influence of wind farms on power system dynamic and transient stability.pdf

7/28/2019 Influence of Wind Farms on Power System Dynamic and Transient Stability.pdf

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Influence of Wind Farms on Power SystemDynamic and Transient Stability

Summary report

M. Hughes, O. Anaya-Lara, N. J enkins and G. Strbac

February 2005

DTI Centre for Distributed Generation andSustainable Electrical Energy


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Influence of wind farms on power system dynamic and transient stability

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Executive Summary

The aim of the work of this report was to investigate the ways in which bulk wind farmgeneration would interact with conventional generation and influence network fundamental

dynamic characteristics. The report is based on current studies being carried out at theUniversity of Manchester as part of the work of the DTI Centre for Distributed Generationand Sustainable Electrical Energy.

The UK Government has a declared target that renewable energy should provide 15% of UKelectricity supplies by 2015. The integration of such levels of renewable generation, mainlyfrom wind energy, into the UK power network will heavily influence network characteristicsand push network operation into currently unknown territory. Whilst the operation, controlcapabilities and dynamic characteristics of networks comprising synchronous generation arewell established and understood, the same cannot be said for networks having mixedsynchronous and induction generators. In light of this, studies are presently being carried outto establish an understanding of the basic interaction and dynamic characteristics of such

mixed generation systems and the outcome of the initial work done is reported here.

A simple generic network model, based on a three-generator system, is used for the presentdynamic studies. In order to provide results and characteristics that could be considereddirectly relevant to the UK network, an operating situation was considered in which onesynchronous generator was chosen to have the combined generating capacity of the England-Wales network, another synchronous generator to have the combined capacity of theSouthern Scotland network and the third generator to have a projected wind generationcapacity for the Northern Scotland network. Appropriate values for the generation andtransmission line interconnections were chosen in consultation with NGT. Whilst this simplegeneric model is in no way intended as an analogue of the UK network, it is considered toreflect the basic dynamic interactions that will influence the behaviour of the UK network

when bulk wind generation is present.

Time response simulation and eigenvalue analysis is used to establish basic transient anddynamic stability characteristics. A variety of generating situations are considered for thegenerator taken to represent the northern Scotland sub network. The wind generation isprovided either by wind farms based on Fixed Speed Induction Generators (FSIGs) orDoubly Fed Induction Generators (DFIGs). In addition, in order to provide a base lineagainst which wind farm influence on network dynamics can be judged, the case is alsoconsidered where the power exported is provided by conventional synchronous generation.

Dependent on the following assumptions made in the modelling, namely:

1. The converters are sufficiently robust to cater for all the demands of the DFIGcontroller during transient operation.

2. The simplified model used for the converter and its crowbar protection provides anadequate representation of behaviour for the situations studied.

3. The DFIG 3rdorder model, that ignores stator dynamics and was chosen for itscompatibility with the models normally used for conventional synchronousgenerators in power system analysis packages, adequately represents dynamicbehaviour for the situations studied.

4. The model representing the shaft dynamics of the turbine/generator system thatignores torsional oscillations is appropriate.

5. The numerous generators of wind farm generation can be represented coherently as a

single generator.


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The studies indicate the following:

i) FSIG based wind farms can contribute significantly to network damping, but arevulnerable to network faults.

ii)The control flexibility and capability of DFIG based wind farms enable suchgeneration to contribute positively to network operation in terms of voltagerecovery following faults and improved system damping.

iii)A DFIG has the potential of providing superior dynamic and transient performancethan that of a conventional synchronous generator.

iv)The results using the newly developed FMAC control scheme demonstrate theimportance of DFIG control in providing good operating performance and networksupport.

From which it can be concluded that:

i) In mixed generation networks, bulk wind generation based entirely on FSIG basedwind farms would make the network vulnerable to system faults, restrict generating

capacity and pose operational problems.ii)Bulk wind generation via DFIG based wind farms, suitably controlled, can beaccommodated on a network without introducing problems of transient or dynamicstability and can contribute positively to network operation and enhance networkdynamic characteristics.


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Table of Contents

Executive Summary..................................................................................................... 2Table of Contents......................................................................................................... 4

List of Figures..............................................................................................................5List of Tables............................................................................................................... 61. Introduction............................................................................................................. 72. Assessment of dynamic and transient stability....................................................... 83. Analysis tools..........................................................................................................84. Generic network model........................................................................................... 95. Simulation and eigenvalue analysis studies.......................................................... 10

5.1 Generator 2 represented as a conventional synchronous generator................ 11

5.2 Generator 2 as a FSIG-based wind farm......................................................... 14

5.3 Generator 2 as a DFIG-based wind farm with PVdq control.......................... 17

5.4 Generator 2 as a DFIG-based wind farm with FMAC control ....................... 186. IPSA time response studies................................................................................... 21

6.1 Generator 2 represents a synchronous generator............................................ 22

6.2 Generator 2 represents a FSIG........................................................................ 23

6.3 Generator 2 represents a DFIG with PVdq control......................................... 24

7. General conclusions.............................................................................................. 268. Appendix............................................................................................................... 27

8.1 FSIG 3rdorder mathematical model................................................................ 27

8.2 DFIG 3rdorder mathematical model ............................................................... 27

8.3 Synchronous generator 6th order mathematical model.................................... 288.4 Schematic block diagram of the synchronous generator excitation controller29

8.5 Machine models parameters............................................................................ 29

8.6 Network parameters........................................................................................ 33

9. Bibliography.......................................................................................................... 34


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List of Figures

Fig. 1. Generic network model. ................................................................................. 10Fig. 2. Generator transient performance following a fault near generator 1 of 60 ms

duration. A PSS having high saturation limits is included on generator 2........ 12Fig. 3. Transient performance following a fault near generator 1 of 60 ms duration.

PSS with nominal saturation limits.................................................................... 12Fig. 4. Transient performance following a fault near generator 1 of 80 ms duration.

Rating and power output of generator 2 reduced to 70% nominal values......... 13Fig. 5. Dominant eigenvalue loci when generator 2 is a synchronous generator with

AVR control.......................................................................................................13Fig. 6. Dominant eigenvalue loci when generator 2 is a synchronous generator with

AVR plus PSS control. ......................................................................................14Fig. 7. Transient performance following a fault near generator 1 of 35 ms duration.15Fig. 8. Transient performance following a fault near generator 1 of 40 ms duration.15

Fig. 9. Transient performance following a fault near generator 1 of 80 ms duration.Rating and power output of generator 2 reduced to 50% nominal value. ......... 16

Fig. 10. Dominant eigenvalue loci when generator 2 is a FSIG................................ 16Fig. 11. Transient performance following a fault near generator 1 of 80 ms duration.

DFIG with PVdq control....................................................................................17Fig. 12. Dominant eigenvalue loci when generator 2 is a DFIG with PVdq control. 18Fig. 13. Transient performance following a fault near generator 1 of 80 ms duration.

