TELKOM
NIKA
, Vol. 11, No. 8, August 2013, pp. 44
3
3
~4
438
e-ISSN: 2087
-278X
4433
Re
cei
v
ed Fe
brua
ry 11, 20
13; Re
vised
Ma
y 13, 20
13
; Accepte
d
May 22, 20
13
Resear
ch on the Wind Power Penetration Limit in
Power System
Yang Zhang*
1
, Hongbo Z
h
ang
1
, Degui
Yao
2
, Qiang Li
2
1
North Chi
na U
n
iversit
y
of W
a
ter Resourc
e
s and El
ec
tric Po
w
e
r, Z
hengz
ho
u, Chin
a, tel: 1393
90
455
21
2
He Nan Electric Pow
e
r Research Institut
e, Zhen
gzh
ou, Chi
na, tel: 137
037
103
51
*Corres
p
o
ndi
n
g
author, e-ma
i
l
: 2865
54
472
@
qq.com
A
b
st
r
a
ct
An appro
a
ch
to calcul
ate the w
i
nd farm p
enet
rati
on ca
p
a
city base
d
o
n
chanc
e con
s
traine
d
progr
a
m
min
g
combi
n
in
g w
i
th transi
ent check
w
a
s pr
esente
d
. A novel
mo
del for pr
ogra
m
mi
ng p
e
n
e
tra
t
io
n
of w
i
nd farm
und
er in
deter
mi
nacy o
per
ati
ng
mod
e
w
a
s presente
d
. C
onstrai
nt cond
i
t
ion cons
isted
of
conve
n
tio
nal
g
ener
ator o
u
tput
li
mits, system
spin
nin
g
res
e
rv
e, trans
missi
on
lin
es cap
a
b
ilit
y, noda
l volt
ag
e,
system freq
ue
ncy etc, and g
enetic
a
l
gor
ith
m
bas
ed o
n
Monte Carl
o s
i
mulati
ng w
a
s used to solv
e the
problem
,
and the actu
al sample system
ver
i
fied the feasi
b
ility of
the
m
odel and
m
e
thod. Results for th
e
app
licati
on
of this a
ppr
oach
r
e
vea
l
ed
the
inf
l
ue
ncin
g fa
ctor
s of pe
netrati
o
n
of w
i
nd
far
m
consiste
d
of the
para
lle
l n
o
d
e
v
o
ltag
e, the
o
u
tput
var
i
atio
n r
ang
e
of w
i
nd
gen
eratin
g
s
e
t an
d
mean
w
i
nd s
p
e
ed
etc.
T
h
e
researc
h
resu
l
t
s have i
m
p
o
rtant practic
a
l s
i
gnific
anc
e, w
h
ich can
gui
de
the actual w
i
nd far
m
s in th
e
pla
nni
ng a
nd o
perati
on a
nalys
is of reality w
i
n
d
farm.
Ke
y
w
ords
: w
i
nd
pow
er p
e
n
e
tration, c
hanc
e constr
ain
ed
progr
a
m
min
g
,
mo
nte c
a
rlo s
i
mu
lati
ng, g
e
n
e
t
ic
alg
o
rith
m, tran
sient stabi
lity
Copy
right
©
2013 Un
ive
r
sita
s Ah
mad
Dah
l
an
. All rig
h
t
s r
ese
rved
.
1. Introduc
tion
With the
prop
ortion
of the
wind
po
we
r in
t
he p
o
we
r
sy
stem in
crea
si
ng, the im
pa
ct on the
system i
s
m
o
re a
nd m
o
re
promi
nent [1,
2]. The bi
g
chang
e of the
wind
sp
eed
may brin
g g
r
eatly
disturban
ce
o
n
the voltage
, frequen
cy a
nd po
we
r
an
gle of the sy
stem an
d the
grid sch
eduli
n
g
depa
rtment
s
often ma
ke
wind farms out
of op
eration
in case the
system lo
ss
stability in
seve
re
ca
se
s. Th
ere
f
ore, the
cap
a
city of
wind
po
we
r
p
enet
rating
into sy
stem be
com
e
s an
i
m
po
rtant
topic in the st
udy of wind p
o
we
r.
This pa
per
studied the ca
pacity of win
d
pow
e
r
pen
etrating into
system. The
dynamic
simulatio
n
method wa
s often use
d
to de
termine the
capa
city [3-8].
