Application of SVC to Increase Power System Damping in Wind Parks

7/29/2019 Application of SVC to Increase Power System Damping in Wind Parks

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Abstract Wind power is one of the most important re-

newable energy in the resent years. Development and analyzingof connection conditions and effects of wind farms especially onremote areas are the main aspects of growing wind power gen-eration. Flexible AC transmission system (FACTS) devices areable to improve power system oscillation through performingflexible power flow control, secure loading, damping powersystem oscillation and even for the stabilization of wind energygeneration. One of the basic advantages of these devices is pro-vision of dynamic reactive power supply not only under system

normal conditions but also in the event of severe faults to sup-port voltage stability. In the paper is suggested adaptive con-troller of Static Var Compensator (SVC) on the basis of astaticadaptive singular regulator. The adaptive regulator identifiesitself in real time on the basis of estimated parameters andvariables of identification model and after that creates a con-trolling signal for SVC. The operation of wind park with elec-tric grid, connected through transmission and SVC is beinginvestigated. Thanks to this adaptive control the damping ofpower system is largely increased and all transient processesperformances are improved.

Index TermsWind generation, Induction generation,FACT device, STATCOM, SVC, Adaptive control.

I. INTRODUCTION

owdays power systems are facing new challenges suchas notably increasing penetration of renewable energy

sources, especially wind energy. It is known that up to nowthe most existing wind generators are equipped with induc-tion generators (IG) turbines, because of the advantages ofIGcompared to synchronous generator [1],[2]. This type ofwind turbines has some disadvantages as: bad voltage regu-lation, influence of the output voltage from the wind turbinespeed and load, the presence of capacitors, provision thenecessary reactive power for excitation. These disadvan-tages cause some problems with stability and reliability ofoperation of wind farms connected to the power system. Forexample when fault occurs somewhere in the power systemor near to connection point of wind parks this will cause

This work is the result of the implementation of Join Research Project:TU-Varna TU-Koice: Utilization of FACTS devices in electrical powersystems.

N. Djagarov is head of Department Electrical Delivery and ElectricalEquipment, Technical University of Varna, 9000, Varna , BUL (e-mail:[email protected]);

Zh. Grozdev is with the Department Electrical Delivery and ElectricalEquipment, Technical University, 9000, Varna, BUL (e-mail: groz-

[email protected]);M. Bonev is with the Department Electrical Delivery and Electrical

Equipment, Technical University of Varna, 9000, Varna, BUL;S. Filchev is with the Department Electrical Delivery and Electrical

Equipment, Technical University of Varna, 9000 Varna BUL.

voltage drop in same connection point. This will bring tounbalance between the mechanical shaft torque and the gen-erators electromagnetic torque, and the induction generatorwill speed up. Consequently, the induction generator willdraw more reactive power from the grid, which in turn willresult in further steps in voltage collapse in the network [3].

One of the main requirements of the electricitytransmission system is to maintain system voltage atappropriate levels. Modern power systems are not verystable when changing the voltage even for short periods. Onthe other hand by generation or absorption of active powerat any given point of the system the power system generatesor absorbs reactive power in significant quantities. This alsocontributes to changing the system condition. In cases whereit is difficult to install new transmission lines for increase ofpower flow it is required the existing facilities to carry morepower. The problems of voltage regulation grow and thismay lead to overbalancing the power system.

Following these conditions, the power systems mustresolve some basic operating problems, such as voltageregulation, power flow control, transient stability andreliability, power system oscillation damping and etc.

The FACTS devices [4] can be a solution to these prob-lems. They are able to provide fast active and reactive pow-er compensations to power systems, and therefore they canbe used to provide voltage support and power flow. Themore efficient utilization of existing transmission networksis obtained when the FACTS devices are suitable located.

One possible FACTS device is SVC, which can be con-nected to wind park substation [5]-[8]. This device repre-sents variable impedance device where the current through areactor is controlled using back to back connected thyristorvalves. These compensators are widely used in distributionnetwork or near large industrial loads to maintain the volt-age within certain limits, to reduce the voltage or currentdisturbances to improve dynamic stability, to increase thepower flow of transmission line. Another major reason forimplementation of these devices is the possibility for damp-ing of electricity fluctuations. The damping of power systemoscillations plays an important role not only in improvingdeliverability, but also in stabilizing the system condition inemergency situations, particularly in loosely coupled powersystems [9].

