evaluating connecting al-mukha new wind farm to yemen ... · evaluating connecting al-mukha new...

Evaluating Connecting Al-Mukha New Wind

Farm to Yemen Power System

Majid M. Al-Barashi1,2

, Doaa Khalil Ibrahim1, and Essam El-Din Abo El-Zahab

1

1Electrical Power and Machines Dept., Faculty of Engineering, Cairo University, Egypt

2Department of Electricity, Technical Industrial Institute, Dhamar, Yemen

Email: [email protected]

Abstract—This paper presents modeling and impact analysis

of Al-Mukha wind farm (MWF) on Yemen power system,

which is made of thermal power plants. In this paper, four

kinds of major components are modeled: a 60MW wind

farm, a transmission network, thermal power plants, and

the Yemen power system load. To analyze the impact of the

wind power generation to the Yemen power system,

simulations are carried out for two case studies by using the

DIgSILENT program. The first is the case of grid impact

studies: impact on thermal limits, voltage variations, and

system stability, in which an aggregated model of the wind

farm is used. The other is the dynamic performance of the

wind farm by analyzing low-voltage ride through LVRT,

harmonics and flicker impact on the basis of the detailed

wind farm layout with 30 wind turbines (WTs) arranged in

four stands and the external grid of 2175MVA short-circuit

capacity. The simulation results show that the loading of

most lines and voltage variations are slightly reduced. In

addition, there is no harmful effect on the system stability

and also the wind farm is capable to ride through the grid

fault. Finally, it is shown that the wind farm contributes

voltage and current harmonics higher than the permissible

limits while the flicker levels are far below any critical

values.

Index Terms—DIgSILENT PowerFactory, doubly fed

induction generator, grid-connected wind farm, impact of

wind power generation, power quality

I. INTRODUCTION

In recent years, the wind power generation has become

a very attractive utilization of renewable energy because

it is now possible to improve the capability of capturing

wind energy with the development of advanced power

electronics technology. It has been a trend in wind power

generation to build a grid-connected wind farm. The

location for a wind farm is usually determined by the

wind speed, and therefore the wind farms are

concentrated in specific areas [1].

The doubly fed induction generator (DFIG) is used in

popular wind turbine (WT) systems because of its various

advantages such as high energy efficiency, variable speed,

reduced mechanical stress on turbine and power

electronics convertor having low rating and cost [2].

The Yemeni Government has initiated the renewable

energy strategy and action plan in which different sources

Manuscript received October 31, 2014; revised May 14, 2015.

of renewable energy have been investigated [3]. The aim

of government policy on renewable energy is to optimize

the use of energy from domestic sources, increase the

share of renewable energy in electricity generation to 15-

20% by 2025, and promote sustainable development of

the electricity sector [4].

Yemen has a long coastline and high altitudes with an

estimated 4.1 hours of full-load wind per day [4].

According to an assessment of wind potential in Al-

Mukha by Egyptian experts, this region alone could

produce 1.8GW of power and the average annual wind

speed is 7.4m/s, which is the main reason why the

Yemeni government decided to construct a wind farm of

60MW capacity in this area. Total wind power potential

is estimated to be 34GW. The technical potential was

estimated at 14,200MW providing about 42,300GWh of

electricity per year [4].

However, there are some constraints on connection of

wind power stations to the Yemen power system due to

the wind velocity distribution and weak power generation.

First of all, total power generation capacity in Yemen

including Mareb-2 power plant, which will operate in

2015, will be by only about 1740MW, and the proposed

capacity of the wind farm is 60MW [5], [6]. The capacity

of wind farm is assessed to be acceptable provided that

any harmful effects on Yemen power system stability will

not be occurred, since the increased penetration level of

wind power produces negative impact on the stability of

existing power system [2]. Therefore, it is recommended

that the impact of wind power generation to the Yemen

power grid will be carefully analyzed before connecting

wind farms to the grid.

The objectives of the presented paper are to analyze

the impact of the proposed Al-Mukha wind farm on the

Yemen power system and to evaluate how the power

quality parameters will be affected. For these purposes,

simulations for both the grid and the wind farm are

carried out using the trusted software DIgSILENT

PowerFactory. Two types of simulations are performed.

One is the case for the studies of network impact (effect

on the thermal limits, voltage changes, and the stability of

the system), which uses a combined model of the wind

farm. The other is the dynamic performance (low voltage

ride through LVRT) and power quality (harmonics and

flicker) for the analysis of the wind farm integration

based on a detailed model of the wind farm with 30WTs

arrayed in four groups.