DFIG with basic FMAC control........................................................................ 19Fig. 14. Transient performance following a fault near generator 1 of 80 ms duration.

DFIG with FMAC basic control plus PSS auxiliary loop. ................................19Fig. 15. Dominant eigenvalues when generator 2 is a DFIG with FMAC basic

control................................................................................................................ 20Fig. 16. Dominant eigenvalues when generator 2 is a DFIG with FMAC basic control

plus auxiliary PSS loop......................................................................................21Fig. 17. Generator transient performance following a fault near generator 1 of 80 ms

duration. Generator 2 represents a synchronous generator................................ 22Fig. 18. Transient performance for the case when generator 2 represents a FSIG. A

fault is applied near generator 1 with 80 ms duration. Synchronous generator 1responses............................................................................................................ 23

Fig. 19. Transient performance for the case when generator 2 represents a FSIG. Afault is applied near generator 1 with 80 ms duration. FSIG responses............ 24

Fig. 20. Transient performance for the case when generator 2 represents a FSIG. Afault is applied near generator 1 with 80 ms duration. Synchronous generator 1responses............................................................................................................ 25

Fig. 21. Transient performance for the case when generator 2 represents a DFIG withPVdq control. A fault is applied near generator 1 with 80 ms duration. DFIGresponses............................................................................................................ 25

Fig. 22. Synchronous generator excitation controller................................................ 29Fig. 23. Steam turbine and governor control scheme model. .................................... 31


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List of Tables

Table 1: FSIG 3rdorder model................................................................................... 27Table 2: DFIG 3rdorder model. .................................................................................27Table 3. Synchronous generator parameters (Generator G1). ................................... 29Table 4. AVR Settings (Generator G1). .................................................................... 30Table 5. AVR PSS Settings (Generator G1).............................................................. 30Table 6. Steam turbine and governor parameters (Generator G1)............................. 31Table 7. Steam turbine and governor parameter (Generator G3 - main system)....... 33


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1. IntroductionThe aim of the work of this report was to investigate the ways in which bulk wind farmgeneration would interact with conventional generation and influence network fundamental

dynamic characteristics. The report is based on current studies being carried out at theUniversity of Manchester as part of the work of the DTI Centre for Distributed Generationand Sustainable Electrical Energy.

The UK Government has a declared target that renewable energy should provide 15% of UKelectricity supplies by 2015. The integration of such levels of renewable generation, mainlyfrom wind energy, into the UK power network will heavily influence network characteristicsand push network operation into currently unknown territory. Whilst the operation, controlcapabilities and dynamic characteristics of networks comprising synchronous generation arewell established and understood, the same cannot be said for networks having mixedsynchronous and induction generators. In light of this, studies are presently being carried outto establish an understanding of the basic interaction and dynamic characteristics of such

mixed generation systems and the outcome of the initial work done is reported here.

A simple generic network model has been established that has proved very useful in thegeneral assessment of wind farm contributions to network support and, in particular, thedevelopment of control schemes for wind farms employing Doubly Fed InductionGenerators (DFIGs). This generic model, based on a three-generator system, is used for thedynamic studies reported here. In order to provide results and characteristics that could beconsidered relevant to the UK network, an operating situation was considered in which onesynchronous generator was chosen to have the combined generating capacity of the England-Wales network, another synchronous generator to have the combined capacity of theSouthern Scotland network and the third generator to have a projected wind generationcapacity for the Northern Scotland network. Appropriate values for the generation and

transmission line interconnections were chosen in consultation with NGT. Whilst this simplegeneric model is in no way is intended as an analogue of the UK network, it is considered toreflect the basic dynamic interactions that will influence the behaviour of the UK networkwhen bulk wind generation is present.

The studies reported consist of both time response simulation studies and eigenvalue analysisto establish basic transient stability and dynamic stability characteristics. A variety ofgenerating situations are considered for the generator taken to represent the northernScotland sub network. The wind generation is provided either by wind farms based on FixedSpeed Induction Generators (FSIGs) or Doubly Fed Induction Generators (DFIGs). FSIGbased wind farms are widely employed but are known to be vulnerable when voltage levelsfall due to a system fault. The ability to manipulate the rotor voltage of a DFIG provides itwith a control capability that is potentially superior to that of a synchronous generator withconventional excitation control. In the DFIG case, existing and newly developed controlschemes are considered in order to demonstrate the crucial contribution that DFIG controlcan provide to network operation and support. In addition, in order to provide a base lineagainst which wind farm influence on network dynamics can be judged, the case is alsoconsidered where the power exported is provided by conventional synchronous generation.

Studies were also carried out using IPSA to demonstrate that the fundamental dynamiccharacteristics predicted for mixed wind farm and conventional generation systems using theSimulink model of the simple generic network are also given by alternative and independentsimulation means.


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2. Assessment of dynamic and transient stabilityTwo distinct stability concerns exist in power system analysis, dynamic stability andtransient stability. The former is concerned with the ability of a system to return to itsoriginal operating condition following a small perturbation. The latter, is concerned with the

ability of the synchronous machines of the system to remain in synchronism following alarge perturbation, such as is caused by a three-phase system fault that is quickly cleared.Although loss of synchronism is usually referred to as transient instability, it is notinstability in the strictest sense, it merely indicates that the system fails to retain acceptableoperating conditions following the disturbance.

The most direct way to assess dynamic stability is via eigenvalue analysis of a model of thepower system. In this case, the small-signal disturbances are considered sufficiently smallso that the equations representing the system may be linearised and expressed in state-spaceform. Then by calculating the eigenvalues and eigenvectors of the linearised system modelthe dynamic stability characteristics of the system can be evaluated. For stability, all of theeigenvalues must lie in the left half complex plane. Any eigenvalue in the right half planedenotes an unstable dynamic mode and system instability. The way in which systemoperating conditions, system parameters and controllers influence dynamic stability can bedemonstrated by observing their influence on the loci of critical eigenvalues, i.e. theeigenvalues furthest to the right in the complex plane.

Transient instability in a power system is caused by a severe disturbance that createssubstantial imbalance between the input power supplied to the synchronous generators (bythe prime-movers) and their electrical power outputs. Some of the severely disturbedgenerators will swing so far from their equilibrium positions that synchronism is lost in theprocess. Such a severe disturbance may be a sudden and large change in load, generation, ornetwork configuration. Usually the severe disturbance, under which transient stability is

tested, is a three-phase short circuit on the network. In power system terminology this isreferred to as a fault. When a fault occurs, certain generators that are electrically close to thefault location are disturbed to a greater extent than the other generators, which are remotefrom the fault. These generators tend to accelerate or decelerate depending on the nature ofthe fault, from the rest of the generators in the system. If the fault duration is too long, onemachine or a group of machines will separate from the rest of the system and losesynchronism, which in power system terms is referred to as transient instability. However,the power network is equipped with automatic devices that sense the existence of the faultsin the network and initiate action to clear the fault, i.e. isolate the faulted section of thenetwork. A matter of great importance, therefore, is that the time required (by the protectiveequipment) to clear the fault should be less than the duration of the fault that would create adisturbance large enough to cause one or more machines to lose synchronism. In systems

consisting solely of synchronous generation, loss of synchronism is the normal mode oftransient failure. However, in networks having mixed wind and conventional synchronousgeneration, transient failure may be encountered for other reasons such as the collapse ofsystem voltage causing induction generator runaway.

