Internati
o
nal
Journal of Ele
c
trical
and Computer
Engineering
(IJE
CE)
V
o
l.
6, N
o
. 1
,
Febr
u
a
r
y
201
6,
pp
. 63
~70
I
S
SN
: 208
8-8
7
0
8
,
D
O
I
:
10.115
91
/ij
ece.v6
i
1.9
061
63
Jo
urn
a
l
h
o
me
pa
ge
: h
ttp
://iaesjo
u
r
na
l.com/
o
n
lin
e/ind
e
x.ph
p
/
IJECE
Application of Component Critic
ality Importance Measures in
Desi
gn S
c
hem
e
of
Power P
l
ants
Smaj
o Bisa
nov
i
c*
, M
e
rsiha
Sa
ma
rdzic*
*,
D
a
mir Aga
n
ov
ic*
* Public Enterpr
i
se Elektropr
ivreda of Bosnia
and
Herzegovina d.d. –
Sarajevo,
B
o
snia and
Herzegovina
** Faculty
of
Electr
i
cal
Engineer
ing, Univ
er
si
ty
of Sa
ra
je
vo, Bo
snia and
Her
zegov
ina
Article Info
A
B
STRAC
T
Article histo
r
y:
Received Sep 22, 2015
Rev
i
sed
No
v
11
, 20
15
Accepted Nov 28, 2015
This paper presents application o
f
co
mponent criticality
importan
c
e measures
in phase of
prep
aration and
design of
power pl
an
ts
. Th
es
e
measur
es provide
a
numerical r
a
nk
to determine
which
components are more important for
power plant
re
li
abili
t
y
im
prove
m
e
nt or m
o
re cr
itic
al fo
r power
plant f
a
ilu
re
.
Identif
y
i
ng cr
itical components
for pow
er
plant reliab
ility
pr
ovides an
important
inpu
t for d
e
cision
-making and
guidance throu
ghout th
e
development pr
oject.
The stud
y
on
se
ver
a
l schematic design
options of
conventional
thermal power plan
t show
that
the
importance meas
ures can b
e
used as an effective tool to assess co
m
ponent cr
iticali
t
y
in the p
r
oject phase
of new produ
ction cap
acities.
Keyword:
Criticality im
p
o
rta
n
ce m
easures
Design sc
hem
e
Discrete e
v
ent
Reliab
ilit
y
Therm
a
l
po
wer
pl
ant
Copyright ©
201
6 Institut
e
o
f
Ad
vanced
Engin
eer
ing and S
c
i
e
nce.
All rights re
se
rve
d
.
Co
rresp
ond
i
ng
Autho
r
:
Sm
ajo Bisanovic,
Pu
bl
i
c
Ent
e
rp
ri
se
El
ekt
r
o
p
ri
vr
eda of
B
o
s
n
i
a
and
He
rze
g
o
v
i
n
a d.
d. – Sara
j
e
vo
,
Vilson
ovo
setaliste 1
5
,
71
0
0
0
Sa
raje
v
o
, B
o
s
n
i
a
an
d
Herze
g
ovi
na.
Em
a
il: s.b
i
sano
v
i
c@elek
tropriv
red
a
.b
a
1.
INTRODUCTION
Therm
a
l powe
r
plant desi
gn
is characterize
d
by m
a
jor co
m
p
l
e
xi
ty
of eq
ui
pm
ent
and t
echn
o
l
o
gi
cal
sch
e
m
e
s th
at req
u
i
res an
i
n
creased
atten
t
i
o
n in
t
h
eir
reliab
i
lity. Th
erefore, a
p
o
wer
p
l
an
t
d
e
sign
m
u
st b
e
ab
le
to
qu
an
tify rel
i
ab
le and
co
st-effectiv
e cho
i
ce o
f
co
m
p
on
en
ts wit
h
resp
ect to
th
e im
p
act th
ey h
a
v
e
on
p
l
an
t
reliability. Design c
oul
d
be optim
i
zed by risk,
rank
ing t
h
e im
portance
of c
o
m
pone
nts
.
When
com
pone
nt
s
with
sign
ifican
t risk
are selected
t
h
i
s
way
,
t
h
e
ri
sk
fre
qu
ency
ca
n be
i
m
prove
d by
decr
easi
ng t
h
e
una
vailability
of the selected com
pone
nts, m
odifica
tion/
replacem
ent with highe
r reliability co
m
ponents
,
im
pro
v
i
n
g t
h
e
defe
nse i
n
r
o
ot
of
fai
l
u
re
occ
u
r
r
ence
com
p
o
n
ent
or
dec
r
ea
si
ng t
h
e c
ont
ri
but
i
o
n
fre
q
u
en
ci
es o
f
in
itial ev
en
t [1].
Com
pone
nt im
portance
m
eas
ures
are
com
m
only
use
d
in ri
sk as
sessm
ents, pa
rticularly proba
b
ilistic
ri
sk ass
e
ssm
ent
s
of
n
u
cl
ear
po
we
r pl
a
n
t
s
[
2
,
3]
. I
n
po
we
r i
n
du
st
ry
, c
o
m
ponent
i
m
port
a
nce m
easur
es are
ap
p
lied in d
i
fferen
t con
f
i
g
uratio
n
s
of
electrical networks
design
[4–6].
In t
h
ese a
p
plications, the
com
p
one
n
t
im
portance m
easure
s
are called ris
k
im
porta
nce m
easures
an
d
are u
s
ed
to
id
en
tify co
m
p
on
en
ts th
at sh
ould
b
e
i
m
p
r
ov
ed in
o
r
d
e
r to
redu
ce t
h
e
risk
and
id
en
tify co
m
p
on
en
ts for risk
-b
ased
serv
ice i
n
spectio
n
an
d testin
g.