International Journal of Electrical Energy, Vol. 3, No. 2, June 2015

©2015 International Journal of Electrical Energy 57doi: 10.12720/ijoee.3.2.57-67

http://mail.ym.163.com/jy3/compose/main.jsp?sid=T0oAq798U6c4h2UDe6W9GLF1Qq43iHMZ&to=majid-barashi%40eng1.cu.edu.eg

This paper is organized as follows: the characteristics of Yemen power system and Al-Mukha wind farm (MWF)

project are presented in Section II, modeling and

simulation of Yemen system and wind turbine are given in Section III, the discussion of the results are presented

in Section IV, and conclusions are finally drawn in Section V.

II. CHARACTERISTICS OF YEMEN POWER SYSTEM AND

MWF PROJECT

A. Power System in Yemen

The power system in Yemen has many kinds of power

system components, including thermal power plants, transmission and distribution networks. The

probability of electric faults is high and will be increased

as the renewable energy sources are added, debasing power system stability. Electricity in Yemen depends

mainly on oil power stations. The total installed capacity of Yemen in 2012 is 1288MW. The Yemeni population

has the lowest access to electricity in the region, with

only 54% having access. In 2009, power shortages in the country reached 250MW [4]. To address these shortages,

many projects, including MWF, are planned to be implemented in the near future. The power plants

generate electrical power at different voltage levels which are 10.5kV, 11kV, 13.8kV, and 15kV and then the

voltage levels are boosted to the transmission voltages

levels of 230kV and 400kV. The medium voltage level of 33kV is used to transmit the electricity from the

substations to the demand locations. The distribution network uses the 11kV to transmit the electricity to the

distribution transformers. The nominal frequency for the

grid is 50Hz.

B. Al-Mukha Wind Farm Project

The assessment of wind potential in Al-Mukha has

shown that this region alone could produce 1.8GW of power [4]. MWF project was initiated with the objectives

of demonstrating the financial feasibility of wind power by implementing the first wind power development

project in Yemen. The target capacity of 60MW will be

met through introducing 30 of 2MW wind turbines generators (WTGs) that will be located according to a

favorable scenario indicated in Fig. 1 [3].

III. MODELING OF YEMEN POWER SYSTEM AND WIND

TURBINES

To verify the feasibility of integration of wind energy

with the electric grid, computer simulations have been

carried out with a 2MW WTGs Gamesa G-90 DFIG

system, the transmission network, and thermal power

plants including diesel engines, steam and gas turbine

generators; and, Yemen power grid load are also modeled

in the simulation.

A. Wind Turbine Modeling

DIgSILENT provides a comprehensive library of

models of electrical components in power systems. The

library includes models of e.g. generators, motors,

controllers, dynamic loads and various passive network

elements (e.g. lines, transformers, static loads and shunts).

Therefore, in the present work, the grid model and the

electrical components of the WT model are included as

standard components in the existing library. The models

of the wind speed, the mechanics, aerodynamics and the

control systems of WTs are written in the dynamic

simulation language (DSL) of DIgSILENT [7]. There is

no wind model included in the DFIG model found in

DIgSILENT library. This model was modified where a

wind model was connected to the wind speed input of the

original model. The implemented wind model is a

measurement file (ElmFile). The measurement file is

used for reading data (wind time series) from a file during

calculations [8]. The wind time series is generated by the

TurbSim software based on the spectral energy

distribution of the wind and a superposed noise signal [9].

In a 0.05 second time step the so gained wind speed is

averaged over the whole rotor area, which takes

turbulence and tower shadow into account. Fig. 2 shows

the modeling scheme of the WTGs in the DIgSILENT

program.

Figure 1. The proposed scenario of WTG in MWF project site [3]


©2015 International Journal of Electrical Energy 58

Figure 2. Complete scheme of the doubly-fed induction machine wind generator

The validation of the developed model in DIgSILENT

is performed for fault free operation at different operating

conditions. The rated wind speed is 11 m/s and the rated

generator speed (𝜔𝑔𝑒𝑛𝑛𝑜𝑚) is 1485rpm. Fig. 3 illustrates the

simulation operation at 8.5m/s mean value turbulent wind

speed with turbulence intensity of 10%. This operation

corresponds to the power optimization with variable

generator speed reference. The speed controller has to be

strong and fast in order to seek the maximum power. The

speed reference corresponds to the generator speed for

which the measured power is optimal. As expected for

this wind speed range, the pitch angle is not active.

Notice that the fast oscillations in the wind speed are

completely filtered out from the electrical power. The

validation is also performed when a turbulent wind speed

with a mean value of 18m/s and a turbulence intensity of

10% is used. This simulation case corresponds to the

power limitation strategy. The power limitation controller

changes the pitch angle to keep the rated power, while the

speed controller prevents the generator speed from

becoming too high.