3. Analysis toolsPower system dynamic and transient stability studies are normally conducted using highlydeveloped software, with facilities for representing very large systems and detailed modelsof system elements. Special-purpose tools of this type are commercially available, e.g.Simpow, PSS/E and EuroStag. While most of these tools are computationally very efficient


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and reasonably user-friendly they have a closed architecture where it is very difficult orimpossible to view or change most of the component models. Some of these tools providethe flexibility of modelling controllers such as governors and exciters using block diagramrepresentation, however, they do not allow the user to modify any of the generator ornetwork models. Therefore, for the studies of this report Matlab/Simulink and IPSA havebeen selected as the analysis tools as they provide the facilities for user-defined models forthe system elements and their control systems. In Matlab/Simulink the generic networkmodel was first linearised to conduct dynamic stability studies using eigenvalue andeigenvector techniques. Although IPSA does not provide at the moment the option toconduct small-signal stability analysis, the influence of wind generation on dynamic stabilitywas assessed by observation of the damping characteristics on the post fault oscillations ofthe time domain responses. Transient stability was determined using both Matlab/Simulinkand IPSA using time domain response analysis.

4. Generic network modelThe generic network model used in the studies is presented in Fig. 1. The generator andnetwork data are chosen on the basis of a projected operating scenario with a large windgeneration component sited on the northern Scotland network.

Generator 3 is a steam turbine driven synchronous generator provided with governor andexcitation control. It is chosen to represent the main England-Wales network and has a ratingof 21,000 MVA. Generator 1 is also a steam turbine driven synchronous generator providedwith governor and excitation control. It is chosen to represent the southern Scotland networkand has a rating of 2,800 MVA. Generator 2 is chosen to represent a projected windgeneration situation on the northern Scotland network and has a rating of 2,500 MVA. Thisgenerator can be a Fixed Speed Induction Generator (FSIG) or a Doubly Fed InductionGenerator (DFIG).

When a FSIG is used capacitive compensation is provided on the generator terminals inorder to supply the reactive power demand of the FSIG whilst maintaining the desiredvoltage profile for the network. In the DFIG case two distinct forms of control scheme aredealt with. The first is a controller, termed the PVdq scheme in this report, that controlsterminal voltage via the manipulation of the d axis component of the DFIG rotor voltage andcontrols torque (or power) via the manipulation of the q axis component of rotor voltage.The second control scheme is a newly developed and patented scheme called the FluxMagnitude and Angle Controller (FMAC) scheme. Here the magnitude of the rotor voltage ismanipulated to control the terminal voltage magnitude and the phase angle of the rotorvoltage is manipulated to control the power output. The latter provides lower interactioncontrol than the PVdq scheme and lends itself more readily to the provision of networksupport, particularly with respect to voltage control and system damping.

In addition, the generation of the northern Scotland network can be provided by conventionalsynchronous generation having the same control provision as modelled for generator 1. Thissituation is used to provide a base line case against which wind generation influence onnetwork dynamics can be evaluated. Basic generator and network data employed areprovided in the Appendix.


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Generator1(SouthernScotland)

Generator 2(NorthernScotland)

Main System(England-Wales)

Load L1

Bus1 Bus2

Bus3

Bus4X1 X2

X3

Load

Fault

X11X12 X22 X21

Fig. 1. Generic network model.

5.Simulation and eigenvalue analysis studiesUsing the generic model described in the previous section, time response simulations andeigenvalue analysis were carried out to determine overall network dynamic characteristics.The time response studies simulate system performance following a three-phase fault that isapplied to the transmission system on the high voltage side of the transformer of generator 1.These studies permitted an assessment to be made of the contributions to network transientperformance of generator 2, representing the northern Scotland network, when variouslyconsidered as a steam turbine driven synchronous generator, a FSIG based wind farm and aDFIG based wind farm.

For all the time response simulation studies carried out, generators 1 and 3 employ turbinegovernor control and an Automatic Voltage Regulator (AVR) excitation control. A PowerSystem Stabiliser (PSS) was not employed on either generator 1 or 3 in order that therequirements of, and damping provision supplied by, generator 2 could be judged moreeasily. The generation levels considered are

Generator 1 2,520 MW ; Generator 2 2,240 MW ; and Generator 3 17,600 MW

The eigenvalue studies aim to establish dynamic stability characteristics and look at the waythat stability is influenced as the wind generation capacity on the northern Scotland system isbuilt up in stages to the full capacity situation employed in the time response studies (2400

MVA - 2240 MW).

For each condition considered the generation capacity of the southern Scotland network isadjusted along with the power it generates so that the central load L1 and the nominal powertransmitted to the England/Wales network are maintained at the same base levels.

The full transmission capacity of line X22 (Fig. 1) is assumed in all the cases. Theparameters of generator 2 and its transformer X21 are scaled appropriately for eachgeneration capacity case considered.


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The capacity factor, f2, of generator 2 used in the studies is defined as,

installed capacity of G2 (MVA)capacity factor 2

maximum capacity of G2 MVA (2400 MVA)f = (1)

Eigenvalues were calculated for four conditions with respect to the generation capacity of thenorthern Scotland network represented by generator 2 (G2). The situations correspond tovalues of

2 110, 2 13, f2=2 3 and 2 1f f f= = =

giving the conditions

i) Generator 2 - 1/10 nominal rating 240 MVA (f2=1/10); power output approx. 224 MWGenerator 1 19/10 nominal rating 5320 MVA; power output approx. 4,536 MW

ii)Generator 2 - 1/3 nominal rating 800 MVA (f2=1/3); power output approx. 750 MWGenerator 1 5/3 nominal rating 4,667 MVA; power output approx. 4,010 MW

iii)Generator 2 - 2/3 nominal rating 1600 MVA (f2=2/3); power output approx. 1,500 MWGenerator 1 4/3 nominal rating 3733 MVA; power output approx. 3,260 MW

iv)Generator 2 - nominal rating 2,400 MVA (f2=1); power output approx. 2,240 MWGenerator1 - nominal rating 2800 MVA; power output approx. 2,520 MW

The eigenvalue analysis was employed to evaluate the way in which both the capacity andtype of generator used to represent the northern Scotland network influence the networkdamping and dynamic stability characteristics.

5.1Generator 2 represented as a conventional synchronous generatorA. Time response studies

As referred to earlier, this case is considered to provide a base line against which thetransient and dynamic performance of the system with wind generation can be judged.

Generator 2 is a conventional round rotor synchronous generator with a static excitationsystem having an AVR with the option of incorporating a Power System Stabiliser (PSS). Itsprime mover is a steam turbine with governor control.