C
o
m
pone
nt
i
m
port
a
nce m
e
asure
s
are a
p
p
l
i
e
d i
n
di
f
f
ere
n
t
p
h
ases
of t
h
e pl
a
n
t
’
s l
i
f
e
cy
cl
e. In t
h
e
desi
g
n
p
h
ase, t
h
e im
port
a
nce m
easure m
a
y
be use
d
t
o
i
d
e
n
t
i
f
y
weak p
o
i
n
t
s
and c
o
m
ponent
s t
h
at
sh
o
u
l
d
be
im
proved to increase the
plant re
liability.
Reliability of a com
ponent
m
a
y be im
proved
by using a highe
r
quality com
p
onent, i
n
troduci
ng
re
dundant c
o
m
pone
nts,
re
duci
ng t
h
e
ope
rational a
n
d environm
ental loads
on
the com
pone
nt
or by im
provi
ng its m
a
intainability. Th
e optim
a
l im
prove
m
e
nts are a com
p
lex problem
and
out
of t
h
i
s
sc
o
p
e.
In t
h
e e
xpl
oi
t
a
t
i
on
phase
,
t
h
e com
p
o
n
e
n
t
i
m
port
a
nce
m
easures m
a
y be
used
t
o
al
l
o
cat
e
i
n
spect
i
o
n a
n
d
m
a
i
n
t
e
nance
re
sou
r
ces
o
n
t
h
e
m
o
st
im
port
a
nt
com
pone
nt
s.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
SN
:
2
088
-87
08
I
J
ECE Vo
l. 6
,
N
o
. 1
,
Febru
a
ry
2
016
: 6
3
–
70
64
Research and a
c
hievem
ent of powe
r plant optim
a
l
re
liab
ili
t
y
p
r
esen
ts co
m
p
lex
prob
lem
t
h
at requ
ires
carefu
l
and
coo
r
d
i
n
a
ted
wo
rk
in
th
e do
m
a
in
o
f
ach
i
ev
i
n
g
qu
ality an
d
reliab
ility in
e
l
ectric p
o
w
er
syste
m
.
Im
portant role in solving this problem
shoul
d be
playe
d
by m
e
thods
of fo
recasting, optim
ization and
n
o
rm
aliz
in
g
reliab
ility
in
d
i
ces with
d
e
p
e
nden
ce on
b
a
sic
tech
n
i
cal and
eco
no
m
i
cal p
a
ram
e
ters, as well as
devel
opm
ent of m
e
thods
for a
c
hiev
ing
reliability in exploita
tion.
Th
e im
p
o
r
tan
c
e
m
easu
r
es q
u
an
tify th
e criti
cality
o
f
p
a
rti
c
u
l
ar co
m
p
on
en
t with
in
a p
l
an
t d
e
sign
.
They
have
bee
n
wi
del
y
use
d
as t
ool
s
f
o
r
i
d
ent
i
f
y
i
n
g
c
o
m
ponent
s t
h
at
m
o
re si
g
n
i
f
i
c
ant
l
y
i
n
fl
u
e
nce
o
n
t
h
e
p
l
an
t b
e
h
a
v
i
o
r
with
resp
ect to reliab
ility, ris
k
and
safety. Th
ey can
also
prov
id
e
v
a
lu
ab
le in
form
atio
n
fo
r the
m
a
i
n
t
e
nance a
nd
o
p
erat
i
o
n
p
l
ant
.
I
n
t
h
i
s
pa
per
,
i
m
port
a
nc
e
m
easures a
r
e
use
d
i
n
case
whe
n
c
o
m
pon
ent
s
i
n
t
h
erm
a
l
power
pl
ant
ex
hi
bi
t
a bi
nary
fu
nct
i
oni
ng
be
havi
o
r
. T
h
i
s
im
pl
i
e
s t
h
at
pl
ant
an
d
i
t
s
co
m
pone
nt
s are
ei
t
h
er f
u
l
l
y
f
u
nct
i
oni
ng
or
f
u
l
l
y
fai
l
e
d.
Fo
r t
h
e
bi
nary
ca
se, c
o
m
pone
nt
s can
be
ra
n
k
e
d
wi
t
h
respe
c
t
t
o
t
h
e
i
m
p
act th
ey h
a
v
e
on
p
o
wer p
l
an
t reliab
ility
b
a
sed
o
n
a g
i
ven
i
m
p
o
r
tan
ce measu
r
es. Th
e m
u
l
ti-state reli
ab
ility
anal
y
s
i
s
can
b
e
use
d
i
n
t
h
e
p
h
ase
of
p
r
e
p
arat
i
o
n a
n
d
desi
g
n
of
p
o
w
e
r pl
a
n
t
sc
he
m
e
s, but
wi
t
h
speci
al
atten
tio
n
.
