked for CEPRI from 2001 to 2004. His special fields of interest in-cluded power system stability and real time control.

Anjan Bose (F’89) received the B.Tech. (Honors) degree from the Indian In-stitute of Technology, Kharagpur, the M.S. degree from the University of Cali-fornia, Berkeley, and the Ph.D. from Iowa State University, Ames.

He has worked for industry, academe, and government for 40 years in powersystem planning, operation, and control. He is currently Regents Professor andholds the endowed Distinguished Professor in Power Engineering at WashingtonState University, Pullman, WA.

Dr. Bose is a member of the National Academy of Engineering and the recip-ient of the Herman Halperin Award and the Millenium Medal from the IEEE.

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Design of Wide-Area Damping Controllers for Interarea Oscillations