The first ste
p
is to set a value
based
on th
e
experi
e
n
c
e
and
ch
eck th
e sta
b
ility in
t
y
pical
ope
rati
on mo
de. T
h
e second
ste
p
is
to adjust th
e value until
the stability requi
reme
nt
s are sati
sfied. This m
e
thod is indi
rect
verification
a
nd the
comp
u
t
ation is inten
s
ive, th
e
r
e al
so so
me othe
r
o
peration condition
s are
not
con
s
id
ere
d
[9]. In recent
years, opti
m
izati
on m
e
thod was m
a
inly used in
the research. It
cal
c
ulate
d
th
e maximum
cap
a
city of th
e win
d
po
we
r in vario
u
s
constraint
con
d
ition, so th
e
full
rang
e of con
d
i
tions were
co
nsid
ere
d
[10-13].
Becau
s
e
of t
he
wind
sp
ee
d is
un
ce
rtain
and
ra
ndom
variation
amo
unt, the o
u
tp
ut of the
wind p
o
wer i
s
un
ce
rtain a
nd it may lea
d
s to the
cha
nge
s of the o
u
tput of
the convention
a
l u
n
it,
the syste
m
spinnin
g
re
se
rve,
the line p
o
we
r, no
de v
o
ltage
s an
d
t
he sy
stem freque
ncy. In t
h
is
pape
r, ch
an
ce con
s
traine
d
prog
rammi
n
g
[14] wa
s u
s
ed to d
eal
with the prob
lem. It made th
e
deci
s
io
n befo
r
e the ra
ndo
m amount su
ch a
s
win
d
speed a
nd loa
d
wa
s ob
se
rved as lo
ng a
s
the
establi
s
h
ed p
r
oba
bility bro
ught by the deci
s
ion
s
ma
d
e
by the constraint con
d
itio
n is highe
r than
the given val
ue. Du
e to th
e load
and
wi
nd spee
d
cha
nge at
any time, som
e
co
nstrai
nt condi
tions
may
not be satisfied
i
n
some
Indi
vidual
ci
rcumstances
even if
th
e probability
of
occurrence is
low an
d in this ca
se the int
egratin
g ca
pa
city we
obtain
ed is a small
e
r value, so t
he win
d
ene
rgy
can
not be
m
a
ximize used. If some constraint
s
were
not sati
sfied i
n
a lo
w probability, the wi
nd
power capa
ci
ty will be a larger value a
n
d
the wind en
e
r
gy coul
d be
made full use
of.
This p
ape
r
pre
s
ente
d
a
step-by-ste
p
method b
a
se
d
on co
mbining
th
e
cha
n
ce
con
s
trai
ned p
r
og
rammi
ng
and dyna
mic calib
ration,
the mathem
atical mo
del of
the wind p
o
w
er
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TELKOM
NIKA
Vol. 11, No
. 8, August 2013: 4433 –
4438
4434
integratio
n
ca
pacity was e
s
tabli
s
he
d. T
he dev
el
ope
d
geneti
c
al
go
rithm is ba
se
d on th
e Mo
nte
Carl
o sim
u
lati
on and o
b
tain
ed the de
sire
d results.
2. Rese
arch
Metho
d
There a
r
e th
ree
step
s for
solving t
he
wind po
we
r i
n
tegratio
n
cap
a
city. The fi
rst step i
s
the ca
pa
city optimizatio
n;
the se
co
nd step
is
th
e cutting
ma
chin
e optimizatio
n; the
third step
is
the tra
n
si
ent
che
c
k. In th
e
first
step
hi
g
her inte
g
r
atio
n capa
city va
lue
coul
d b
e
get in
case t
h
e
constrai
nt condition
was not satisf
ied in a lower
probability. In
the second step, cutting m
a
chi
n
e
to satisfy all t
he con
s
traint
s on
ce
co
nstraint co
ndition
wa
s not
satisfied [10], and
the optimization
goal i
s
th
e
wi
nd p
o
wer
wit
h
a m
a
ximum
loadi
ng
rate
after
cutting t
he ma
chi
n
e
s
, so
the
re
se
rving
wind tu
rbin
e
coul
d take lo
ad a
s
mu
ch
a
s
po
ssible. T
he effect of th
e two
step i
s
the probabilit
y of
wind
en
ergy i
n
tegratio
n
ca
pacity into
sy
stem
be
high
er, a
nd m
a
ximizing
the
u
s
e of
wind
en
e
r
gy
in case the constraint condition were not satisfi
ed. The third step is to check the stability
that
obtaine
d by the se
co
nd st
ep in a typical syst
em o
p
e
rating m
ode
to ensu
r
e the stea
dy an
d
transi
ent ope
ration are all
stable after the
wind po
we
r integratin
g into system.