Nam
e
ly,
m
a
in
p
o
wer p
l
an
t co
m
p
on
en
ts (steam
b
o
iler, pu
m
p
s, tu
rb
in
e, g
e
n
e
rat
o
r), b
ecau
s
e of th
eir
ch
aracteristics in
stru
ct
u
r
al sch
e
m
e
, lo
se th
eir to
tal cap
ab
ilit
ies cau
sed
b
y
d
a
m
a
g
e
s. For ex
am
p
l
e, d
a
m
a
g
e
s in
st
eam
boi
l
e
r pi
pe sy
st
em
redu
ce boi
l
e
r ca
pac
i
t
y
and po
we
r out
put
of t
u
rbi
n
e an
d ge
ne
rat
o
r
,
b
u
t
l
ead t
o
ne
w
dam
a
ges of pi
pe sy
st
em
and t
o
a bi
gge
r l
o
ss of st
eam
, final
l
y
l
eadi
ng t
o
an o
u
t
a
ge
. It
i
s
very
im
port
a
nt
t
o
recognize whi
c
h parts of m
a
in power
plant com
pone
nts can be
m
ode
led as
m
u
lti-state co
m
pone
nt
s and
ope
rat
e
at
vari
ous l
e
vel
s
o
f
p
e
rf
orm
a
nce, o
p
posi
t
e
t
o
t
h
e bi
nary
pers
pect
i
v
e. T
h
ese t
y
pe
s of c
o
m
pone
n
t
s
m
a
y
pr
o
v
i
d
e f
unct
i
oni
ng
or se
rvi
c
e at
degra
d
ed c
o
m
pone
nt
per
f
o
rm
ance l
e
vel
s
. In rece
nt
y
ear
s, m
u
l
t
i
-
st
at
e sy
st
em
reliability theory and a
n
alysis ha
ve
receive
d considera
b
le
at
tention [7].
The
pape
r i
s
or
ga
ni
zed as
fol
l
o
ws:
Sect
i
o
n
2
p
r
ov
id
es th
e ov
erv
i
ew o
f
com
p
onent criticality
i
m
portance m
easure
s
use
d
i
n
recent literature and app
lied for
t
h
erm
a
l
power plant desi
gn.
Section 3 applies
and c
o
m
p
ares im
portance m
easure
s
for di
fferent options
of the structural schem
e
of
conve
n
tional t
h
erm
a
l
po
we
r pl
ant
,
a
n
d
Sect
i
o
n 4 pr
esent
s
c
oncl
u
si
ons
.
2.
REVIEW OF
THE MOST
WIDELY USED
C
O
MPO
N
ENT I
M
P
O
RTA
NCE
ME
AS
URES
Findi
ng the cri
tical co
m
pone
nts is
an im
portant issue for reliability
analysis and the optim
i
zation of
t
h
erm
a
l
power
pl
ant
desi
gn
. The ai
m
i
s
t
o
obt
ai
n i
n
f
o
rm
at
i
on co
ncer
ni
n
g
com
p
o
n
ent
’
s
cont
ri
but
i
o
n t
o
t
h
e
p
l
an
t reliab
ility. Reliab
ilit
y i
m
p
o
r
tan
ce indices are v
a
l
u
ab
le in
estab
lish
i
ng
d
i
rectio
n an
d
prioritizatio
n
of
actio
n
s
related to
reliab
ility i
m
p
r
o
v
e
m
e
n
t
i
n
power
p
l
an
t
d
e
sign
or in
su
gg
esting
th
e
m
o
st efficien
t way to
ope
rat
e
an
d m
a
i
n
t
a
i
n
pl
ant
st
at
us. I
n
g
e
ne
ra
l
,
com
pone
nt
i
m
port
a
nce m
e
asure
s
i
n
pl
a
n
t
use a n
u
m
e
ri
cal
ran
k
(rel
a
t
i
v
e i
m
por
t
a
nce),
base
d
on ce
rt
ai
n c
h
a
r
act
eri
s
t
i
c
of
i
n
terest, su
ch
as th
e co
m
p
on
en
t’s co
n
t
ribu
tio
n
t
o
powe
r plant (failure) event occurrence
.
The
m
o
st freq
u
ent
l
y
used risk im
po
rtance m
e
trics are give
n in [1,
4,
8
–12
]. Th
e
follo
wing
assu
mp
tio
ns are m
a
d
e
: (i) ind
e
p
e
n
d
e
n
t
failu
re
p
r
ob
ab
ilities an
d rep
a
ir ti
mes for
com
pone
nts is com
m
on sim
p
lification in reliability m
odeling, (ii) com
pone
nt
states and as
sociate
d
p
r
ob
ab
ilities are k
nown, (iii)
ex
pon
en
tial d
i
strib
u
tion
for re
p
a
ir tim
e an
d
ti
m
e
to
failu
re,
(iv
)
t
w
o-state m
o
d
e
l
(in t
h
e
power plant, com
p
one
n
ts are
di
rectly connecte
d
t
o
e
ach
othe
r)
[4].
Birn
bau
m
impo
rtan
ce
i
s
o
n
e
o
f
t
h
e
m
o
s
t
w
i
d
e
l
y
u
s
e
d
im
portance
measures in risk theory.
Anal
y
t
i
cal
l
y
, B
i
rn
baum
m
easure
of i
m
port
a
n
ce o
f
c
o
m
pone
nt
i
at tim
e
t
, i
s
de
fi
ne
d
by
:
()
(
)
(;
(
)
1
)
(;
(
)
0
)
()
B
s
si
si
i
i
Rt
I
t
Rt
R
t
Rt
R
t
Rt
(
1
)
whe
r
e
I
i
B
(
t
) i
s
t
h
e B
i
r
nba
um
im
port
a
nce
o
f
com
p
o
n
e
n
t
i
,
R
S
(
t
) t
h
e sy
s
t
em
(the p
o
we
r pla
n
t in
o
u
r
case
)
reliab
ility at ti
me
t
,
R
i
(
t
) the
reliability of c
o
m
pone
nt
i
at tim
e
t
,
R
S
(
t
;
R
i
(
t
)
= 0
)
t
h
e p
o
wer p
l
an
t reliab
ility
at
ti
m
e
t
gi
ven co
m
ponent
i
is failed
an
d
R
S
(
t
;
R
i
(
t
) = 1) is th
e p
o
wer
p
l
an
t reliab
ility
at t
i
m
e
t
gi
ven c
o
m
ponent
i
is p
e
rfectly work
i
n
g.