For control of FACTS devices are used all known meth-ods from the theory of automatic control: classical PI-regulators, methods of fuzzy logic and neural network, regu-

lators with adjusted parameters, regulators with variablestructure and others. The main trend is to make these con-trollers adaptive [10], [11].

Application of SVC to Increase PowerSystem Damping in Wind Parks

Nikolay Djagarov, Zhivko Grozdev, Milen Bonev and Stefan Filchev

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However, this relates to the need of large computationalresources, which will worsen their performance and hence -the quality of regulation.

The proposed adaptive regulator uses optimal singularadaptive observers. These observers based on measuredparameters of the controlled object identify the parametersand variables of minimal model of Frobenius. The maindifference of this identification from the known is that not

only the current vector is estimated but also the initial vec-tor. That avoids the iterative solution of Riccati equationsand achieves very high speed of identification and calcula-tion of control signal. Thanks to this, the calculation time ofthe control signal and feedback is negligible small in com-parison with the speed of running processes in the system.

Therefore, these regulators improve all parameters of thetransition process, damp the oscillations and improve thepower system stability like whole.

II. STUDIED POWER SYSTEM

On Fig. 1 is presented studied power system. The stud-ied system includes wind park connected to power systemtrough powerful step-up transformer (TrTL), transmissionline (TL) and static active-inductive load (Load). A windfarm consisting of six 1,5MW wind turbines is connected toa 33kV distribution system exports power to a 110kV gridthrough a 25km transmission line. The 9 MW wind farm issimulated by three pairs of 1,5MW wind-turbines. Windturbines use squirrel-cage induction generators (IG1-6). Thewind generators are connected through coupling transform-ers Tr1-6and connecting lineL1-6to wind substation busses(WSB). The wind turbine is a variable-pitch wind turbine.The pitch angle is controlled in order to limit the generatoroutput power at its nominal value for winds exceeding thenominal speed (9 m/s). In order to generate power theIGspeed must be slightly above the synchronous speed. Therequired reactive power provided by capacitor banks C1-6foreach wind generator ensures the normal operation of induc-tion generator.

On the WSB is connected static var compensator (Fig.2). This compensator represents shunt connected condenserCand thyristors controlled reactorL. The control of thyris-

tors is ensured by adaptive regulator (AR) creating control-ling signal which is proportional to conductivity of thyristorcontrolled reactor BL. After that this signal is transformedfrom control module for thyristors (CMT) into firing anglefor thyristorsTh. The thyristors controlled reactor continu-ously regulates reactive energy by regulation magnitude of

reactors current. This regulation is performed by control offiring angle of thyristors and is a result from regulating ofinductivity of shunt connected reactor. Each three-phasecapacitor banks and thyristors controlled reactor are con-nected in delta so that, during normal balanced operation,the zero-sequence tripplen harmonics (3rd, 9th... ) remaintrapped inside the delta, thus reducing harmonic injectioninto the power system.

III. MATHEMATICAL MODEL OF STUDIED POWER SYSTEM

The mathematical model of suggested power system ispresented in [12].

The transformersTrj, (j=16), TrL, TrTL and TrSVC are re-placed by aggregate dispersion resistance of primary andsecondary windings 21 TrlTrlTr zzz += . The studied power

system has n+3 nodes (where n is number of wind genera-tors) as equivalent transformer resistance are summed withreactance of corresponding lines connected in series withthem. In this way the node voltages of studied system are:terminal voltage of wing generators, UGj; voltage of WSB,USVC; voltage of infinity busses, UB;

In this equivalent replacement diagram in each nodethere is one condenser as its voltage represents a state vari-able. For this voltage is written equation which enters intoright part of equation of other elements.