The operating conditions considered proved quite onerous. Without the PSS on generator 2,the system was dynamically unstable. In addition, the system was found to be transientlyunstable, with the system failing to regain synchronism, for the nominal transmission faultclearance time of 80 ms.

The response of Fig. 2 is for a fault clearance time of 60 ms. The system is seen to remain insynchronism following fault clearance. The gain that can be employed on the PSS ofgenerator 2 is restricted by transient stability considerations and the saturation limits of thePSS. In order to employ a PSS gain that was sufficiently large to produce the requiredimprovement in system damping, the saturation limits of the PSS had to be increased totwice their nominal values.


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With the nominal limit values, the gain employed in the PSS to provide the necessarydamping, leads to saturation in the PSS and the consequent loss of its stabilising influencefor the large signal levels in existence following a three-phase fault. The generator then slipsinto a dynamically unstable operating situation and the increasing swings in power and angleexcursions result in loss of synchronism as can be seen in Fig. 3.

Fig. 2. Generator transient performance following a fault near generator 1 of 60 ms duration.A PSS having high saturation limits is included on generator 2.

Fig. 3. Transient performance following a fault near generator 1 of 60 ms duration. PSS withnominal saturation limits.

The network can tolerate a clearance time of 80 ms for the fault considered, if the size ofgenerator 2 (i.e. in terms of rating and hence power output) is reduced to 70% of its nominalvalue, keeping unchanged the size and output of generator 1, and the level of the central busload. This effectively reduces both the generation capability of the northern Scotlandnetwork and the power transmitted from Scotland to the England/Wales network. Thegenerator responses for this situation are shown in Fig. 4.


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Fig. 4. Transient performance following a fault near generator 1 of 80 ms duration. Ratingand power output of generator 2 reduced to 70% nominal values.

B. Eigenvalue analysis

Generator 2 as a Synchronous generator with AVR control only

The loci of the eigenvalues that dictate the dominant oscillation mode of the system arepresented in Fig. 5 for the case where generator 2 has AVR excitation control only.

Fig. 5. Dominant eigenvalue loci when generator 2 is a synchronous generator with AVRcontrol.

The system is dynamically unstable for every generator capacity considered. The imaginaryparts of the eigenvalues indicate that the system suffers from an oscillatory instability having


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a frequency of oscillation of approximately 4 rad/s. It can be seen that as the capacity ofgenerator 2 is increased the network becomes increasingly unstable with the dominanteigenvalue being shifted further into the right half plane.

Generator 2 as a synchronous generator with AVR +PSS control

The introduction of the Power System Stabiliser significantly improves the system dynamicstability and for generator capacity factors of f2 =1 and f2 =2/3 the system is dynamicallystable as shown in Fig. 6.

Fig. 6. Dominant eigenvalue loci when generator 2 is a synchronous generator with AVRplus PSS control.

5.2Generator 2 as a FSIG-based wind farmIn this case the introduction of bulk wind power generation is considered for the northernScotland network. It is assumed that all the generation is from Fixed Speed InductionGenerator (FSIG) based wind farms. The same ratings and nominal power levels are

employed as for the purely synchronous generator case i.e.:


A. Time response studies

The responses of Fig. 7, Fig. 8 and Fig. 9 clearly demonstrate that whilst an FSIG cansignificantly contribute to network damping it is reliant on the rest of the system to maintainthe voltage levels needed for it to remain functional following network faults.

Fig. 7 presents responses for the case where the fault clearance time is 35 ms, anddemonstrates the significant damping contribution that a FSIG can provide. It can be seen


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that when generator 2 is an FSIG, the power oscillations of generator 3 decay more quicklythan they do when generator 2 is a synchronous generator with Power System Stabilisercontrol.

Fig. 7. Transient performance following a fault near generator 1 of 35 ms duration.

However, if the fault clearance time is increased to 40 ms it can be seen in Fig. 8 that, due tothe collapse of the FSIG terminal voltage, the power output of the FSIG is drasticallyreduced causing machine runaway. Despite this, the system retains transient stability, dueto generator 3 increasing its power output via governor control to make up for the loss ofgeneration from the FSIG. The system response can be seen to be very oscillatory butsynchronous generators 1 and 3 remain in synchronism.

Fig. 8. Transient performance following a fault near generator 1 of 40 ms duration.

Reducing the rating and power delivered from generator 2 to 50% of its nominal valueenables the system to withstand a fault near generator 1 of duration 80 ms without voltagecollapse (Fig. 9). The output power of generator 2 recovers following fault clearance andrelatively well-damped post fault transient performance is achieved. However, as thenominal power output level of generator 1 remains unchanged, the reduction in the powergeneration from the FSIG results in reduced power transmission to the England/Walesnetwork.


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Fig. 9. Transient performance following a fault near generator 1 of 80 ms duration. Ratingand power output of generator 2 reduced to 50% nominal value.


In the FSIG case, as the capacity factor f2 is increased the dominant eigenvalues are shiftedto the left of the complex plane (Fig. 10). An FSIG naturally contributes positively tonetwork damping and as the generator capacity increases so does the magnitude of itsdamping contribution to the network. For the capacity factors of f2 =1 and f2 =2/3 theoverall system is seen to be dynamically stable with the dominant eigenvalue lying in the lefthalf plane. At the lower values of f2 =1/3 and f2 =1/10, the eigenvalues lie in the right halfplane indicating dynamic instability.

Fig. 10. Dominant eigenvalue loci when generator 2 is a FSIG.

The system can be made dynamically stable by introducing a PSS on generator 1. Hencealthough a power system stabiliser contribution would be required from the rest of thesystem during the initial build up of wind generation, it would not be required at later stageswhen the higher wind generation capacity levels are reached.


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5.3Generator 2 as a DFIG-based wind farm with PVdq controlA. Time response studies

Again the introduction of bulk wind power generation is considered for the northern

Scotland network. In this case it is assumed that all the generation is from Doubly FedInduction Generator based wind farms with PVdq control. The same ratings and nominalpower levels are employed as previously i.e.:


The responses of Fig. 11 indicate that when generator 2 is a DFIG based wind farm withPVdq controller, the system can withstand a fault clearance time of 80 ms without the DFIGsuffering from runaway or the network suffering from loss of synchronism. Thus thenetwork transient stability when generator 2 is a DFIG is significantly better than that whenit is a synchronous generator. In addition, the responses indicate that the DFIG also

contributes to network damping. The decay rate of the power oscillations of generator 3 isseen to be faster than that obtained when generator 2 is a synchronous generator with PSScontrol. The major difference lies in the frequency of oscillation involved, with a highernatural frequency being evident in the DFIG case. With the PVdq control scheme, the formof control adopted leads to interaction between the power and voltage control loops andresults in significant oscillations in the DFIG terminal voltage following fault clearance.

Fig. 11. Transient performance following a fault near generator 1 of 80 ms duration. DFIGwith PVdq control.