B. Modeling of Yemen Power System

Fig. 4 shows the DIgSILENT model of Yemen

power system. There are four types of components:

thermal power plants, the proposed MWF, the

transmission network, and the loads. The supply of

electric power is from thermal power plants composed

of 439MW diesel engines, 510MW steam turbine

generation systems, and 791MW gas turbine generation

systems including 452MW of Mareb-2 power plant, and

MWF supplying power up to the maximum of 60MW.

In case of studying grid impact (impact on thermal

limits, voltage variations, and system stability), an

aggregated model of the wind farm is typically used.

Wind speed diversity within the wind farm is initially not

considered and these studies are based on the assumption

that up to the registered capacity of 60MW will

potentially be generated at the grid connection point.

When encountering problems, such as LVRT and power

quality studies, a more detailed assessment considering

wind speed diversity will be carried out. In this case, the

WTGs are arranged in four strands; two strands are

connecting seven WTs each and the other two strands are

connecting eight WTs for each one, while the power

system is modeled as external grid with 2175MVA short-

circuit capacity.

Generic DFIG-Turbine_resync:

Electronic

Mechanics

Wind*ElmFile

TurbineElmDsl*

SlowFrequM..ElmPhi*

OverFreq P..ElmDsl*

SpeedRefElmDsl*

Ir_ctrl*

Speed-CtrlElmDsl*

Shaf tElmDsl*

Pitch Cont..ElmDsl*

Current Measurement*

CompensationElmCom

udc

Vac_genStaVmea*

Vac_busStaVmea*

Theta meas..ElmPhi*

ProtectionElmPro*

MPTElmMpt*

PQ ControlElmPQ*

Ptot

DFIGElmAsm*

PQ_totStaPqmea

Generic DFIG-Turbine_resync:

vw

Pref

ird_ref;ir..

dud_sy nch;duq_sy nchu;ugr;ugi

Fmeas

pref _in

usr;usi

ird;i

rq

pctrl;qctrl

Irot

speed

id;iq

beta

pt

pw

speed_re

f

psir_r;psi..

cosphiref;..

cosp

hiu

;si..

cosphim;si..

DIg

SIL

EN

T



Figure 3. Simulation with turbulent wind speed of 8.5m/s mean speed and turbulence intensity of 10%

Figure 4. Yemen network scheme

60.00048.00036.00024.00012.0000.0000 [s]

12.25

11.00

9.75

8.50

7.25

6.00

Turbine: wind_speed in m/s

60.00048.00036.00024.00012.0000.0000 [s]

1.23

1.18

1.13

1.08

1.03

0.98

Speed-Controller: speed_ref in p.u.

Speed-Controller: speed in p.u.

60.00048.00036.00024.00012.0000.0000 [s]

0.80

0.60

0.40

0.20

0.00

-0.20

Pitch Control: beta in deg

60.00048.00036.00024.00012.0000.0000 [s]

2.20

1.90

1.60

1.30

1.00

0.70

DFIG_2MW(1): Total Active Power in MW

SubPlot(1)

Date: 10/23/2014

Annex: /2

DIg

SIL

EN

T

Voltage Levels

400. kV

132. kV

33. kV

15. kV

13.8 kV

11. kV

0.69 kV

0.48 kV

LV

MWF/S/S

MWF(1)/S/S

Mukha/P/S

Amran+Shebam+..

Khormakser/P/S

Mansorah/P/S

Block80/S/S

Khormaksar(1)/P/S

Hali/P/S

Ja'ar(1)/S/S

Ja'ar(2)/P/S

Hodieda/S/S

Hodieda(1)/S/S

Hiswa/S/S

Taiz(2)/P/..

Bajil(1)/S/S

Jarahi(1)/S/..

Mukha(1)/S/S

Rahida+Turbah..

Habilain+Dalea/S/S

Mareb(4)/P..

Mareb/S/S

Bani Alhareth(1)/S/..

Bani Alhareth/S/..

Dhahban/P/S

Hizyaz(1)/P/S

Sana'a(Aser)/B...

Ras Katheb(1)/S/S

Sana'a(1)/S/S

Dhamar/B.S.P

Barh(1)/S/S

Dahban/B.S.P

Hizyaz/S/S

Taiz(1)/S/..

Hiswa(1)/P/S

Taiz/B.S.P

Ras Katheb/P/S

Bajil/B.S.P

Rahida/S/S

Shinaz/S/S

Amran/S/S

N.Doukaim/S/S

Habilain/S/S

G~

DFIG_2MWIG2MW

SG~

Mukha(3)Steam(1)

2-W

Tr(

2)

Muk

ha(1

)2

-W T

r(2

)M

uk

ha(1

)

MWF-MukhaT L

MWF-MukhaT L

Trf

Trf

..T

rfT

rf..