2.1.
Mathem
atical
Model of
the Wind Turbine
The active po
wer
cha
r
a
c
teristics of the wind
turbin
e are expre
s
sed i
n
piecewi
s
e f
unctio
n
in the cal
c
ulat
ion, as sho
w
n
in formula (1
) belo
w
.
R
R
R
in
in
in
R
Ri
in
R
R
out
in
W
v
v
P
v
v
v
v
v
v
P
v
v
v
P
v
orv
v
v
P
3
3
3
3
3
3
0
(1)
V is the wi
nd
spe
ed at hu
b height; V
in
and V
out
are
wind spe
ed cut
in
and cut out;
V
R
is
the rated wi
n
d
spe
ed; P
R
is the rate
d po
wer.
Wind
spe
ed o
beys the Wei
bull Di
stributi
on, as sho
w
n
in formula (2
) belo
w
:
k
C
V
k
e
C
V
C
k
V
p
)
(
1
)
(
)
(
(2)
K is the
sh
a
pe facto
r
;
C refle
c
t the
size of the
a
nnual
averag
e win
d
spe
e
d
. Load
distrib
u
tion could take the norm
a
l distri
b
u
tion,
uniform
distributio
n o
r
other di
strib
u
tion types.
2.2. Mathem
atical Model
of the
Cap
a
c
i
t
y
Optimization
The
optimiza
t
ion obj
ective
is to
maxim
i
ze th
e in
stal
led
cap
a
city
of win
d
fa
rm
s. Th
e
con
s
trai
nts i
n
clud
e p
o
we
r f
l
ow
equ
ation
s
, the
co
nven
tional u
n
it out
put con
s
traint
s, tra
n
smi
s
si
on
cap
a
city of th
e line
po
we
r
con
s
trai
nts, n
ode volt
a
ge constraints,
rot
a
ting
reserve
con
s
trai
nts a
nd
system fre
q
u
ency con
s
trai
nts.
Constrai
nts of the flow equat
ion and conventional unit c
ontri
bution are the probability
wa
s sati
sfied
with pro
babili
ty 1; constrai
nts of
the tra
n
smi
ssi
on ca
pacity of the line po
wer, no
de
voltage, spin
ning reserve
and sy
stem freque
ncy a
r
e
satisfie
d with
a highe
r p
r
ob
ability less th
an
1. The
purpo
se i
s
to
exclu
de the
co
nditi
on that o
c
curren
ce
pro
babi
lity is very lo
w but limitin
g
the
integratio
n
ca
pacity of th
e
wind
farm
in
a large
r
exte
nt. The
ca
pa
city optimization math
emati
c
al
model is exp
r
essed a
s
follo
ws:
Ri
P
max
s
.t.
)
cos
sin
(
)
sin
cos
(
1
1
ij
ij
ij
ij
N
j
j
i
Li
Gi
Wi
ij
ij
ij
ij
N
j
j
i
Li
Gi
Wi
B
G
V
V
Q
Q
Q
B
G
V
V
P
P
P
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TELKOM
NIKA
e-ISSN:
2087
-278X
Re
sea
r
ch on
the Wind Po
wer Pe
netrati
on Lim
i
t in Po
wer S
ystem
(Yang Zha
ng)
4435
h
Gi
Gi
l
Gi
h
Gi
Gi
l
Gi
Q
Q
Q
P
P
P
(3)
2
1
h
l
l
l
l
h
l
l
l
l
Q
Q
Q
p
P
P
P
p
3
h
i
i
l
i
V
V
V
p
4
)
(
S
Gi
h
Gi
P
P
P
p
5
h
l
f
f
f
p
i,j repre
s
e
n
ts any node
re
spe
c
tively in formula
(3)
；
l
rep
r
e
s
ent
s a
n
y bran
ch
；
P
R
is the
wind turbine
rated po
wer;P
W
an
d Q
W
a
r
e
the active and rea
c
tive p
o
we
r of the wind turbine;
G
P
,
l
G
P
,
h
G
P
,
G
Q
,
l
G
Q
,
h
G
Q
are the
act
i
ve power, a
c
tive powe
r
lo
wer li
mits, a
c
tive powe
r
up
per limit ,
rea
c
tive po
wer, re
active l
o
we
r limit, re
active po
we
r
uppe
r limit of
conve
n
tional
units;
L
P
an
d
L
Q
are the
acti
ve and rea
c
tive load po
wer;
i
V
is the
voltage of n
ode i;
ij
G
,
ij
B
,
ij
are t
h
e
con
d
u
c
tan
c
e,
susce
p
tance
and voltage pha
se angl
e differen
c
e bet
wee
n
node
i
and
j
;
S
P
is the
spin
ning rese
rve of the system;
l
P
,
l
l
P
,
h
l
P
are the ctive powe
r
, active powe
r
lowe
r limit,
active
power u
ppe
r
limit of the lin
e
l
;
l
Q
,
l
l
Q
,
h
l
Q
are the
reactive p
o
we
r, rea
c
tive lo
wer limit, rea
c
tive
power u
ppe
r
limit of line
l
;
f
、
l
f
、
h
f
are the f
r
eque
ncy, freq
uen
cy lower l
i
mit and the
uppe
r
freque
ncy lim
it of the system.
