Contribution of Variable-speed Wind Farms

8/6/2019 Contribution of Variable-speed Wind Farms

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Contribution of variable-speed wind farms to

damping of power system oscillations

Pablo LedesmaUniversidad Carlos III de Madrid

28911 Leganes, Madrid, Spain

Email: [email protected]

Carlos GallardoUniversidad Carlos III de Madrid

28911 Leganes, Madrid, Spain

Email: [email protected]

AbstractThis paper shows a variable speed windmill controlsystem intended to damp inter-area power system oscillations.The proposed control is evaluated performing several simulationson a modified version of the 39 buses New England power system,which includes several wind farms. The simulations representa three-phase shortcircuit, and the damping control system isapplied with different gains. Inter-area oscillations and windenergy production graphics are shown and discussed. A modalanalysis is performed on the inter-area active power flow in order

to evaluate numerically the effect of the control system.

I. INTRODUCTION

Wind power production has been increasing during the

last two decades in several European countries, mainly in

Denmark, Germany and Spain, while there are plans to install

a significant amount of wind power in several other countries,

such as Great Britain. As a result of the demands on reducing

polluting emissions, wind energy targets for the incoming

years are ambitious, and include large scale offshore wind

farms.

The increase of wind energy production leads to the sub-

stitution of a significant amount of conventional generation,particularly when load is low and wind speed is high. In

this cases, the power system dynamic behavior after a se-

vere perturbation may be different from the expected, and

Transmission System Operators may face situations which are

different from the usual ones during the previous decades. On

one hand, this has risen concern about the effect of the wind

farms on several aspects of system operation, and particularly

on the electromechanical oscillations after a fault. On the other

hand, the evolution of wind turbine technology during the last

years offers new possibilities, which may be used to maintain,

or even improve, power system stability [1].

Some of the efforts made to use wind turbine technology to

improve power system performance, are oriented to contributeto voltage stability [2]. Others are oriented to make the

dynamic characteristics of the wind farm similar to that of

a conventional power plant [3], [4]. This paper proposes

a wind turbine active power control system, which is not

intended to reproduce the behaviour of conventional generation

plants. The purpose of this control is the damping of the

power system electromechanical oscillations, and specially the

inter-area oscillations. This objective is interesting for power

systems such as the transmission grid in the Spanish Peninsula,

K

GeneratorQref = 0

Pwpss

gridPw

f

Pref

Fig. 1. Proposed control system.

which has a large amount of wind power generation, and a

relatively weak connection with the rest of the UCTE power

system across the Pyrenees.

This paper contains three main parts: the first one describes

the wind turbine control, the second one shows and discusses

several simulations performed on the 39-buses test power

system, and the third one performs a modal analysis on the

inter-area oscillations obtained in the simulations.

II. DESCRIPTION OF THE CONTROL SYSTEM

The proposed control is based on the ability of variablespeed wind turbines to perform an active power control which

is decoupled from reactive power control and from rotor

mechanical speed. Usually, active power reference is provided

by a wind turbine speed control loop, and it is used to track

the operation point at which maximum power is absorbed from

the wind or to limit the blades speed during high winds.

In order to damp power system oscillations, a control

signal proportional to the deviation of the frequency is added

to the active power reference. This is depicted in Fig. 1,

where f is the deviation of the frequency in per unit,Pdamp is the proposed control signal, Pw is the active powerreference as provided by the turbine usual control, and Pref

is the new active power reference. This control is intendedto be performed in windmills with voltage-dip ride-through

capability, and will actuate only during transient oscillations.

During normal operation, when frequency deviation is null,

the control signal Pdamp will be zero.

Reactive power reference Qref is supposed to be zero, thisis, wind turbine is operating at unity power factor. Although

different control strategies may be used here, there is no reason

to suppose that they would have major effects on the results

of the study.


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81

10

7

2

3

4 5

9

6

W

W

W

W

W W

W

W

W

W

W

W

Fig. 2. Modified 39 buses New England power system.

It should also be noted that this control technique uses onlylocal variables, so that it does not involve any telecommuni-

cation issue.

III. SIMULATIONS IN PSS/E

Some simulations have been performed, using the PSS/E

software tool, in order to evaluate the performance of the

proposed control. Variable speed wind farms are modelled

as devices which inject into the power system the active and

reactive power provided as a reference by the control system,

independently of the voltage at the connection point. The total

amount of output current is limited to 110% of the nominal

current, in order to protect the semiconductors in the windmill.So, if voltage decreases significantly (during a fault) wind

power production may also decrease.

Electromagnetic transients in the generators has been ne-

glected, as it is a usual practice in transient stability simula-

tions. Active and reactive power control loops have also been

neglected, because their time scale is very small compared to

that of electromechanical oscillations. A user model has been

developed in PSS/E to accomplish with this characteristics.