2-W

Tr(

31)

MW

F(1

)2

-W T

r(3

1)

MW

F(1

)

Mukha-BarhT.L.

Mukha-BarhT.L.

Barh-TaizT.L.

Barh-TaizT.L.J

ara

hi-M

uk

ha

T.L

.J

ara

hi-M

uk

ha

T.L

.

2-W

Tr(

24)

Ba

rh2

-W T

r(2

4)

Ba

rh

Taiz

-Ibb

T.L

.T

aiz

-Ibb

T.L

.

Khormaksar-Block80T L.

Khormaksar-Block80T L.

Bani Alhareth-HizyazT.L.

Bani Alhareth-HizyazT.L.

Hiswa-Ja'arT.L.

Hiswa-Ja'arT.L.

3-W Tr(3)Ja'ar(3)

3-W Tr(3)Ja'ar(3)

3-W Tr(3)Ja'ar(3)

2-W

Tr(

19)

Jara

hi

2-W

Tr(

19)

Jara

hi

2-W

Tr(

26)

Ibb

2-W

Tr(

26)

Ibb

Ibb-D

ha

ma

rT

.L.

Ibb-D

ha

ma

rT

.L.

Mansora-KhormaksarT L.

Mansora-KhormaksarT L.

Aden+Lahj(1)

Mansora-Block80T L.

Mansora-Block80T L.

Khormaksar

SG~

Khormaksar(2)Diesel(2)

SG~


SG~


2-W

Tr(

11)

Kh

orm

aks

ar(

3)

2-W

Tr(

11)

Kh

orm

aks

ar(

3)

Shinaz-KhormaksarT L.

Shinaz-KhormaksarT L.

Hali(1)

SG~

AlhaliDiesel(13)

SG~

Alhali(1)Diesel(14)

2-W

Tr(

3)

His

wa

(3)

2-W

Tr(

3)

His

wa

(3)

Aden+Lahj(2)

2-W

Tr(

9)

Man

sora

(2)

2-W

Tr(

9)

Man

sora

(2)

2-W

Tr(

10)

Man

sora

(3)

2-W

Tr(

10)

Man

sora

(3)

SG~

Mansora(1)Diesel(1)

SG~

MansoraDiesel

Hiswa-MansoraT L.

Hiswa-MansoraT L.

Mansora-ShinazT L.

Mansora-ShinazT L.

Ja'ar(5)

2-W

Tr(

15)

Ja'a

r(2)

2-W

Tr(

15)

Ja'a

r(2)

SG~

Ja'ar(4)Diesel(16)

SG~

Ja'ar(3)Diesel(15)

Hodieda(2)

2-W

Tr(

20)

Ho

die

da

h2

-W T

r(2

0)

Ho

die

da

h

Ho

die

da

-Ra

s K

ath

eb

T.L

.H

odie

da

-Ra

s K

ath

eb

T.L

.

2-W

Tr(

14)

Ha

li(2

)2

-W T

r(1

4)

Ha

li(2

)

SG~

Hiswa(3)Steam(3)

2-W

Tr(

4)

His

wa

(2)

2-W

Tr(

4)

His

wa

(2)

2-W

Tr(

5)

Dh

ah

ban

(2)

2-W

Tr(

5)

Dh

ah

ban

(2)

2-W

Tr(

7)

Hiz

ya

z(2

)2

-W T

r(7

)H

izy

az(2

)

Ras Katheb(2)

Rahida+Turbah(1)

Mareb(1)

Mareb-Bani AlharethT.L

Mareb-Bani AlharethT.L

SG~

Mareb(3)Gas

2-W

Tr

Mare

b(1

)2

-W T

rM

are

b(1

)

2-W

Tr(

30)

Mare

b(2

)2

-W T

r(3

0)

Mare

b(2

)

Aser(1)Aser

2-W

Tr(

29)

Ba

ni

Alh

are

th2

-W T

r(2

9)

Ba

ni

Alh

are

th

Mareb(2)

Sana'a(2)

Sana'a(3)

Dhamar-AserT.L.

Dhamar-AserT.L.

2-W

Tr(

21)

Ba

jil2

-W T

r(2

1)

Ba

jil

2-W

Tr(

16)

Ra

s K

ath

eb

2-W

Tr(

16)

Ra

s K

ath

eb

SG~

Ras Katheb(3)Steam

2-W

Tr(

1)

Ra

s K

ath

eb

(1)

2-W

Tr(

1)

Ra

s K

ath

eb

(1)

Taiz(3)

SG~

Taiz(5)Diesel(10)

SG~

Taiz(6)Diesel(11)

SG~

Taiz(7)Diesel(12)

Sana'a

SG~

Sana'a(4)Diesel(7)

2-W

Tr(

12)

Sa

na

'a (

2)

2-W

Tr(

12)

Sa

na

'a (

2)

3-W TrHisa

3-W TrHisa

3-W TrHisa

Hiswa Pst-Hiswa S/ST L.