5
1
~
are the probability values.
2.3. Optimization Ma
the
m
atical Mod
e
l of Cutting
Machine
Optimizatio
n
obje
c
tive
is maximizin
g
the
load ca
rrying
rate
of the
wind po
wer after
cutting ma
chi
ne.
The co
nstrain
t
s includ
e po
wer flo
w
equ
ations
, the co
nventional un
it
output constraints,
transmissio
n capa
city of the line po
we
r con
s
tr
aint
s, node voltag
e con
s
trai
nts, rotating re
se
rve
con
s
trai
nts a
nd
system
freque
ncy
co
n
s
traint
s. A
ll
t
he con
s
traints sho
u
ld be
sati
sfied wit
h
probability 1. The aim i
s
to give full considerat
ion to various
situations that limitting the wind
farm ca
pa
city. Optimization
mathematica
l
model of
cut
t
ing machi
ne
is expre
s
sed
as form
ula (4
):
Li
Wi
P
P
max
(4)
The
con
s
trai
n
t
conditio
n
is
simila
r to t
he
formula
(3
) a
nd the diffe
re
nce i
s
that
5
1
~
are the val
u
e
less than 1 i
n
formul
a (3
), but
1
5
4
3
2
1
in the optimizatio
n
mathemati
c
al
model.
2.4. Solv
ing Metho
d
s
Take wi
nd
power insta
lled capacity as chrom
o
som
e
an
d test the adapt
ability of each
chromo
som
e
usin
g the Mo
nte Carl
o sim
u
lation techni
que, the pro
c
ess is sho
w
n
as follo
ws:
(1) Ente
r the prima
r
y data;
(2) Evolution
gene
ration ini
t
ialized to ze
ro and
give the initial values of the popu
lation,
the cro
s
sove
r rate and mut
a
tion rate;
(3) Mo
dify the network pa
ra
meters and start the flow calcul
ation;
(4) Produ
ce
chromo
som
e
and appli
c
at
e the Monte Carl
o simul
a
tion tech
nolog
y to test
the feasibility of chro
mo
so
mes, sort the i
ndividual, inspect the con
s
traint con
d
itio
ns;
(5)Output the
best i
ndivid
ual in
ca
se t
he evolutio
n
gene
ration
a
c
hieve th
e m
a
ximum
value; Otherwise start to code, sel
e
ct, crosso
ve
r, mut
a
tion and d
e
code, then sub
to step (3).
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e-ISSN: 2
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TELKOM
NIKA
Vol. 11, No
. 8, August 2013: 4433 –
4438
4436
3. Results a
nd Analy
s
is
of Sample Sy
stem
The sampl
e
system
wa
s
sho
w
n i
n
Fi
gure
1. No
d
e
1 re
prese
n
ts wi
nd farm whi
c
h
con
n
e
c
ted
wit
h
no
de
s 8
through
tran
smi
ssi
on li
ne
s;
T
he n
ode
s
2, 3
,
4, 5
rep
r
e
s
e
n
t co
nvention
a
l
thermal po
we
r gene
rating
units and the
total inst
alled
capa
city is 1072.68M
W,a
nd the maximum
load of the
sy
stem i
s
682.5
M
W.The foll
o
w
ing
analy
s
is
is to dete
r
mi
ne the o
p
tima
l cap
a
city of the
wind farm of the
sy
st
em.