A. Base case

The proposed control system has been applied to the 39

buses New England test power system, which has been modi-fied to include wind power installations. A total of three wind

farms have been simulated, connected at three points of the

transmission grid as shown in fig. 2. Each of these wind

farms may represent an aggregation of several wind farms

connected to the same point. Each of the wind farms produce

250 MW. As total production is 6225 MW, this results in a

12% of wind power penetration. The production of generator

10, which represents another area, has been reduced in order

to accommodate wind power.

CHNL

#1

0:

[P

OWR

39

[

1.0000]

[1

]]

20.000

1

0.00

TIME (SECONDS)

0.01.0000

2.00003.0000

4.00005.0000

6.00007.0000

8.00009.0000

10.000

Fig. 3. Inter-area power flow, no damping from wind farms.

CHNL

#11

:

[P

OWR

14

[

1.0000]

[1

]]

3.0000

0.0

CHNL

#12

:

[P

OWR

16

[

1.0000]

[1

]]

3.0000

0.0

CHNL

#1

3:

[P

OWR

17

[

1.0000]

[1

]]

3.0000

0.0

TIME (SECONDS)

0.0

1.0000

2.0000

3.0000

4.0000

5.0000

6.0000

7.0000

8.0000

9.0000

10.000

Fig. 4. Wind farms output power, no damping from wind farms.

B. Simulation results with no damping control

A three-phase shortcircuit at the bus shown in fig. 2 has been

simulated, with a duration of 200 ms. The topology of the grid

before and after the fault are the same. Fig. 3 shows the active

power flow between the New England power system and the

area represented by generator 10. It can be seen a 0.5 Hz,

poorly damped inter-area oscillation.

Fig. 4 shows the active power production of the three wind

farms. This production remains basically constant, because the

active power reference at the windfarms is independent from

the grid conditions. Only during, and immediately after the

fault, active power output decreases as a result of voltage de-

cay, because of current limitation in the electronic converters.

C. Simulation results with damping control

Figs. 5 to 7 show the active power flow between both areas

using different control gains. The control loop gain, which is

depicted as K in fig. 1, is 16, 64 and 256 respectively. It can


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CHNL

#

10:

[P

OWR

39

[

1.0000]

[1

]]

20.000

1

0.00

TIME (SECONDS)

0.01.0000

2.00003.0000

4.00005.0000

6.00007.0000

8.00009.0000

10.000

Fig. 5. Inter-area power flow, wind farm damping control with gain=16.

CHNL

#

10:

[P

OWR

39

[

1.0000]

[1

]]

20.000

1

0.00

TIME (SECONDS)

0.0

1.0000

2.0000

3.0000

4.0000

5.0000

6.0000

7.0000

8.0000

9.0000

10.000


CHNL

#1

0:

[P

OWR

39

[

1.0000]

[1

]]

20.000

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TIME (SECONDS)

0.0

1.0000

2.0000

3.0000

4.0000

5.0000

6.0000

7.0000

8.0000

9.0000

10.000


CHNL

#11

:

[P

OWR

14

[

1.0000]

[1

]]

3.0000

0.0

CHNL

#12

:

[P

OWR

16

[

1.0000]

[1

]]

3.0000

0.0

CHNL

#1

3:

[P

OWR

17

[

1.0000]

[1

]]

3.0000

0.0

TIME (SECONDS)

0.01.0000

2.00003.0000

4.00005.0000

6.00007.0000

8.00009.0000

10.000

Fig. 8. Wind farms output power, wind farm damping control with gain=16.

CHNL

#

11

:

[P

OWR

14

[

1.0000]

[1

]]

3.0000

0.0

CHNL

#

12

:

[P

OWR

16

[

1.0000]

[1

]]

3.0000

0.0

CHNL

#

13:

[P

OWR

17

[

1.0000]

[1

]]

3.0000

0.0

TIME (SECONDS)

0.0

1.0000

2.0000

3.0000

4.0000

5.0000

6.0000

7.0000

8.0000

9.0000

10.000

Fig. 9. Wind farms output power, wind farm damping control with gain=64.

CHNL

#11

:

[P

OWR

14

[

1.0000]

[1

]]

4.0000

0.0

CHNL

#12

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[P

OWR

16

[

1.0000]

[1

]]

4.0000

0.0

CHNL

#1

3:

[P

OWR

17

[

1.0000]

[1

]]

4.0000

0.0

TIME (SECONDS)

0.0

1.0000

2.0000

3.0000

4.0000

5.0000

6.0000

7.0000

8.0000

9.0000

10.000

Fig. 10. Wind farms output power, wind farm damping control withgain=256.