A. Induction Generator

The equations of the induction generator are written insynchronous coordinate systemdq0syn:

;CGj.

jj

.

jjdt

dU

Brs

B ss

Ir

Is

ArrArs

AsrAss

Ir

Is

+

=

(1)

( )ejTTjTmj

rjdt

d=

1(2)

where: subscripts refers to the stator parameters and vari-ables, and subscript r- rotor; the elements of matrices andvectorsA and are in function of the stator and rotor resis-tance and inductive impedance and the rotor angular speed -

r and coordinate system - k; [ ] tqd i,i=Is ;

[ ] trqrd i,i=Ir ; [ ] tjqd u,u=UGj ; TTj wind turbine torque;

SVC

G1

G6

C1

C6

Tr1

Tr6 L6

L1 Load

TL

Power

SystemTrL

TrTL

TrSVCWSB

Wind Park

Fig.1. Diagram of studied power system

IG1

Il1

IG6

ICG1

ICG6

Il6

IL

ITLISVC

h1

LC

LC

LC

h2

R S T

h3

h4 h6

h5

CMT

AR

BL

UREFUT

Fig.2. SVC delta connection diagram with control structure

Th1 2 Th3,4 Th5,6


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i.ii.i.xT drqqrdadej = - the generator electromagnetic

torque; UCGj voltage vector of exciting condenser of windgenerator; mj - mechanical time constant of wind genera-

tor:

B. Wind Turbine

For the mathematical model of wind turbine is assumed

that the hardness of the gearbox is infinite and thecoefficient of friction and mechanical time constant of theturbine are combined with those of the generator. Output ofthe turbine is described by the following dependence [13]

( )3

wv2

.A.

T

,.pC

TT = (3)

where: Cpis a specific nonlinear factor depending from two

parameters:wv

R. = - relation of speed at the top of turbine

blade to the wind speed and attack angle of wind turbineblades [grad]. Also this factor depends also from aerody-

namic characteristics of wind turbine blades and workingmode; specific density of air [kg/m3]; A surface of tur-bine circle [m2];w wind speed [m/s]

C. Exciting Capacitor

CGj.CGjCGjCGjdt

dIBHU += (4)

where: CGjCGjCGj UAH .= ; ljGjCGj III = , the ele-

ments of matricesACGj andBCGj are in function from pa-rameter of condenser capacity.

D. Reactor of SVC

SVCSVCLSVCLSVCL.

dt

dUBHI += (5)

where:SVCLSVCLSVCL

.IAH = ; the elements of the matri-

cesALSVCandBLSVCare functions of parameter of SVC reac-tor.

E. Capacitor of SVC

SVCCSVCCSVCCSVC.

dt

dIBHU += (6)

where: SVCSVCCSVCC .UAH = ; SVCCSVCLSVC III += ;

TLLSVCLlCGj IIIII = ; =

6

1ljl II ;

F. Transmission lines L16and TL

( )jiljljlj -.dt

dUUBHI += (7)

where: ljljlj .IAH = ; the elements matrices Alj and lj are

functions of transmission line parameters; Ui and Uj, -volt-age vector of connection nodes for corresponding line.

IV. ALGORITHM FOR ADAPTIVE CONTROL OFSVC

The basic function of the adaptive control is continuously

identifying a control object in real time by linear modelfrom low order and creation of control signal. In studiedsystem is used a scalar modal adaptive regulator. Its mainfunction is keeping the voltage magnitudeUT close to refer-

ence point UREF, which is given from the operator. On theinputs of adaptive regulator is feeding discrete sample fromvoltage vector from measuring point and reference voltagegiven from operator. The scalar adaptive modal regulatoridentifies in real time control object on the basis of esti-mated parameters and variables of the model and create con-trol signal. The obtained signal after adaptive regulatorBL isfed on the input on the controlling module for thyristors.

The CMT creates firing angle for thyristorsTh1-6(Fig. 2).The observed system might be present by a following

type of a linear model in the state space describing fromfollowing differential equations [14]:

( ) ( ) ( )k.k.x1kx vbA +=+ (8)

( ) ( )k.xky tc= (9)

( ) ( ) ( )kzkk += uv (10)where: x(0)=x0, k=0,1,2,.; x(k),x(k+1) are an unknowncurrent state vector in two neighbor moments of sample;x(0) is an unknown initial state vector; u(k) is an input sig-nal;z(k) is a limited input sequence using for identification.