The positive contribution of the DFIG with PVdq control to network damping, indicated inthe time response study, is confirmed by the eigenvalue analysis (Fig. 12). As the DFIGcapacity factor, f2, increases, the level of damping contribution increases and this shifts thedominant eigenvalues further to the left in the complex plane. For the higher value of f2 =1,the network is dynamically stable. Comparison of the eigenvalues corresponding to the FSIGand DFIG (with PVdq control) cases, the damping in the FSIG case is slightly greater.


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As before, dynamic stability can be achieved for lower values of f2 by introducing a PSS ongenerator 1. As for the FSIG case, although a power system stabiliser contribution would berequired from the rest of the system during the initial build up of wind generation it wouldnot be required at later stages when the higher wind generation capacity levels are reached.

Fig. 12. Dominant eigenvalue loci when generator 2 is a DFIG with PVdq control.

5.4Generator 2 as a DFIG-based wind farm with FMAC controlAgain the introduction of bulk wind power generation is considered for the northernScotland network. In this case it is assumed that all the generation of the northern Scotlandnetwork is by wind farms based on Doubly Fed Induction Generators (DFIGs) with thenewly developed FMAC control scheme. This scheme provides lower interaction controlthan that of the PVdq scheme and provides a control capability that enables a wind farm tocontribute more positively to network damping and voltage support.

The same ratings and nominal power levels are employed as previously i.e.:


A. Time responses analysis

The responses of Fig. 13 show that the DFIG based wind farm with the basic FMAC controlcan readily accommodate a fault clearance time of duration 80 ms. It can be seen that thesystem damping is better than in any of the cases previously considered. In addition, verygood post fault recovery of the DFIG terminal voltage is provided and unlike the PVdqcontrol case, the voltage response is practically non-oscillatory.

Real part (damping)

Imaginarypart(frequencyofoscillation)


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Fig. 13. Transient performance following a fault near generator 1 of 80 ms duration. DFIGwith basic FMAC control.

Generator 2 a DFIG with FMAC basic control plus PSS auxiliary loop

The FMAC control scheme lends itself readily to the accommodation of auxiliary loops forthe provision of specific control contributions to network support. In the study of concern, anauxiliary loop that provides the wind farm with a Power System Stabiliser (PSS) facility isadded. The network operating conditions are identical to those of the previous section.

Fig. 14. Transient performance following a fault near generator 1 of 80 ms duration. DFIGwith FMAC basic control plus PSS auxiliary loop.

Fig. 14 shows that with the PSS auxiliary loop included, the FMAC scheme provides theDFIG with a much superior contribution to network damping following the fault. Theoscillations in the power outputs of synchronous generators 1 and 3 are eliminated within 4seconds. It should also be pointed out that the increase in system damping provided by theauxiliary PSS loop is not gained at the expense of a poorer voltage control, which is still very


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fast and practically non-oscillatory. This is in contrast to the situation of a PSS on asynchronous generator where, as the AVR voltage control and the PSS control bothmanipulate the same control variable, namely the generator field voltage, any increase indamping due to PSS action is invariably at the expense of the quality of the voltage control.The responses of this section clearly demonstrate the importance of DFIG control to theprovision of voltage control and system damping in wind farm operation.


The eigenvalue loci for the DFIG with the basic FMAC control scheme as the capacity factorf2 is increased are shown in Fig. 15. The positive contribution to network damping indicatedin the time response study, is confirmed by the eigenvalue analysis. As the DFIG capacityfactor, f2, increases, the level of damping that it contributes to the network also increases andthis shifts the dominant eigenvalues further to the left in the complex plane. For values off2 = 1/3 and above, the eigenvalues lie in the left half of the complex plane, so thatdynamically stable network operation is achieved for smaller levels of wind farm generation

than in the previous cases where generator 2 is an FSIG or a DFIG with PVdq control.

Fig. 15. Dominant eigenvalues when generator 2 is a DFIG with FMAC basic control.

When the PSS auxiliary loop is added to the basic FMAC scheme, the damping is increasedsignificantly (Fig. 16). Again, the larger the generation capacity factor, f2, the greater theshift towards the left in the complex plane.

Real part (damping)

Imaginarypart(frequencyofoscillation)


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Fig. 16. Dominant eigenvalues when generator 2 is a DFIG with FMAC basic control plusauxiliary PSS loop.

In Fig. 16 the dominant eigenvalue, that which most influences the power and angletransients in the time domain has an oscillation frequency of approximately 5 rad/s, and isinfluenced significantly by the DFIG and its controller. The second eigenvalue loci shown in

Fig. 16, with an oscillation frequency of approximately 6 rad/s, has high damping associatedwith it for all the conditions considered. Although this eigenvalue also influences the powerand angle responses of the generators, it plays a smaller role in the power and angleresponses than the other eigenvalue shown.

Since the dominant eigenvalue lies in the right half complex plane for very low values ofgeneration capacity factor f2, a power system stabiliser contribution would be required fromthe rest of the system during the initial build up of the wind generation capacity. Again thisprovision could be dispensed with at later stages when the higher wind generation capacitylevels are reached.

6. IPSA time response studiesSimulation studies were also carried out using IPSA with the purpose of demonstrating thatthe contributions of FSIGs and DFIGs to network performance indicated from theSIMULINK model are also shown when using a separate and independent simulationpackage.

The same network as that of the generic model was implemented on IPSA. However, due tothe restrictive time frame available for the work, in place of the comprehensive models usedto represent the turbine-generator controllers adopted in the SIMULINK model, simplifiedmodels provided as default representations on IPSA were employed instead. The purpose of


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Page 22 of 34

the studies was therefore, not that of detailed comparison of the responses of one simulationpackage against another, but rather a demonstration that alternative and independent sourcesproduce the same fundamental dynamic contributions to overall network performance.

6.1Generator 2 represents a synchronous generatorIn the IPSA implementation the dynamic stability was achieved, not by introducing a PSS ongenerator 2, but by

1. using constant mechanical power for generators 1 and 2 to eliminate the negativedamping introduced by governor control.

2. employing very low transient gains for the AVRs of generators 1,2 and 3. Thisserves to reduce the negative damping contributions of the AVR voltage feedbackloops.

Fig. 17shows the generators time responses obtained in IPSA for the case when generator 2represents a synchronous generator and a fault is applied near generator 1 with a clearance

time of 80 ms. It can be seen that the system possesses low damping and that Generators 1and 2 oscillate in unison against the main system represented by generator 3. Again, as forthe SIMULINK case, with the full capacity generation (2,400MW) for generator 2, thesystem failed to regain synchronism following a fault of 80 ms. The responses of Fig. 17 arefor the case where the power capacity of generator 2 is reduced to the 70% value (1,560MW).