The Birnba
um
im
portance
is
basically a sensitivity
analysis in pla
n
t relia
bility due to c
o
m
ponent
i
. If
I
i
B
(
t
) is large, a
rather sm
all change
in t
h
e re
liability of com
ponent
i
will h
a
v
e
larg
e consequ
e
n
ces
on
th
e p
l
an
t
reliab
ility at ti
me
t
. Th
e Birnb
a
u
m
i
m
p
o
r
tance ran
k
i
n
g
rep
r
esen
ts th
e m
a
x
i
m
u
m
lo
ss in
plan
t reliab
ility wh
en
com
pone
nt
i
o
p
erat
es f
r
o
m
the co
n
d
i
t
i
on
o
f
pe
rfect
f
unct
i
oni
ng
(
R
i
(
t
) = 1
)
to
t
h
e con
d
i
tio
n
of certain
failu
re
(
R
i
(
t
) =
0)
. I
n
(
1
) B
i
r
n
baum
’s im
port
a
nce m
easure
o
f
com
p
o
n
e
n
t
i
onl
y
depe
n
d
s
on t
h
e
st
ruct
u
r
e
of t
h
e pl
ant
and t
h
e relia
bilities of the ot
her c
o
m
pone
nt
s.
I
i
B
(
t
) is ind
e
p
e
nd
en
t of th
e reliab
ility
R
i
(
t
) o
f
c
o
m
pone
n
t
i
and
t
h
i
s
i
s
t
h
e
wea
kne
ss
of
B
i
rn
b
a
um
’s im
port
a
nce m
easure.
The
fact
t
h
at
c
o
m
pone
nt
i
is
critical fo
r th
e
syste
m
(pl
a
nt
), e
x
pres
ses n
o
t
h
i
ng a
b
out t
h
e state of com
p
onent
i
. Th
e
d
e
fi
n
itio
n con
cern
s
o
t
h
e
r co
m
p
on
en
ts
o
f
t
h
e
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
ECE
I
S
SN
:
208
8-8
7
0
8
App
lica
tio
n o
f
Co
mp
on
en
t Critica
lity Impo
rt
a
n
c
e Mea
s
ures in
Design
S
c
heme
o
f
Po
wer
Pla
n
t
s
(
S
. Bi
s
a
novi
c
)
65
pl
ant
o
n
l
y
. If c
o
m
pone
nt
i
i
s
cri
t
i
cal
for t
h
e
pl
ant
,
t
h
a
n
co
m
ponent
i
m
u
st
ei
t
h
er be cut
set
of o
r
de
r 1
,
or
be
me
m
b
er of cut
set where all t
h
e othe
r c
o
m
p
on
en
ts in
t
h
e same cu
t set h
a
ve failed
.
Ano
t
h
e
r
p
opu
lar m
e
tric
m
eas
u
r
e, is
critica
lity impo
rtan
ce
measu
r
e th
at i
n
clud
es the unreliab
ility o
f
com
pone
nt
,
F
i
(
t
),
wh
ereas B
i
rnb
a
u
m
i
m
p
o
r
tan
ce m
easu
r
e do
es
n
o
t
. Analytical
ly, criti
cality i
m
p
o
r
tan
ce is
defi
ned
as:
()
1
(
)
(;
(
)
1
)
(;
(
)
0
)
()
()
()
1
(
)
CR
B
i
Ft
R
t
ii
Rt
R
t
Rt
R
t
It
I
t
si
s
i
i
Ft
R
t
s
s
(
2
)
whe
r
e
F
i
(
t
) is the unreliability of com
pone
nt
i
at time
t
and
F
S
(
t
) th
e system (th
e
p
o
w
er p
l
an
t) unreliabilit
y a
t
ti
m
e
t
.
B
a
sed
on
t
h
i
s
defi
ni
t
i
on,
m
e
asure
o
f
c
r
i
t
i
cali
t
y
im
port
a
nce
I
i
CR
(
t
) of
com
p
o
n
e
n
t
i
at time
t
present
s
the probability that com
pone
nt
i
is critical f
o
r th
e
po
wer plan
t an
d
is fail
ed
at ti
m
e
t
, w
h
en t
h
e power
plant is
failed
at tim
e
t
. As m
o
tiv
atio
n
for in
t
r
odu
cin
g
criticality i
m
p
o
r
tan
ce m
e
asu
r
e,
we
n
o
t
e th
at co
m
p
on
en
t
i
is
cri
t
i
cal
for t
h
e
pl
ant
,
i
f
t
h
e
ot
h
e
r com
pone
nt
s
i
n
t
h
e pl
ant
are
i
n
such st
at
es
t
h
at
t
h
e pl
ant
i
s
fu
nct
i
oni
n
g
, i
f
an
d
o
n
l
y if
co
m
p
on
en
t
i
is fun
c
tio
n
i
ng
. To
say th
at co
m
p
on
en
t
i
is critical, the stat
ement about the other
com
pone
nt
s i
n
t
h
e pl
ant
i
s
n
eeded
, an
d n
o
t
st
at
em
ent
about
com
pone
nt
i
. Criticality
im
portance m
e
asure is
p
a
rticu
l
arly su
i
t
ab
le fo
r
prio
rit
i
zin
g
m
a
in
ten
a
n
ce activ
ities.