Hiswa Pst-Hiswa S/ST L.

2-W

Tr(

23)

Am

ran

2-W

Tr(

23)

Am

ran

Amran+Shebam+Hajah

Dh

ah

ban

-Am

ran

T.L

.D

hah

ban

-Am

ran

T.L

.

Aser-DhahbanT.L.

Aser-DhahbanT.L.

SG~

Hizyaz(3)Diesel(9)

SG~

Hizyaz(2)Diesel(8)

2-W

Tr(

8)

Hiz

ya

z(3

)2

-W T

r(8

)H

izy

az(3

)

2-W

Tr(

27)

Hiz

ya

z(4

)2

-W T

r(2

7)

Hiz

ya

z(4

)

SG~

Dhahban(2)Diesel(6)

2-W

Tr(

6)

Dh

ah

ban

(3)

2-W

Tr(

6)

Dh

ah

ban

(3)

Ras Katheb-BajilT.L.

Ras Katheb-BajilT.L.

Barh(2)

Dhamar-HizyazT.L.

Dhamar-HizyazT.L.

Bajil-DhamarT.L.

Bajil-DhamarT.L.

2-W

Tr(

13)

Taiz

(3)

2-W

Tr(

13)

Taiz

(3)

2-W

Tr(

25)

Taiz

(4)

2-W

Tr(

25)

Taiz

(4)

Taiz(4)

Rahida-N.DoukaimT.L.

Rahida-N.DoukaimT.L.

3-W Tr(2)Rahida

3-W Tr(2)Rahida

3-W Tr(2)Rahida

Taiz-RahidaT.L.

Taiz-RahidaT.L.

2-W

Tr(

18)

Sa

na

'a (

3)

2-W

Tr(

18)

Sa

na

'a (

3)

Hiz

ya

z-A

se

rT

.L.

Hiz

ya

z-A

se

rT

.L.

SG~

Dhahban(1)Diesel(5)

SG~

Hiswa(2)Steam(2)

Aser-AmranT.L.

Aser-AmranT.L.

Aden+Lahj

Habilain+Dalea(1)

N.D

ou

ka

im-H

isw

aT

.L.

N.D

ou

ka

im-H

isw

aT

.L.

N.Doukaim-HabilainT.L.

N.Doukaim-HabilainT.L.

3-W Tr(1)Habilain3-W Tr(1)Habilain3-W Tr(1)Habilain

Dhamar(2)

2-W

Tr(

22)

Dh

am

ar

2-W

Tr(

22)

Dh

am

ar

Ba

jil-J

ara

hi

T.L

.B

ajil-J

ara

hi

T.L

.

Jarahi(2)

Mukha(2)

2-W

Tr(

17)

Muk

ha(2

)2

-W T

r(1

7)

Muk

ha(2

)

Bajil+Almahit

Ibb(2)

2-W

Tr(

28)

Dh

ah

ban

(4)

2-W

Tr(

28)

Dh

ah

ban

(4)

Dhahban-Bani AlharethT.L.

Dhahban-Bani AlharethT.L.

DIg

SIL

EN

T



IV. SIMULATION RESULTS AND DISCUSSION

A. Impact on Thermal Limits and Voltage Variations

The load flow and contingency analysis studies allow

analyzing the impact of wind generation on thermal limits

and voltage variations during normal operations and

during contingencies. The load flow study cases were:

Peak load without MWF

Peak load with MWF

Minimum load without MWF

Minimum load with MWF

For quick assessment, the current in transmission lines

for peak load in case of without and with MWF are fully

compared in Fig. 5, while Fig. 6 depicts the current

comparison for minimum load case. Besides, Fig. 7

demonstrates the comparison of the voltage in the

substations for peak load case without and with MWF.

Fig. 8 demonstrates the comparison of the voltage in the

substations for minimum load case without and with

MWF respectively.

It can be concluded that when connecting MWF, the

current flows are redistributed in the lines and reduced in

most of the lines, where the maximum current is reduced

by 6.32% in the peak load case and 7.17% in the

minimum load case while the voltage in substation buses

slightly rises enhancing the lowest value (in Dhamar)

from 0.910 to 0.923pu in the peak load case.

From the results shown, it can be deduced that MWF

integration does not significantly affect the voltages and

currents performance along the network.

This section also contains the analysis of the power

system performance (in the peak load with MWF) in the

following contingencies:

Losing one of the lines of Mareb – Bani Alhareth.

Losing one of the lines of Al-Mukha – Barh.