A,b and c are unknown matrices and vectors of the fol-lowing type:

=

321 aaa

100

010

A ; [ ]0,0,1=tb ; [ ]1,0,0=tc (11)

The input/output data are shaped in following matricesand vectors.

=

y(2)

y(1)

y(0)

1Y ;

=

y(5)

y(4)

y(3)

2Y ;

=

v(2)

v(1)

v(0)

1V ;

=

y(4)y(3)y(2)

y(3)y(2)y(1)

y(2)y(1)y(0)

12Y (12)

The vector estimate a is calculating by following ex-pression:

1212 VYa.Y = (13)

The initial steady state vector ( )0x estimation is calcu-lated by the optimal estimator of following type:

( ) 1Y0x = (14)The current state vector is estimated by full optimal sin-

gular adaptive (OSA) observer

( ) ( ) ( ) ( )k.yk.vk.1k gbxFx ++=+ )

(15)( ) 0xx =0 ; k=0, 1, 2, ,

where:Tg.cAF =

))

(16)

[ ]n21 ,...g,gg=Tg (17)

The determination of formulate problem with the help ofsuggested algorithm exist only if matrix Y12 is singular

0det 12Y (18)

The stabilizing signalBL is calculated by using of astaticscalar modal stabilizer with scale factor k0 from followingtype [15]:

( ) ( ) ( ) ( )[ ]k,....kk,kkkk n21=k (19)

( ) ( )k1k kbAAz .=)))

(20)


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( ) ( ) ( )1

0 1kkk

= b.AIc

1zn

T))

(21)

( ) ( ) ( ) ( )1k.k.ykkkB ref0L += xk)

(22)

where:yref is reference signal given from the operator.After determination of control signal for SVC reactors

BL follows transformation of specific values ofBL into val-ues of firing angle Th for thyristors in degrees. This trans-

formation is performed by next expression:( )( ) LnomL .B2sin22B += (23)

where:BLpu - values ofBL converted into real system in perunits (p.u.);BLnom nominal value ofBL.

V. EXPERIMENTAL RESULTS

For provision of correctness and effectiveness of thestudied power system a computer model inMatlab spacewas created. Different disturbances causing transient proc-

esses are simulated. Parts of obtained results are shown bel-low. The illustrated simulation processes are: Three-phaseshort cut on low voltage and medium voltage side and itsdisconnection from circuit breaker, connec-

tion/disconnection of powerful static active/inductive load,small variation of voltage from high voltage side, variationof wind speed and etc. In the graphics are shown some op-erating parameters and they are compared with conventional

control of SVC, suggested adaptive control of SVC andwithout SVC. On Fig. 3 and Fig. 4 is shown the WSBvoltage at three-phase short cut in low voltage side in time10.00sec with duration 0.088s (in one wind generator termi-nals). On the figures is illustrated with solid line the studiedsystem with adaptive control of SVC, with dashed line with conventional control of SVC and with dotted line without SVC. On Fig. 5 is shown the zoom part from

same transient process but only operation of SVC (adaptivecontrol and conventional control).

On the Fig. 5 can be observed the operation of SVCand comparison between adaptive control and conventionalcontrol at connection/disconnection of powerful static ac-tive-inductive load in WSB. Also, as in Fig. 3 the opera-tion of wind park is simulated without connected SVC.

On the Fig. 6 can be observed the performance of windpark at variation of wind speed (in 10th sec. the wind speeddecrease to minimum and in 15th sec. returns to same levelof speed).

Fig. 4. Voltage at WSB buses

UWSB [p.u.]

9.5 10 10.5 11 11.5 12 12.5 13 13.5 14

0.993

0.994

0.995

0.996

0.997

0.998

0.999

1

1.001

1.002

1.003

time [sec]

Fig. 3. Voltage at WSB buses

UWSB [p.u.]

9.8 10 10.2 10.4 10.6 10.8 11 11.2

0.5

0.6

0.7

0.8

0.9

1

1.1

time [sec]

Fig. 5. WSB operation characteristics at connection/disconnection ofpowerful static active inductive load:a) - WSB voltage; b) Reactivepower

UWSB [p.u.]