Gr aph 1: BUSBAR VOLTAGE - PU

1. 0 2. 0 3. 0 4. 0 5. 0 6. 0 7. 0 8. 0 9. 0 10. 0

0. 5

1. 0

0. 0

Bus1 Bus2

Graph 2: SM ANGLE - degrees

1. 0 2. 0 3. 0 4. 0 5. 0 6. 0 7. 0 8. 0 9. 0 10. 0

- 90

- 45

45

90

0. 0

Bus1 Bus2

Graph 3: SM SLIP - PU

1. 0 2. 0 3. 0 4. 0 5. 0 6. 0 7. 0 8. 0 9. 0 10. 0

-0. 020

-0. 010

0.010

0.020

0. 0

Bus1 Bus2

Graph 4: SM POWER ( P) - MW

1. 0 2. 0 3. 0 4. 0 5. 0 6. 0 7. 0 8. 0 9. 0 10. 0

500

1000

1500

2000

2500

3000

3500

4000

0. 0

Bus1 Bus2

Title: nassernet with synchgen IPSA 22DC 01 F eb 2005 12:41:39

nassernet with synchgen

Fig. 17. Generator transient performance following a fault near generator 1 of 80 msduration. Generator 2 represents a synchronous generator.


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Page 23 of 34

6.2Generator 2 represents a FSIGThe case was also considered where generator 2 is an FSIG but maintaining the samemodels, controllers and data for generators 1 and 3 as in the previous case.

As in the SIMULINK case, when the full capacity value of generator 2 (2,240MW) is used, afault duration time of 80ms causes voltage and power collapse and machine runaway forgenerator 2. Reducing the capacity of generator 2 to 50% of the full capacity level (1,120MW) enables the responses of Fig. 18 and 19 to be achieved.

The benefits that an FSIG brings to network damping can be seen, with damping many timesgreater than that in the case where only synchronous generation is involved being provided.

nassernet with fsigGr aph 1: BUSBAR VOLTAGE - PU

1. 0 2. 0 3. 0 4. 0 5. 0 6. 0 7. 0 8. 0 9. 0 10. 0

0. 5

1. 0

0. 0

Bus1 Bus3


1. 0 2. 0 3. 0 4. 0 5. 0 6. 0 7. 0 8. 0 9. 0 10. 0

- 90

- 45

45

90

0. 0

Bus1


1. 0 2. 0 3. 0 4. 0 5. 0 6. 0 7. 0 8. 0 9. 0 10. 0

-0. 050

-0. 040

-0. 030

-0. 020

-0. 010

0.010

0.020

0.030

0.040

0. 0

Bus1 Bus3


1. 0 2. 0 3. 0 4. 0 5. 0 6. 0 7. 0 8. 0 9. 0 10. 0

5000

10000

15000

20000

25000

0. 0

Bus1 Bus3

Title: nassernet with fsig IPSA 22DC 01 F eb 2005 13:17:47

Fig. 18. Transient performance for the case when generator 2 represents a FSIG. A fault isapplied near generator 1 with 80 ms duration. Synchronous generator 1 responses.


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Page 24 of 34

nassernet with fsigGr aph 1: BUSBAR VOLTAGE - PU

1. 0 2. 0 3. 0 4. 0 5. 0 6. 0 7. 0 8. 0 9. 0 10. 0

0. 5

1. 0

0. 0

Bus2

Gr aph 2 : I M SLI P - %1. 0 2. 0 3. 0 4. 0 5. 0 6. 0 7. 0 8. 0 9. 0 10. 0

- 2 . 5

- 2 . 0

- 1 . 5

- 1 . 0

- 0 . 5

-6E -70. 0

Bus2

Graph 3: I M POWER ( P) - MW1. 0 2. 0 3. 0 4. 0 5. 0 6. 0 7. 0 8. 0 9. 0 10. 0

- 2000

- 1800

- 1600

- 1400

- 1200

- 1000

- 800

- 600

- 400

- 200

0. 0

Bus2

Graph 4: I M TERM. CURR. - PU

1. 0 2. 0 3. 0 4. 0 5. 0 6. 0 7. 0 8. 0 9. 0 10. 0

0. 5

1. 0

1. 5

2. 0

2. 5

3. 0

0. 0

Bus2

Title: nassernet with fsig IPSA 22DC 01 F eb 2005 14:03:18

Fig. 19. Transient performance for the case when generator 2 represents a FSIG. A fault isapplied near generator 1 with 80 ms duration. FSIG responses.

6.3Generator 2 represents a DFIG with PVdq controlStudies were also carried out for the case where generator 2 is a DFIG with PVqd control.

With the DFIG, a fault of duration 80 ms with the full power capacity of generator 2 (2,240MW) does not cause post fault operation problems as Figs 19 and 20 show.

Again, the introduction of the DFIG significantly improves network damping over thatwhen generator 2 is a synchronous generator. The network damping level is similar to thatwith the FSIG. However, in the FSIG case the machine size was half that used in the DFIGcase. Consequently the FSIG contribution to system damping in terms of machine size isrelatively much greater than that of the DFIG.

The IPSA studies showed the same basic characteristics and contributions to networkperformance of FSIGs and DFIGs as indicated by the SIMULINK studies namely that

1. FSIGs are vulnerable to network faults, but contribute significantly to networkdamping

2. DFIG with PVdq control have better fault performance characteristics thansynchronous generators and also contribute positively to system damping.Although the damping contribution is less than that provided by a FSIG.


25/34


Page 25 of 34

nassernet with dfigGraph 1: BUSBAR VOLTAGE - PU

1. 0 2. 0 3. 0 4. 0 5. 0 6. 0 7. 0 8. 0 9. 0 10. 0

0. 5

1. 0

0. 0

Bus1 Bus3


1. 0 2. 0 3. 0 4. 0 5. 0 6. 0 7. 0 8. 0 9. 0 10. 0

- 90

- 45

45

90

0. 0

Bus1


1. 0 2. 0 3. 0 4. 0 5. 0 6. 0 7. 0 8. 0 9. 0 10. 0

-0 . 050

-0 . 040

-0 . 030

-0 . 020

-0 . 010

0.010

0.020

0.030

0.040

0. 0

Bus1 Bus3


1. 0 2. 0 3. 0 4. 0 5. 0 6. 0 7. 0 8. 0 9. 0 10. 0

5000

10000

15000

20000

25000

0. 0

Bus1 Bus3

Title: nassernet with dfig IPSA 22DC 01 F eb 2005 14:25:26

Fig. 20. Transient performance for the case when generator 2 represents a FSIG. A fault isapplied near generator 1 with 80 ms duration. Synchronous generator 1 responses.

nassernet with dfigGraph 1: BUSBAR VOLTAGE - PU

1. 0 2. 0 3. 0 4. 0 5. 0 6. 0 7. 0 8. 0 9. 0 10. 0

0. 5

1. 0

0. 0

Bus2

Graph 2 : I M SLIP - %1. 0 2. 0 3. 0 4. 0 5. 0 6. 0 7. 0 8. 0 9. 0 10. 0

-2 5. 0

-2 0. 0

-1 5. 0

-1 0. 0

- 5 . 0

0. 0

Bus2

Graph 3: I M POWER ( P) - MW1. 0 2. 0 3. 0 4. 0 5. 0 6. 0 7. 0 8. 0 9. 0 10. 0

- 4000

- 3500

- 3000

- 2500

- 2000

- 1500

- 1000

- 500

0. 0

Bus2

Graph 4: IM TERM. CURR. - PU

1. 0 2. 0 3. 0 4. 0 5. 0 6. 0 7. 0 8. 0 9. 0 10. 0

0. 5

1. 0

1. 5

2. 0

2. 5

3. 0

3. 5

4. 0

0. 0

Bus2

Title: nassernet with dfig IPSA 22DC 01 F eb 2005 14:21:58

Fig. 21. Transient performance for the case when generator 2 represents a DFIG with PVdqcontrol. A fault is applied near generator 1 with 80 ms duration. DFIG responses.