The n-1 analysis based on load flow calculations of the

considered lines leads to the conclusion that there is a

thermal overload problem in the case that one of the

parallel circuits between Mareb and Bani Alhareth is out

of service.



Figure 5. Comparison of the current in transmission lines (peak load without and with MWF)

Figure 6. Comparison of the current in transmission lines (minimum load without and with MWF)

Figure 7. Comparison of the voltage in the substations (peak load without and with MWF)

Figure 8. Comparison of the voltage in the substations (minimum load without and with MWF)



B. Impact on the System Stability

The following cases were considered as transient

events:

Sudden fall of MWF (stop producing energy). 3-Phase short circuit in Al-Mukha substation (the

point of common coupling (PCC)).For these cases, the stability of voltage and frequency

were verified by the angles obtained for the power plants’ generators. These angles are represented below in Fig. 9 and Fig. 10. As shown, a stability status was reached after clearing the fault, which is assumed at 100ms.

According to these achieved results, the system is

capable to return to a stable state and MWF will not

weaken the transient stability of the system.

Figure 9. Generators relative power angle in degrees (sudden fall of MWF)

Figure 10. Generators relative power angle in degrees (3-phase short circuit in the PCC)

C. LVRT Capability of DFIG Based WTG

LVRT capability of the WTG is defined as the

capability of the generator to remain connected to the grid

under grid disturbances. In this study, three different

wind scenarios were used for the investigation of the

wind generator behavior as follows:

Strong wind conditions

Medium wind conditions

Low wind conditions

For different wind conditions, various faults are

applied to the grid. The following fault scenarios are

simulated at the PCC:

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Solid 3-phase short circuit with 150ms clearing

time (0% remaining voltage).

3-Phase short circuit with 150ms clearing time, 20%

remaining voltage.

3-Phase short circuit with 150ms clearing time, 80%

remaining voltage.

Solid 2-phase short circuit with 150ms clearing

time.

Fig. 11 shows the simulation results of a solid three-

phase fault in the PCC at high wind conditions. When the

fault was created at the HV bus at zero second, a voltage

dip of zero p.u occurs at HV bus and occurs at MV bus

with 0.1p.u. The rotor speed is increased from 1.2p.u. to

about 1.27p.u. With respect to the change in speed, there

is a variation in pitch angle between zero degree to 6.5

degrees. The current in the rotor is suddenly raised to

about 1.9 times the rated capacity of the rotor. The fault is

cleared at 150ms, at this moment; the voltage is rising to

its pre-fault level. The speed and also pitch angle are also

reduced after the clearance of fault. The value of rotor

current is also reduced after the fault. In post fault

conditions, the rotor current reached the value of about

0.8p.u.

As shown in Fig. 12, the active power generated by

DFIG before fault occurrence is about 2MW. When the

fault occurred, there is a reduction of power to zero value.

After the fault clearance, there is a slight increase in

power to 0.65MW there after it reached to zero value at

180ms then it gradually regained to its original value at

1.35s then there is a slight increase in power till 3.5s there

after it regained to its original value. The phase current of

the generator is also raised to about 3.5kA when the fault

was occurred; it came gradually, after decreasing to

0.63kA, to its original value after the clearance of the

fault.

The results show that the generators do not face

instability. Besides, at low or medium wind conditions,

i.e. at a low loading of the generators, no unstable

behavior was shown.

During the fault, the DFIG supports the voltage

stability by reactive current (reactive power) as shown in

Fig. 12. The voltage supporting properties allow the wind

farm to better ride-through network faults.

The results of the tested cases for the transient stability

are summarized in Table I.

TABLE I. TRANSIENT STABILITY RESULTS

Fault conditions Strong wind Medium wind Low wind

3ph short-circuit, 0% Stable stable stable



2ph short-circuit Stable stable stable

Figure 11. Voltages (at the PCC and at the MV bus), the generator speed, the rotor current, and the pitch angle during a solid three-phase fault for 150ms at high wind conditions

4.00833.18672.36501.54330.7217-0.1000 [s]

1.295

1.270

1.245

1.220

1.195

1.170

DFIG_2MW(1): Speed in p.u.

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Current Measurement: Irot in p.u.

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Pitch Control: beta in deg

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1.20

0.90

0.60

0.30

0.00

-0.30

PCC\Bus Bar(32): Positive-Sequence Voltage, Magnitude in p.u.

Cub_1/MV(1): Positive-Sequence Voltage, Magnitude in p.u.

Plot Wind Turbine 1

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Figure 12. Generator active power, phase current, reactive current, and reactive power during a solid three-phase fault for 150 ms at high wind conditions

D. Analysis of Power Quality Aspects:

1) Analysis of harmonic impact of wind turbines on the

grid:

[10], harmonic load-flows allow the calculation of

harmonic voltages or current based on the pre-defined

harmonic sources and grid characteristics. Also, the

software allows for the user-defined harmonic current

sources to be located at any bus-bar on the grid. In this

investigation the PMW converter has been defined as the

harmonic source, its harmonic current spectrum has also

been assumed to resemble that of the ideal (generic)

model given in DIgSILENT.