Figure 1. The
Geographi
c
Diag
ram of Sample Syste
m
3.1. Capaci
t
y
Optimizatio
n
The nod
e 8 repre
s
e
n
ts 11
0kV bu
s and
35kV bu
s of the 110
kV su
bstation a
s
shown in
Figure 1,
whi
c
h i
s
ta
ken
a
s
p
a
rall
el poi
nt. Paramete
rs
are set a
s
follows: wi
n
d
speed
Wei
bull
distrib
u
tion
paramete
r
is k=2.0
;
The cut-i
n
speed o
f
wind turbine i
s
4m/s;
95
.
0
5
4
3
2
1
; The p
opul
ation si
ze
i
s
10;
The
maximum
evolution
gene
ration
is 100;
The
cross rate
ra
nge i
s
[0.5,0
.9]; The
sco
pe of
the
m
u
tation
rate
is
[0.001,0.1]. The cal
c
ul
ation
result
s we
re
sho
w
n in Ta
b
l
e 1.
Table 1. The
Cal
c
ulation
Result
s of Win
d
Powe
r
Node 8 voltage g
r
ade
C=6,
ou
t
v
=20(m/s)
C=6,
ou
t
v
=25(m/s)
C=8,
ou
t
v
=20(m/s)
C=8,
ou
t
v
=25(m/s)
110kV
98.54(MW)
91.37
94.56
86.64
35kV
79.32
72.67
78.34
68.02
It can
be
se
e
n
from
the
Ta
ble 1
that the
wind
po
we
r in
tegration
cap
a
city is g
r
eat
er
whe
n
the ra
nge
of the outp
u
t of the wi
nd tu
rbi
ne is sm
alle
r, the voltage l
e
vel is
highe
r and th
e ave
r
age
wind
spe
ed is smalle
r.
3.2. Wind Ge
neratin
g
Set
Cutting Op
timization
Take th
e pa
rameters e
q
u
a
l to the valu
e of the
corre
s
po
ndin
g
wh
en calculatio
n value i
s
98.54 M
W
. The cal
c
ul
ation
result
s we
re
sho
w
n in Ta
b
l
e 2.
Table 2. The
Cal
c
ulation
Result
s of Win
d
Gene
rating
Set Cutting O
p
timization
The Genetic
Gene
ration
Number of
Optimum Value
Wind Pow
e
r
Capacit
y
(MW
)
Wind Pow
e
r
Active
Power(MW
)
Load Rate o
f
Wind Pow
e
r
Cutting off
Rate of Wind
Power
43 65.69
59.12
8.66%
33.34%
Table
2 sho
w
ed th
at wi
n
d
po
we
r pe
n
e
trati
on limit
decrea
s
e
d
by
33.34%
whe
n
all the
constrai
nt conditions were meet compared to
be m
e
et with a
certain proba
bility, to explain
the
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Re
sea
r
ch on
the Wind Po
wer Pe
netrati
on Lim
i
t in Po
wer S
ystem
(Yang Zha
ng)
4437
condition wit
h
minimum
occurring probability (0
.05) limitted the wind power capacity, which
made the cal
c
ulatio
n re
sul
t
s be co
nserv
a
tive, lose a lot of wind.
3.3. Transien
t Che
c
k
1. Wind spee
d disturban
ce
and fault mode
(1)
Wi
nd sp
e
ed cha
nge
s at
the
m
o
st d
r
asti
c m
odel:
from
the
rat
ed
wind
spee
d 14
m/s
down to cutting win
d
sp
ee
d 4m/s within
2s.
(2)
N-1fault:1
10kV lin
es b
e
twee
n nod
e
3 and 4 o
ccur thre
e ph
ase sho
r
t-circuit
,
cut off
fault lines after 0.12
s.
2.