The
reliability ac
hieveme
n
t
worth
(R
A
W
)
im
port
a
nce
m
e
asure
o
f
c
o
m
pone
nt
i
is t
h
e
ratio
o
f
t
h
e
actu
a
l power plan
t reliab
ility o
b
t
ain
e
d wh
en co
m
p
on
en
t
i
i
s
al
way
s
i
n
pe
rfect
fu
nct
i
o
ni
ng
(
R
i
(
t
) =
1
)
to
th
e
actu
a
l v
a
lu
e
o
f
th
e po
wer p
l
an
t reliab
ility. Th
e RAW m
eas
u
r
e
d
e
term
in
es th
e m
a
x
i
m
u
m p
e
rcen
tag
e
i
n
crease
in
th
e
po
wer
p
l
an
t reliab
ility gen
e
rated
b
y
p
a
rticu
l
ar co
m
p
on
en
t:
(;
(
)
1
)
()
()
RA
W
si
i
s
Rt
R
t
It
Rt
(
3
)
The
relia
b
ility redu
ctio
n
wo
rt
h
(R
R
W) im
port
a
nce m
easure of com
pone
nt
i
is
th
e ratio
o
f
th
e actu
a
l
p
o
wer
p
l
an
t
reliab
ility to
th
e
v
a
lu
e of t
h
e
p
l
an
t reliab
ility wh
en
co
m
p
onen
t
i
is al
ways in
p
e
rfect
un
reliab
l
e
(
R
i
(
t
) =
0
)
. The RR
W
m
easu
r
e
d
e
term
in
es th
e ind
e
x m
e
a
s
u
r
i
n
g th
e
po
ten
tial d
a
m
a
g
e
cau
sed
to th
e
p
o
wer
pl
ant
by
a part
i
c
ul
ar
c
o
m
pone
nt
:
()
()
(;
(
)
0
)
RRW
s
i
si
Rt
It
Rt
R
t
(
4
)
Reliab
ilit
y achiev
e
m
e
n
t
wo
rt
h
an
d reliab
ility redu
ction
wo
rt
h
m
easu
r
es
are m
a
in
ly u
s
ed
as a risk
i
m
p
o
r
tan
c
e m
e
asu
r
es in prob
ab
ilistic safety
assessm
en
ts
o
f
n
u
c
lear p
o
wer p
l
an
ts.
Fussell-Vesely
’s
i
m
port
a
nce
m
easure
I
i
FV
(
t
) is prob
ab
ilit
y th
at at least on
e m
i
n
i
m
a
l
cu
t set th
at
cont
ai
n
s
com
pone
nt
i
is failed
at ti
m
e
t
, g
i
v
e
n
th
at th
e
p
o
wer p
l
an
t is failed
at ti
m
e
t
. Accord
i
n
g
to
th
is
m
easure, t
h
e i
m
port
a
nce of a
com
ponent
i
i
n
t
h
e p
o
we
r pl
ant
depe
n
d
s o
n
t
h
e num
ber an
d t
h
e or
de
r of t
h
e cut
-
sets wh
ere it ap
p
e
ars. An
alytically, Fu
ssell-Vesely’s m
e
tri
c
is d
e
fin
e
d
as:
1
()
Pr
(
(
)
)
()
Pr
(
(
)
)
1
(
)
FV
m
i
j
j
i
i
s
t
Dt
It
Ct
R
t
(
5
)
whe
r
e
D
i
(
t
) sta
t
es that at leas
t o
n
e
of
the
m
i
nim
a
l cut set
containi
ng
c
o
m
ponent
i
has failed at tim
e
t
,
C
(
t
)
states that the powe
r
plant
is failed at time
t
,
j
i
(
t
)
denotes t
h
e
probability that the m
i
ni
m
a
l cut set
j
,
containi
ng
c
o
m
ponent
i
, is failed at ti
m
e
t
.
Fussell-
Vesely
’s m
easure takes int
o
co
nsi
d
eratio
n the
f
act that a co
m
ponent m
a
y cont
rib
u
te to
po
we
r plant fai
l
ure with
out be
ing criti
cal. Th
e com
ponent c
ont
rib
u
tes to plant failure w
h
e
n
a
m
i
nim
a
l cu
t set,
containi
ng
the
com
pone
nt, is
failed.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
SN:
2
088
-87
08
I
J
ECE Vo
l. 6
,
No. 1
,
Febru
a
ry
2
016
: 6
3
–
70
66
3.
CO
MPO
N
EN
T IMP
O
RT
A
NCE
ME
AS
U
R
ES
IN THE
R
MAL POWER PLANT
DESIGN
Seve
ral o
p
tion
s
of c
o
nve
ntio
nal therm
a
l po
wer
plant
of
6
00 M
W
incl
ud
ing m
a
in pipes
of t
h
e fir
s
t
an
d seco
nd
l
o
o
p
s
(I
L
, II
L
), m
a
in circ
ulation
p
u
m
p
s an
d s
u
pply
(fee
d
)
p
u
m
ps (M
C
P
, SP
), steam
boiler
s
(SB
)
and turbi
n
es (T) are illustrated in Figure 1. The relia
bility block diagram
s
for total failure assessm
e
n
t are
prese
n
ted i
n
Figu
re 1
.
Each c
o
m
pone
nt has
eno
u
gh ca
pac
ity
to satisfy
the needs
of its o
w
n
ge
nerato
r a
t
their
nom
inal po
we
r
o
u
tp
ut.
a)
Design
co
nfig
ur
atio
n #1
.
b
)
Desi
g
n
config
ur
atio
n #2
.