10 11 12 13 14 15 16 17 18 19

-2

0

2

4

6

8

time [sec]

0.82

0.84

0.86

0.88

0.9

0.92

0.94

0.96

0.98

1

1.02

QWSB [MVar]

a)

b)


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VI. CONCLUSION

In the paper is suggested the adaptive controller for SVCused in wind parks. The proposed adaptive control allowsimproving the dynamic characteristics of the studied com-pensator. Due to low requirements of computing resources

the adaptive controller allows utmost the damping of systemoscillation in power system containing wind parks.

VII. REFERENCES

[1] Claudio L.Souza et. al., Power System Transient Stability Analysisincluding Synchronous and Induction Generator,IEEE Porto PowerTech Proceedings, vol. 2, pp. 6, 2001.

[2]

V. Akhmatov, Analysis of Dynamic Behavior of Electric PowerSystems with Large Amount of Wind Power, Ph.D. dissertation,Technical University of Denmark, Kgs. Lyngby, Denmark, Apr. 2003.

[3] J. O. G. Tande, Grid Integration of Wind Farms,Wind Energy, vol.6, No. 3, pp. 281-295, June 2003.

[4] N. G. Hingorani, L. Gyugyi, Understanding FACTS: Concepts andTechnology of Flexible AC Transmission Systems, IEEE, New York,2000, ISBN 0-7803-3455-8.

[5] P. Girox, G. Sybille, SVC controller, Power System Laboratory,IREQ Hydro-Quebec, www.mathworks.com, 2006.

[6] M. Noroozian, SVC Modelling in Power Systems, ABB PowerSystems AB, S-721 64 Vasteras, Sweden, Apr. 1996.

[7] Z. Gu, D.T. Rizy, Neural Networks for Combined Control of Capaci-tors Banks and Voltage Regulators in Distribution Systems,IEEETransactions on Power Delivery, vol. 11, No. 4, Oct. 1996, pp. 1921-1928.

[8] P. N. Boonchian, A. Sode-Y ome, N. Mithulananthan, K. Aodsup,Voltage Stability in Power Network when connected Wind FarmGenerators, PEDS, 2009, pp. 655-660.

[9] E. Z. Zhou, Application of Static Var Compensators to IncreasePower System Damping,IEEE Trans. On Power Systems, vol. 8, No.2, May 1993, pp.655-661.

[10] N. Yang, Q. Liu and J.D. McCalley, TCSC Controller design fordamping interarea oscillations, IEEE Trans. on Power Systems, vol.13, No. 4, Nov. 1998, pp. 1304-1310.

[11] C. A. Canizares, Z. T. Faur, Analysis of SVC and TCSC controllersin voltage collapse,IEEE Trans. on Power System., vol. 14, pp. 158-165, Feb. 1999.

[12] N. F. Djagarov, Transient electromechanical processes calculation ofpower systems with complex topology,Electricity, Moscow, No.1,1990, pp. 9-16.

[13]J. Zaragoza, J. Pou, A. Arias, C. Spiteri, E. Robles, S. Ceballos,Study and experimental verification of control tuning strategies in avariable speed wind energy conversion system,Renewable Energy,vol. 36, 2011, pp. 1421-1430.

[14] L. N. Sotirov, Selected chapters from modern control theory, Techni-cal University, Varna, Bulgaria 1998.

[15] N. N. Nikolov, Study of algorithms for synthesis of state modaladaptive regulators, Ph.D dissertation, Dept. of Computing andAutomation, Technical Univ. Varna, Bulgaria, 2008.

6th I nternational Conference on Deregulated ElectricityMarket Issues in South-Eastern Europe DEMSEE, Bled,Slovenia, 20-21 Sept 2011

0.94

0.95

0.96

0.97

0.98

0.99

1

8 10 12 14 16 18 20 22

0

1

2

3

4

5

6

7

Fig. 6. WSB operation characteristics at wind variation:a) - WSBvoltage; b) Reactive power.

UWSB [p.u.]

QWSB [MVar]

a)

b)

time [sec]

Application of SVC to Increase Power System Damping in Wind Parks

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