Che
ck
res
u
lt
The no
rmal o
peratio
n with
wind p
o
wer 6
5
.69M
W
(1) Wi
nd
sp
e
ed di
sturban
ce
s. Th
e pa
rt of
syste
m
node
voltage
variation
cu
rve was
sho
w
n
in
Fig
u
re
2. Syste
m
freq
uen
cy
and
syste
m
t
y
pical unit rel
a
tive
ang
el chang
e curve
wa
s
sho
w
n in Fig
u
re 3. The Fi
gure 2 an
d F
i
gure 3
sho
w
ed the voltage of part of the system u
n
it
appe
are
d
sm
all-sco
pe fluct
uation after th
e gradi
ent
wi
nd startin
g
at 3s, then re
co
verde to no
rmal
level; And th
e pa
ralleli
ng
node
freq
uen
cy keep
in
rated value, t
he typical un
it relative a
n
g
le
fluctuated
wit
h
in a
na
rrow ra
nge,
th
en
re
stored
co
nstant,
so
th
e sy
stem vol
t
age, fre
que
n
c
y,
angle
were st
able after wi
n
d
spe
ed di
stu
r
ban
ce.
Figure 2. Nod
a
l Voltage Cu
rve unde
r Wi
nd
Speed Di
stu
r
ban
ce
Figure 3. System Freq
uen
cy and Power-angl
e
Curve u
nde
r
Wind Spe
ed
Distu
r
ba
nce
(2)
Fault di
st
urba
nce the
part of
syste
m
nod
e volta
ge vari
ation
curve
was
shown in
Figure 4. System frequ
en
cy and sy
stem
typical uni
t relative
ang
el cha
nge cu
rve
we
re sho
w
n in
Figure 5. Th
e Figure 4 a
nd Figu
re 5
sho
w
e
d
the
voltage of pa
rt of the syst
em we
re in t
h
e
accepta
b
le ra
nge (0.9p.u.
~1.1p.u.)
b
e
fore
sh
ort-
ci
rcuit, but app
eare
d
large-scop
e
agitation, the
n
recovered to
norm
a
l level
after
cutting
o
ff fault lines;
And the
pa
ral
l
eling
node
freque
ncy
ke
e
p
in
rated valu
e, the typical u
n
i
t relative an
gle fluc
tuate
d
within a
wid
e
ran
ge d
u
ri
ng dist
urb
a
n
c
e,
then resto
r
ed
con
s
tant, th
erefo
r
e, the
system vo
ltag
e, frequ
en
cy, angle
we
re
stable
after f
ault
disturban
ce.
Figure 4. Nod
a
l Voltage Cu
rve unde
r Fa
ult
Distu
r
ba
nce
Figure 5.
Syst
em Fre
quen
cy and Powe
r-angle
Curve u
nde
r
Fault Distu
r
b
ance
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e-ISSN: 2
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TELKOM
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Vol. 11, No
. 8, August 2013: 4433 –
4438
4438
4. Conclusio
n
This pa
per e
s
tablish
ed the optimizatio
n mat
hemati
c
al
models of wi
nd power p
e
n
e
tration
and cutting m
a
chi
ne, and g
enetic al
gorit
hm based on
Monte Ca
rlo
simulatin
g
wa
s used to sol
v
e
the problem.
the analy
s
is
of pra
c
tical e
x
ample
sh
o
w
ed that the i
n
fluenci
ng fa
ctor of p
enet
rat
i
on
of wind fa
rm
con
s
i
s
t of the
parall
e
l no
d
e
voltage, th
e output vari
ation ra
nge
o
f
wind g
ene
ratin
g
set an
d mea
n
win
d
spee
d
etc. The
win
d
po
wer
ca
pa
city equal
s to
the optimi
z
e
d
ca
pa
city value
in ca
se of high proba
bil
i
ty operation
conditi
o
n
; otherwi
se e
q
u
a
ls to the cutting machi
n
e
optimized
capacity value.
Thus the st
ability of
the transient
process of the system
can be
guarantee
d, and ma
king
the best use
of wind power
. Research co
ncl
u
si
o
n
can direct
the
prog
ram
m
ing
and ope
ratio
n
of reality wind farm.
Ackn
o
w
l
e
dg
ements
Found
ation it
em: Natu
ral
sci
en
ce a
d
va
nce
d
proje
c
t pro
g
ram
s
f
unde
d by ed
ucatio
n
depa
rtment o
f
Henan p
r
ovi
n
ce (201
0A4
7000
4).
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ces
[1]
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oha
nd
as, Ash
w
a
n
i K
u
mar Ch
an
del.
T
r
ans
ient Stabilit
y E
nha
nce
m
ent
of the P
o
w
e
r S
y
st
e
m
w
i
t
h
Wind Generation.
T
e
lko
m
n
i
ka Ind
o
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an Jour
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ngi
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i
t
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le W
i
n
d
Po
w
e
r Generat
i
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lko
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H
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h
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