SB
SB
SB
SB
SP
SP
MC
P
MC
P
MC
P
MC
P
II
L
II
L
I
L
I
L
I
L
I
L
G
G
30
0 MW
30
0 MW
T
T
[
1
]
[
2]
[
3
]
[
4]
[
9
]
[
10]
[
5
]
[
6]
[
7
]
[
8]
[
1
1]
[
1
2]
[
13]
[
14]
[
19]
[
20]
[
15]
[
1
6]
[
17]
[
18]
I
L
SP
SP
II
L
SB
SB
SB
SB
MC
P
MC
P
MC
P
MC
P
T
T
I
L
I
L
I
L
II
L
II
L
II
L
SB
SB
MC
P
SP
MC
P
I
L
II
L
II
L
I
L
G
30
0 M
W
T
G
30
0 M
W
T
SP
SP
[
1
]
[
2]
[
3
]
[
4]
[
5
]
[
6
]
[
7
]
[
8]
[
9
]
[
10
]
[
1
1
]
[
12]
SP
SP
I
L
I
L
II
L
II
L
SB
SB
MC
P
MC
P
T
T
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
ECE
I
S
SN:
208
8-8
7
0
8
Application of
Comp
onent Criticality Import
anc
e
Measures
in Design Scheme of
Power Plants
(
S
. Bis
a
novi
c
)
67
c)
Design
co
nfig
ur
atio
n #3
.
Figu
re
1.
Str
u
c
t
ural sc
hem
a
tic o
p
tion
s
of c
o
n
v
entio
nal t
h
er
m
a
l powe
r
pla
n
t o
f
6
0
0
M
W
Selected desig
n
co
nfig
u
r
atio
ns (
optio
ns
) of c
onventi
onal therm
a
l power
plant consider those
com
pone
nts, whic
h greatly
depe
n
d
o
n
bas
i
c
therm
ody
na
m
i
c
param
e
ter
s
[
1
3
,
1
4
]
.
S
o
,
f
o
r
exam
ple, steam
boiler is com
pone
nt of synthesized heating surface, ai
r he
ater, convectional and ai
r ec
onom
izer, scree
n
and
convection ste
a
m
heaters, et
c. Illustrate
d da
ta applied in t
h
e calcu
lation
of c
o
m
pone
nt criticality im
p
o
rta
n
ce
m
easures
fo
r t
h
e the
r
m
a
l po
wer
pla
n
t desi
g
n
, a
r
e
pre
s
ente
d in
Ta
ble 1
.
Table
1.
Com
p
onent specification an
d reliabi
lity data applie
d in the calculations
option
Component reliabi
lity
I
L
MCP
SB
II
L
SP
T
#1
0.
998
0.
9945
0.
997
0.
998
0.
9962
0.
996
#2
0.
997
0.
991
0.
995
0.
997
0.
9962
0.
996
#3
0.
997
0.
991
0.
995
0.
9975
0.
9962
0.
992
Reliability im
p
o
rta
n
ce m
easu
r
es were c
o
m
puted fo
r eac
h com
pone
nt and
for each analy
zed option.
The com
p
one
n
ts were ra
nked according to t
h
eir im
portanc
e based
on thei
r res
p
ective m
e
tric values as
give
n
in
Tables 2–4. Design
co
nfiguration are di
fferent am
ong the
m
selves
in a
manner
of reli
ability increase –
by
com
p
licating structural sc
hem
e
with
gre
a
t num
ber
of com
pone
nts
with less c
a
pacity (higher
quality
com
pone
nt). T
a
bles 2
–4 s
h
o
w
the m
e
tric values an
d
ran
k
i
ng o
f
dif
f
ere
n
t co
m
pone
nts in the analy
zed
desig
n
configurations
(options) in case of
therm
a
l power
plant t
o
tal failure.
For c
o
n
f
ig
urati
on (
o
ption
)
#
1
the hig
h
est ran
k
ed
c
o
m
pone
n
t
is steam
turbi
n
e (T)
,
the secon
d
ra
nke
d
com
pone
nt is sup
p
ly
p
u
m
p
(SP), a
n
d the least im
por
tant
com
ponents a
r
e the first an
d
the secon
d
lo
op
(I
L
,
II
L
), as shown in Table 2. T
h
is is
conceptua
l
identificatio
n regarding the
com
pone
nt
ranking, although each
i
m
portance m
e
tric has respective rank
.
From
all analyzed diffe
re
nt m
e
tr
ics, Criticalit
y
Im
portance m
easure
and F
u
ssell-Ve
sely’s m
easure ha
ve cl
osest
m
e
tric values
a
n
d equal
ra
nk for each c
o
m
ponent
in
desi
gn
opti
on
#
1
. In
th
is
op
tio
n, m
i
n
i
m
a
l cu
t sets f
our
th
o
r
d
e
r
ar
e
d
o
m
in
atin
g
b
e
cau
se
o
f
topolo
g
i
cal sch
e
m
e
an
d
com
pone
nt ca
p
acity
that is en
ou
g
h
to
satisfy
need
s
of
o
w
ne
r
ge
nerat
o
r at
th
eir n
o
m
i
nal out
put.
For c
o
n
f
ig
urat
ion #
2
, the hi
g
h
est ran
k
e
d
co
m
ponent
is
m
a
in circulation
pum
p (M
C
P
),
the seco
nd
ranke
d
com
p
onent is steam
b
o
iler (SB
)
, and the least im
portant com
pon
e
n
ts are the fi
rst and the sec
o
n
d
lo
op
(I
L
, II
L
), a
s
s
h
ow
n i
n
Ta
ble
2.