Various wind turbines may emit variable harmonic

spectra and their shapes (magnitudes) are dependent on

the characteristics and control of the wind turbine

converters used. In this case, the ideal spectrum which is

provided in the DIgSILENT manual was used and

modified to be IEC 61000 harmonic source with only

integer harmonics.

The harmonic load-flow was performed for a 60MW

DFIG wind farm. The monitoring was done at the PCC

and, Fig. 13 illustrates the harmonic distortion (HD). The

resultant total harmonic distortions (THD) are 18.8% and

6.61% of Irated for current and voltage total harmonic

distortion respectively.

The limits for HD and THD are IEC 61800-3 [11] and

IEEE 519 standards are used in DIgSILENT for current

and voltage harmonics respectively.

The current and voltage THD for the proposed wind

farm is much higher than the limits imposed by the

standards. Also the current and voltage HD of the 5th

, 7th

,

11th

, and 13th

harmonics were above the permissible

limits with a maximum current HD of 9.89% in the 11th

harmonic and a maximum voltage individual harmonic

content of 3.71% in the 7th

harmonic. In such a case, it is

needed to install filters to mitigate the distortions.

2) Analysis of flicker:

carried out according to IEC 61000-3-7 [12], and IEC

61400-21 [13]. The method requires the calculation of the

minimum short circuit level and impedance angle (ψk) at

the PCC.

Based on the impedance angle ψk

, the maximum

values for 𝐶(𝜓𝑘), 𝑘𝑓(𝜓𝑘), 𝑘𝑢(𝜓𝑘), 𝑁10, and 𝑁120 for the

relevant impedance angle at the PCC must be taken from

a wind turbine measurement sheet according to IEC

61400-21, where:

C(ψk) : Flicker coefficient as a function of the

network impedance angle.

kf(ψk): Flicker step-factor as a function of the


ku(ψk): Voltage change factor as a function of the


N10 , N120 Maximum number of switching

operations in a 10-minutes, and 120-minutes

period respectively.

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DFIG_2MW(1): Phase Current, Magnitude A in kA

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DFIG_2MW(1): Total Active Power in MW

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DFIG_2MW(1): Positive-Sequence Reactive Current in kA

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DFIG_2MW(1): Total Reactive Power in Mvar

Plot Wind Turbine 1(2)

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According to DIgSILENT technical reference manual

Flicker assessment for the wind farm is typically

Figure 13. Current and voltage HD at the PCC

These values together with the minimum fault level at

the PCC allow calculating:

Short-Term and long term flicker disturbance

factors ( 𝑃st_cont / 𝑃lt_cont ) during continuous

operation.

Short-Term and long term flicker disturbance

factors (𝑃st_sw/𝑃lt_sw) due to switching actions.

The resulting flicker levels are as follows:

Pst_cont = Pst_sw = 0.01,

Plt_cont = 0.04, and Plt_sw = 0.01.

The significance of the actual results is very limited

because the actual results will depend on the actual type

of turbines that will be installed. However, since the

calculated numbers are far below any critical values

(found in [12]), it can be assumed that flicker will not

cause any problem in the case of a 60MW at MWF

project.

V. CONCLUSION

Modeling and impact analysis of integrating Al-

Mukha wind farm to the Yemen power system, have been

performed using the DIgSILENT program.

The studies of load flow showed that the loading of

most lines and voltage variations are slightly changed.

Under the contingency situations, there is a thermal

overload issue of the overhead lines. Additional findings

from the transient stability studies indicate that MWF will

not weaken the system transient stability. The LVRT

study showed that after the fault is cleared, the wind

turbine generators recovered their voltage level almost to

its pre-fault voltage value. It is found that the proposed

wind farm contributed voltage and current THDs higher

than the permissible limits specified in the standards. This

would require a harmonic filter to be installed in order to

mitigate the harmonics. As for the flicker, the resulting

levels are far below any critical values so it can be

assumed that flicker will not cause any problem in the

studied case.

REFERENCES

[1] E.-H. Kim, J.-H. Kim, S.-H. Kim, and J. Choi, “Impact analysis of

wind farms in the Jeju Island power system,” IEEE Systems

Journal, vol. 6, no. 1, pp. 134-139, Mar. 2012.

[2] J. M. Aga and H. T. Jadhav, “Improving fault ride-through

capability of DFIG connected wind turbine system: A review,” in

Proc. IEEE International Conf. on Power, Energy and Control

(ICPEC), Sri Rangalatchum Dindigul, 2013, pp. 613-618.