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TABLE IMODAL ANALYSIS

Gain (p.u.) Interval (s) Error (%) Frequency (Hz) Damping

0 2-12 0.14 0.507 0.0858 2-12 0.34 0.509 0.090

16 2-12 0.27 0.510 0.09332 2-12 0.27 0.510 0.10164 2-12 0.57 0.509 0.122

128 2-12 0.61 0.499 0.159256 2-12 0.98 0.501 0.375

be seen how inter-area power oscillations are damped by the

proposed control.

Figs. 8 to 10 show the active power production of the three

wind farms under the same circumstances. It can be seen at

fig. 8, which corresponds to a gain K=16, how wind power

production is modified after the fault in order to damp power

system oscillations. The variation in the power production is

not very large compared to the total production, and could be

performed by modern wind turbines.

Fig. 9, which corresponds to a gain K=64, shows larger

oscillations in wind power production, which represent anadditional effort to the wind turbine control. However, it can

be seen that, immediately after the fault, the wind power

production always decrease, which will result in a slight

increase in rotor speed and, consecuently, in the kinetic energy

stored in the rotor and the blades. Thus, the windmill will be

able to use this kinetic energy to perform the required active

power control.

Finally, fig. 10 shows wind power oscillations with a gain

K=256. The damping of electromechanical oscillations is very

energic, as shown in fig. 7, but at the price of larger active

power excursions at the wind farms. In this case, wind power

decays to zero during, approximately, 700 ms.

IV. MODAL ANALYSIS

A modal analysis has been performed on the inter-area

active power oscillation, in order to obtain a better evaluation

of the performance of the damping control. Table I shows

the results obtained evaluating the eigenvalues using the least

square approximation method provided by the PSS/E software

tool. The first column shows the gain K, as depicted in

fig. 1. The second column shows the time interval used to

perform the modal analysis. Column number three sohws the

percentage error, and is an indicator of the accuracy of the

analysis. Column number four shows the frequency of the

main component, which is the only one examinated here, and

is always around 0.5 Hz. The last column shows the dampingfactor, calculated as = /

2 + 2, were and are

the real and imaginary part of the corresponding eigenvalue.

It can be seen, examinating the last column, how the

damping of the inter-area oscillations is increased by the

actuation of the wind farm control. Fig. 11 shows the resuls

in a graphic format. Damping factor increase is approximately

linear when control gain increases from 0 to 128 p.u.. At

higher values of gain K, this relation is not linear any more.

The reason is that the limitation in windmills output power,

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0 50 100 150 200 250 300

Damping control gain K (p.u.)

Dampingfactor

Fig. 11. Effect of the control gain on the damping factor.

which cannot be lower than zero and cannot be higher than

the maximum provided by the current limiter, results in strong

non-linearities.

V. CONCLUSION

It has been shown how wind farms can damp inter-area

power system oscillations by means of a simple control loop.

This control loop has several advantages:

It is simple. Simpler, for example, than power system

stabilizers (PSS).

It can be implemented by modern windmills without

additional costs.

It uses only local variables (frequency at the connection

point).

Among the negative aspects, it should be noted that this

control represents a different behaviour to that of conventional

generation plants, so that somehow it forces a certain change

in the view of power system operation. Also, several issues

should be studied in more detail, among then:

A small-signal linear analysis, in order to know the effect

of the control on the critical eigenvalues.

The performance in larger systems with much higher

inertia and smaller frequency deviations.

The effect on primary frequency control.

ACKNOWLEDGMENT

The authors would like to thank Francisco Rodrguez-

Bobada for his guidance through the modal analysis procedure.

They thank also Red Electrica de Espana for the financialsupport for this work.

REFERENCES

[1] Z. Chen, Issues of Connecting Wind Farms into Power Systems, 2005IEEE/PES Transmission and Distribution Conference & Exhibition: Asiaand Pacific, Dalian, China.

[2] R. D. Fernndez, R. J. Mantz, P. E. Battaiotto, Contribution of wind farmsto the network stability, IEEE PES 2006 General Meeting, Montreal.

[3] O. Anaya-Lara, F.M. Hughes, N. Jenkins and G. Strbac, Contribution ofDFIG-based wind farms to power system short-term frequency regulation,IEE Proc.-Gener. Transm. Distrib., Vol. 153, No. 2, March 2006.


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[4] O. Anaya-Lara, F.M. Hughes, N. Jenkins and G. Strbac, Provision ofa synchronising power characteristic on DFIG-based wind farms, IETGener. Transm. Distrib., Vol. 1, No. 1, January 2007.

Contribution of Variable-speed Wind Farms

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