In
this
o
p
tio
n, all m
e
tric
s have
eq
ual c
o
m
ponent
ran
k
i
ngs
, e
x
ce
pt R
e
liability
R
e
ductio
n
Wo
rth im
portance
m
easure that has ra
nk e
q
u
a
l 1 fo
r all com
pone
nts, an
d d
o
es n
o
t p
r
ovi
de
inf
o
rm
ation regar
d
in
g the
m
o
st im
portan
t
co
m
pone
nt.
From
all analy
zed diffe
re
nt
m
e
trics, C
r
iticality
Im
portance m
easure a
nd Fussell-Vesely’s
m
easure ha
ve
closest
m
e
tric values and equal ra
nk
for each
com
pone
nt in
study
c
o
n
f
ig
uratio
n
#2
. I
n
this o
p
tion
,
m
i
nim
a
l cut sets secon
d
or
der e
x
ist beca
use
o
f
top
o
lo
gical schem
e
and com
ponent capa
c
ity
that is e
nou
g
h
to satisfy
needs o
f
o
w
ne
r ge
nerat
o
r at their
nom
inal out
p
u
t.
SB
SB
G
60
0
M
W
MC
P
SP
SP
MC
P
I
L
II
L
II
L
I
L
T
T
SP
SP
I
L
[
1
]
[
2]
[
3
]
[
4]
[
5
]
[1
1
]
[
6
]
[
7]
[
8
]
[
9]
[
1
0
]
I
L
II
L
II
L
SB
SB
MC
P
MC
P
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
SN:
2
088
-87
08
I
J
ECE Vo
l. 6
,
No. 1
,
Febru
a
ry
2
016
: 6
3
–
70
68
For c
o
n
f
ig
urati
on (
o
ption
)
#
3
the hig
h
est ran
k
ed
c
o
m
pone
n
t
is steam
turbi
n
e (T)
,
the secon
d
ra
nke
d
com
pone
nt is
m
a
in circulatio
n
pum
p (M
C
P
), a
n
d
the
least
im
porta
nt co
m
ponent is the
seco
nd
lo
op
(
I
I
L
),
as
shown i
n
Ta
bl
e 4. In t
h
is
option, all m
e
trics ha
ve e
q
ual c
o
m
pone
nt ra
nkings
, e
x
cept R
e
liability Reduction
Wo
rth im
port
a
nce m
easure
that has
ran
k
eq
ual
2 f
o
r
all com
pone
nts exce
pt ste
a
m
turbine
w
h
ich
has
boundless Reliability Reduction
Worth
value (Inf) and rank
equal
1. From
al
l analyz
e
d
different m
e
trics,
Criticality I
m
porta
nce m
easure and Fuss
ell-
Vesely
’s m
easure
ha
ve close
s
t
m
e
tric values an
d eq
ual ra
nk
f
o
r
each c
o
m
pone
nt in c
o
nfigura
tion
#3. In t
h
is option m
i
nim
a
l cut sets sec
o
nd orde
r e
x
ist,
plus
one m
i
nim
a
l cut
set first
order that relates t
o
turbi
n
e
outage.
Table 2.
C
o
m
pone
nt ran
k
in
gs
an
d
m
e
tric
values fo
r o
p
tion
#1
co
m
p
.
m
a
rk
Birnbau
m
Criticalit
y
Fu
ssell-Vesely RAW
RRW
r
a
nk
value r
a
nk value r
a
nk
value
r
a
nk
value r
a
nk value
I
L
1,
5,
11,
15
3 0.
0000
97
5
0.
0030
79
5 0.
0031
56
4 1.
0000
00
2
1.
0000
97
M
C
P
2,
6,
12,
16
3 0.
0000
97
3
0.
0084
96
3 0.
0086
80
3 1.
0000
01
2
1.
0000
97
SB
3,
7,
13,
17
3 0.
0000
97
4
0.
0046
22
4 0.
0047
34
4 1.
0000
00
2
1.
0000
97
II
L
4,
8,
14,
18
3 0.
0000
97
5
0.
0030
79
5 0.
0031
56
4 1.
0000
00
2
1.
0000
97
SP
9,
19
2 0.
0079
06
2
0.
4766
92
2 0.
4797
52
2 1.
0000
30
1
1.
0079
38
T
10,
20
1 0.
0079
07
1
0.
5018
82
1 0.
5050
02
1 1.
0000
32
1
1.
0079
38
mi
n
i
ma
l
c
u
t
s
e
t
s
:
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12,
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{1,
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{1,
5
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14,
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{1,
5
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14,
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{1
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9
}
, {1
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0
}
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{1,
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8
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{1,
8
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5
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{2,
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1
3,
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6
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16
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6
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6
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14,
15
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6
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16},
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6
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17},
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6
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6
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19},
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6
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20},
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7
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7
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7
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11,
17
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7
,
11,
18},
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7
,
12,
15},
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7
,
12,
16},
{4,
7
,
12,
17},
{4,
7
,
12,
18},
{4,
7
,
1
3,
15},
{4,
7
,
13,
16
},
{4,
7
,
13,
17},
{4,
7
,
13,
18},
{4,
7
,
14,
15
},
{4,
7
,
14,
16},
{4,
7
,
14,
17},
{4,
7
,
14,
18},
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7
,
19},
{4,
7
,
20},
{4,
8
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11,
15},
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8
,
11,
16},
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8
,
11,
17
},
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8
,
11,
18},
{4,
8
,
12,
15},
{4,
8
,
12,
16},
{4,
8
,
12,
17},
{4,
8
,
12,
18},
{4,
8
,
1
3,
15},
{4,
8
,
13,
16
},
{4,
8
,
13,
17},
{4,
8
,
13,
18},
{4,
8
,
14,
15
},
{4,
8
,
14,
16},
{4,
8
,
14,
17},
{4,
8
,
14,
18},
{4,
8
,
19},
{4,
8
,
20},
{9,
11,
15},
{9,
11,
1
6
},
{9,
11,
17},
{9,
11,
18},
{9,
12,
15},
{9,
12,
16},
{9,
12,
17
},
{9,
12,
18},
{9,
13,
15},
{9,
13,
16},
{9,
13,
17},
{9,
13,
18}
,
{9,
14,
15},
{9,
14,
1
6
},
{9,
14,
17},
{9,
14,
18},
{9,
19},
{9,
20},
{10,
11,
15},
{10,
1
1
,
16},
{10,
11,
17},
{10,
11,
18},
{10,
1
2
,
15},
{10,
12,
16},
{10,
12,
17},
{
10,
1
2
,
18},
{10,
13,
15},
{10,
13,
16},
{10,
1
3
,
17},
{10,
13,
18},
{10,
1
4
,
15},
{10,
14,
16},
{10,
14,
17},
{10,
1
4
,
18},
{10,
19},
{1
0,
20}
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
ECE
I
S
SN:
208
8-8
7
0
8
Application of
Comp
onent Criticality Import
anc
e
Measures
in Design Scheme of
Power Plants
(
S
. Bis
a
novi
c
)
69
Table 3.