26/34


Page 26 of 34

7. General conclusionsDependent on the following assumptions made in the modelling, namely:

1. The converters are sufficiently robust to cater for all the demands of the DFIG

controller during transient operation.2. The simplified model used for the converter and its crowbar protection provides an

adequate representation of behaviour for the situations studied.3. The DFIG 3rdorder model, that ignores stator dynamics and was chosen for its

compatibility with the models normally used for conventional synchronousgenerators in power system analysis packages, adequately represents dynamicbehaviour for the situations studied.

4. The model representing the shaft dynamics of the turbine/generator system thatignores torsional oscillations is appropriate.

5. The numerous generators of wind farm generation can be represented coherently as asingle generator.

The studies on the simple generic network model indicate that

i) FSIG based wind farms can contribute significantly to network damping, but arevulnerable to network faults. Reductions in network voltage due to system faultscan result in a collapse of both the terminal voltage and power output of the FSIGand consequent machine runaway and tripping.

ii) DFIG based wind farms using the PVdq control scheme can contribute positivelyto system damping, although to a lesser extent than FSIGs.

iii) A DFIG based wind farm is capable of providing a superior transientperformance to that of a conventional synchronous generator following a systemfault.

iv) DFIG based wind farms using the FMAC control scheme have the capability ofstrongly contributing to system damping, particularly when the auxiliary PSSloop is employed. It is also capable of providing superior performance, in termsof both voltage recovery and system damping compared with that of the PVdqcontrol, following system faults.

v) The results using the FMAC control scheme demonstrate the importance of DFIGcontrol in providing good operating performance and network support.

vi) The results generally indicate that in terms of the expansion of renewable energyin mixed generation networks, wind generation based entirely on FSIG basedwind farms would make the network vulnerable to system faults, would restrictgeneration capacity and pose operational problems.

vii)The control flexibility of DFIG based wind farms can enable wind generation to

contribute positively to network operation in terms of voltage recovery followingfaults and improved system damping. This is particularly true when the FMACcontrol scheme is employed.

viii)The IPSA results demonstrate wind farm dynamic characteristics andcontributions to network performance fundamentally the same as those given bythe generic network model. This provides further confidence in the use of thegeneric model in the prediction of the basic dynamic interactions in mixedgeneration systems and the general conclusions drawn in this report.


27/34


Page 27 of 34

8. Appendix8.1FSIG 3rd order mathematical model

The FSIG 3rd

order model equations are provide in Table 1.

Table 1: FSIG 3rdorder model.

ds s ds qs dv R i X i e= + +

qs s qs ds qv R i X i e= +

( )( ) ( )

2 2

1ds d ds s q qs

s

i e v R e v XR X

= + +

( )( ) ( ) '

2 '2

1qs q qs s d ds

s

i e v R e v XR X

= +

( )'1d d qs s qo

de e X X i sedt T

= +

( )'1q

q ds s do

dee X X i se

dt T = +

s md qr

rr

Le

L

= ; s mq dr

rr

Le

L

=

( )1

r m e

dT T

dt J = ; e d ds q qsT e i e i= +

r ms

r m

X XX X

X X = +

+; s mX X X= +

r mrro

r r

L LLT

R R

+= =

8.2DFIG 3rd order mathematical modelThe 3rdorder model equations are given in Table 2

Table 2: DFIG 3rdorder model.

ds s ds qs dv R i X i e= + +

qs s qs ds qv R i X i e= +

( )( ) ( )

2 2

1ds d ds s q qs

s

i e v R e v XR X

= + +

( )( ) ( ) '

2 '2

1qs q qs s d ds

s

i e v R e v XR X

= +

( )'1d m

d qs s q s qro rr

de Le X X i se v

dt T L = +

( )'1q mq ds s d s dro rr

de Le X X i se v

dt T L = + +


28/34


Page 28 of 34

s md qr

rr

Le

L

= ; s mq dr

rr

Le

L

=

( )1

r m e

dT T

dt J = ; e d ds q qsT e i e i= +

r m

sr m

X X

X X X X = + + ; s mX X X= +

r mrro

r r

L LLT

R R

+= =

8.3Synchronous generator 6th order mathematical modelThe synchronous generator is represented in the generic network model by a 6th ordermodel given by Equations (2) - (11).

( ) ( )( )

( )21 d d

q fd q d d d do kddo d d

X Xd dE E E X X i T

dt T dtX X

= +

(2)

( ) ( )1

kd q kd d a ddo

dE X X i

dt T =

(3)

d a d dq d q kd d d

d a d a

X X X XE E X i

X X X X

= = +

(4)

( ) ( ) ( ) ( )21 q q

d d q q q qo kqqo

q a

X Xd d

E E X X i Tdt T dtX X

= +

(5)

( ) ( ) ( )1

kq d q a q kqqo

dE X X i

dt T =

(6)

( )q a q qd q d kq q qq a q a

X X X XE E X i

X X X X

= = + +

(7)

( ) ( )1

2m e

dP P

dt H = (8)

( ) 2

d

fdt =

(9)

;d q d d q d q qE X i E X i = + = + (10)

2 2

e d d q q

e q d d q

t d q

P e i e i

Q E i E i

E E E

= +

=

= +

(11)


29/34


Page 29 of 34

8.4Schematic block diagram of the synchronous generator excitation controllerA simplified block diagram of the control system designed for the synchronousmachine is illustrated in Fig. 22. The control system comprises the AutomaticVoltage Regulator (AVR) and Power System Stabiliser (PSS).

1

p

e

K

sT+1

11w

w

sT

sT+

+

1K

errmxV

errmnV

3

4

1

1

sT

sT

+

+Anti-

winduplogic

mxR

mnR 5

1

1 sT+

1

s

m2LIK m1LIK

+

eP

+

-

_t ref V

1

1 vtsT+

tV

AVR

PSS

1

1c

d

sT

sT

+

+

1

1a

b

sT

sT

+

+2

21w

w

sT

sT+

1

1 prsT+

1L

1L

2L

2L

1

2

1

1

sT

sT

+

+

-

1

2

1

1

f

f

sT

sT

+

+

1

1

f

g

sT

sT

+

+ 1

fbk

ct

K

sT+

+bcuK

mxE

mnE

cnvK

trmV

commX

fdI

fdVerrmxV

errmnV

Fig. 22. Synchronous generator excitation controller.