[3] Al Mukha 60MW Wind Farm Project - Resettlement Policy

Framework, Ministry of Electricity and Energy, Yemen, May

2011.

[4] Reegle. (2012). Policy and regulatory overviews - Clean energy

information portal. [Online]. Available:

http://www.reegle.info/profiles/YE

[5] PEC High Voltage System (400/132/33/11KV), Public Electricity

Corporation (PEC), Yemen, Oct. 2011.

[6] Summary Table of Lines, Transformers and Generators Data,

Public Electricity Corporation, Yemen, 2012.

[7] A. D. Hansen, et al., Dynamic Wind Turbine Models in Power

System Simulation Tool DIgSILENT, 2nd ed., Roskilde, Denmark:

Risø National Laboratory, 2007, ch. 2.

[8] DIgSILENT PowerFactory - Measurement File, Technical

Reference Documentation, DIgSILENT GmbH, 2011.

1.06.00,” Technical Report, National Renewable Energy

Laboratory, Sep. 2012.

[10] DIgSILENT PowerFactory - Version 15.1 User Manual,

DIgSILENT GmbH, Dec. 2013.

[11] Å. Larsson, “The power quality of wind turbines,” Ph.D. thesis,

Dept. Elect. Eng., Chalmers Univ., Göteborg, Sweden, 2000.

5.00 7.00 11.0 13.0 17.0 19.0 23.0 25.0 29.0 31.0 35.0 37.0 41.0 43.0 47.0 49.0

5.00

4.00

3.00

2.00

1.00

0.00

Mukha\P/S: Voltage Harmonic Distortion in %

resultat harmonics

5.00 7.00 11.0 13.0 17.0 19.0 23.0 25.0 29.0 31.0 35.0 37.0 41.0 43.0 47.0 49.0

12.50

10.00

7.50

5.00

2.50

0.00

MWF-Mukha: Current Harmonic Distortion in %

resultant harmonicsHarmonic currents of wind farm at PCC

Voltage Harmonics of wind farm at PCC

IEEE Voltage Limits

IEC 61800-3 Curret Limits

DIgSILENT Wind Farm Example Distortion

Harmonics

Date: 9/30/2014

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[9] B. J. Jonkman and L. Kilcher, “TurbSim user’s guide: Version

http://www.reegle.info/profiles/YE

[12] Electromagnetic Compatibility (EMC) – Part 3: Limits – Section 7:

Assessment of Emission Limits for Fluctuating Loads in MV and

HV Power Systems, IEC 1000-3-7, Oct. 1996. [13] Wind Turbine Generator Systems - Part 21: Measurement and

Assessment of Power Quality Characteristics of Grid Connected

Wind Turbines, IEC 61400-21, Dec. 2001.

Majid M. Al-Barashi was born in Dhamar,

Yemen, on March 5, 1985. He received the

B.S. degree in Electrical Power Systems Engineering from University of Aleppo,

Aleppo, Syria, in 2009. He was a Lecturer in

Faculty of Medical, Engineering and Technological Sciences, Dhamar, Yemen,

from 2008 to 2009. From 2009 to 2012, he

was a Sales Support Engineer and Supervisor

of Legrand Showroom in MAM International

Corporation, Sana’a, Yemen. Since 2010, he has been a Member of the Teaching Staff of the Department of

Electricity, Technical Industrial Institute, Dhamar, Yemen. Presently, he

is pursuing for M.S. degree in Cairo University, Egypt. His current research interests include utilization of electrical power, power systems,

and wind power generation.

Doaa Khalil Ibrahim (IEEE M’06, SM'13) was born in Egypt in December 1973. She

received the M.Sc. and Ph.D. degrees in digital

protection from Cairo University, Egypt, in 2001 and 2005, respectively. From 1996 to

2005, she was a Demonstrator and Research

Assistant with Cairo University. In 2005, she became an Assistant Professor with Cairo

University. In 2011, she became an Associate

Professor with Cairo University. Since 2009, she has contributed to the Program of Continuous Improvement and Qualifying for Accreditation

in Higher Education in Egypt. Her research interests include digital

protection of power system as well as utilization and generation of electric power, distributed generation and renewable energy sources.

Essam EL-Din Abou EL-Zahab: received the BSc. and MSc. degrees in electrical power

and machines from Cairo University, Egypt, in

1970 and 1974, respectively. He received the PhD. degree in Electrical Power from Paul

Sabatier, Toulouse France, in 1979. Currently

he is a Professor in the department of electrical power and machines at Cairo University. His

research areas include protection system,

renewable energy, and power distribution. He is also the author or co-author of many referenced journal and

conference papers.



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