8.5Machine models parametersGenerator G1 (Synchronous generator - Hunterston)

The dynamics of the synchronous generator are represented by a 6th order model. The

model takes into account the dynamics of the stator, field, and damper windings. Thegenerator rotor is represented by a field winding with a single damper winding on thed axis and two damper windings on the q axis. The parameters used in the initial

studies are shown in Table 3.

Table 3. Synchronous generator parameters (Generator G1).Parameter Value

( )0 0d qT T 6.0857 (1.653)

0dT 0.0526

0qT 0.3538


30/34


Page 30 of 34

InertiaH 3.84

Speed DampingD 0.0

dX 2.13

qX 2.07

( )d qX X 0.308 (0.906)

( )d qX X 0.234

1X 0.190

Saturation (1.0) 0.150

Saturation (1.2) 0.7025

Excitation control system parameters of Generator 1

Table 4 shows the excitation control system parameters used in the initial studies.

Table 4. AVR Settings (Generator G1).Parameter Value Parameter Value

1K 250 mnV 0.0

1T 0.3 mxV 40.0

2T 6.0 mnE -0.788

3T 0.4 mxE 0.966

4T 1.4 comnX 0.1273

5T 0.015 LIMK 166.0

bcuK 3.78 vtT 0.013

iK 0.001 ctT 0.025cnvK 9.275 1fT 1.3

fbkK 0.87 2fT 0.6

fT 0.13 errmnV -1.0

gT 1.4 errmxV 1.0

mnR -6.0 lim1K 10.0

mxR 40.0

Power System Stabiliser parameters

Table 5 shows the Power System Stabiliser parameters used in the initial studies.

Table 5. AVR PSS Settings (Generator G1).Parameter Value

pK 5.1

prT 0.01

1wT 5.0

eT 0.02

2wT 5.0


31/34


Page 31 of 34

3wT 5.0

aT 1.32

bT 1.96

cT 0.49

dT 2.85

1L 0.32

2L 0.1

Steam turbine plus governor (Generator G1)

Fig. 23 illustrates the block diagram of the steam turbine and governor controlscheme model implemented in Simulink for the case when Generator 1 is driven by asteam turbine. Table 6 shows the steam turbine and governor parameters used in theinitial studies.

Fig. 23. Steam turbine and governor control scheme model.

Table 6. Steam turbine and governor parameters (Generator G1).Parameter Value

Droop gain (equivalent 4% droop) Kds1=25Governor filter time constant Tfs1=0.05 sActuator time constant Tas1=0.15 sHigh-pressure cylinder time constant Thp1=0.3 sReheater time constant Tr1=6 sIntermediate-pressure cylinder time constant Tip1=0.35 sLow-pressure cylinder time constant Tlp1=0.4 s

Proportion of total power from high-pressure cylinder Khp1=0.3Proportion of total power from intermediate -pressure cylinder Kip1=0.3Proportion of total power from low-pressure cylinder Klp1=0.4Inertia constant Hs1=3.84 s

Generator G3 - main system (synchronous generator)

Generator 3 is a steam turbine driven synchronous generator. 7 shows the parametersused for synchronous generator G3 in the initial studies.


32/34


Page 32 of 34

Table 7. Synchronous generator parameters (Generator G3-main system).Parameter ValueSynchronous reactance d-axis X3d=2.0Synchronous reactance q-axis X3q=1.9Transient reactance d-axis X3d1=0.35Transient time constant d-axis T3d1=5 sInertia constant H3=4 s

AVR parameters (Generator G3 - main system)

Fig. 24 illustrates the block diagram of the excitation control system implemented inSimulink for the synchronous generator G3. The parameters used in the initial studiesare displayed in Table 8.

Fig. 24. Generator G3 excitation control system.

Table 8. AVR parameters (Generator G3 - main system).Parameter ValueAVR gain K3a=250Time constants of phase-lag compensator T3a=5

T3b=1.5Exciter time constant T3A=0.025

Steam turbine and governor (Generator G3)

Fig. presents the block diagram of Generator G3 steam turbine and governorimplemented in Simulink. The parameters used in the initial studies for Generator G3steam turbine and governor are shown in Table 9.


33/34


Page 33 of 34

Fig. 25. Generator G3 steam turbine with governor.

Table 7. Steam turbine and governor parameter (Generator G3 - main system).Parameter ValueDroop gain (equivalent 4% droop) K3d=25Governor actuator time constant T3g=0.2High-pressure cylinder time constant T3hp=0.25Reheater time constant T3r=6Proportion of total power output from high-pressurecylinder

K3hp=0.3

Induction Generator Parameters (Generator G2)

Generator 2 can represent a wind farm employing either fixed-speed or doubly-fedinduction generators. Table 10 shows the parameters of the induction generator usedin the initial studies.

Table 10. Induction generator model parameters.Parameter Value

Stator resistance Rs =0.00488 (PU)Rotor resistance Rr =0.00549 (PU)Stator reactance Xls =0.09241 (PU)Rotor reactance Xlr =0.09955 (PU)

Magnetising reactance Xlm =3.95279 (PU)Inertia H =3.5 s

When generator 2 is a synchronous generator all parameters and controllers are identical tothose listed for Generator G1.

8.6Network parametersX11 =0.05 PU X1 =X11+X12X12 =0.01 PUX21 =0.05714 PU X2 =X21+X22X22 =0.1333 PUX3 =0.2 PUBase MVA =1000


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9. Bibliography[1] NATIONAL GRID TRANSCO: Appendix 1, Extracts from the Grid Code

Connection Conditions, www.nationalgrid.com, June 2004.[2] EKANAYAKE, J. B., HOLDSWORTH, L., WU, X., and JENKINS, N.:

"Dynamic modelling of doubly fed induction generator wind turbines," IEEETrans. on Power Systems, 2003, 18, (2), pp. 803-809.

[3] ANAYA-LARA, O. HUGHES, M. and JENKINS, N.: Generic network modelfor wind farm control scheme design and performance assessment, Proceedingsof the EWEC 2005 (European Wind Energy Conference), London, UK, 2005.

[4] SLOOTWEG, J. G. and KLING, W. L.: Modelling and analysing impacts ofwind power on transient stability of power systems, Wind Engineering, 25, (6),pp. 3-20, 2001.

[5] KUNDUR, P.: "Power systems stability and control," McGraw-Hill, 1994.[6] SLOOTWEG, J . G.: Wind Power: Modelling and Impact on Power System

Dynamics, PhD Thesis, Delft University of Technology, 2003.[7] HAGSTROM, E., NORHEIM, I. and UHLEN, K.: Large Scale Wind PowerIntegration in Norway and Effect on Damping in the Nordic Grid, Proceedingsof the Nordic Power Conference, 2004, Chalmers, Sweden, 2004.

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