C
o
m
pone
nt ran
k
in
gs
an
d
m
e
tric
values fo
r o
p
tion
#2
co
m
p
.
m
a
rk
Birnbau
m
Criticalit
y
Fu
ssell-Vesely RAW
RRW
r
a
nk value r
a
nk value r
a
nk
value r
a
nk value r
a
nk value
I
L
1,
7
5
0.
0268
17
5
0.
1064
40
5
0.
1103
41
5
1.
0000
81
1
1.
0274
93
M
C
P
2,
8
1
0.
0269
80
1
0.
3212
52
1
0.
3310
22
1
1.
0002
43
1
1.
0274
93
SB
3,
9
2
0.
0268
71
2
0.
1777
56
2
0.
1839
01
2
1.
0001
34
1
1.
0274
93
II
L
4,
10
5
0.
0268
17
5
0.
1064
40
5
0.
1103
41
5
1.
0000
81
1
1.
0274
93
SP
5,
11
4
0.
0268
39
4
0.
1349
32
4
0.
1397
65
4
1.
0001
02
1
1.
0274
93
T
6,
12
3
0.
0268
44
3
0.
1420
62
3
0.
1471
21
3
1.
0001
07
1
1.
0274
93
mi
n
i
ma
l
c
u
t
s
e
t
s
:
{1
,7
}, {1
,8
}, {1
,9
}, {1
,1
0
}
, {1
,1
1
}
, {
1
,1
2
}
, {2
,7
}, {2
,8
}, {2
,9
}, {2
,1
0
}
, {2
,
1
1
}
, {2
,1
2
}
,
{3
,7
}, {3
,8
}, {3
,9
}, {3
,1
0
}
, {3
,1
1
}
, {
3
,1
2
}
, {4
,7
}, {4
,8
}, {4
,9
}, {4
,1
0
}
, {4
,
1
1
}
, {4
,1
2
}
,
{5
,7
}, {5
,8
}, {5
,9
}, {5
,1
0
}
, {5
,1
1
}
, {
5
,1
2
}
,
{6,7}, {6,8}, {6,9},
{6,
10},
{6,11},
{6,
12}
Table 4.
C
o
m
pone
nt ran
k
in
gs
an
d
m
e
tric
values fo
r o
p
tion
#3
co
m
p
.
m
a
rk
Birnbau
m
Criticalit
y
Fu
ssell-Vesely RAW
RRW
r
a
nk value r
a
nk value r
a
nk
value r
a
nk value
r
a
nk
value
I
L
1,
6
5
0.
0224
51
5
0.
0078
97
5
0.
0081
95
5
1.
0000
68
2
1.
0230
97
M
C
P
2,
7
2
0.
0225
87
2
0.
0238
33
2
0.
0245
86
2
1.
0002
05
2
1.
0230
97
SB
3,
8
3
0.
0224
96
3
0.
0131
87
3
0.
0136
59
3
1.
0001
13
2
1.
0230
97
II
L
4,
9
6
0.
0224
39
6
0.
0065
77
6
0.
0068
29
6
1.
0000
57
2
1.
0230
97
SP
5,
10
4
0.
0224
69
4
0.
0100
10
4
0.
0103
81
4
1.
0000
86
2
1.
0230
97
T
11
1
0.
9994
67
1
0.
9374
52
1
0.
9379
53
1
1.
0080
65
1
I
n
f
mi
n
i
ma
l
c
u
t
s
e
t
s
:
{1,6}, {1,7}, {1,8}, {1
,9}, {1,10}, {2,6}, {2,7
}, {2,8}, {
2
,9}, {2,10}
, {3,6}, {3,7},
{3,8}, {3,9
}, {3,10}, {4,6},
{4,7}, {4,8}, {4,9}, {4
,10}, {5,6}, {5,7}, {5,8
}, {5
,9
}, {
5
,1
0
}
, {1
1
}
The o
b
se
rvatio
ns fr
om
the experim
e
ntal results in the different de
si
gn c
o
n
f
ig
uratio
ns (
optio
ns
) f
o
r
total failure of
therm
a
l power
plant incl
ude:
1.
The Reliability Reduction
Worth im
portance m
easur
e cannot distinguish
betwee
n com
pone
nts that
occupy appropriate position i
n
a se
ries
structure but have
significantly
different failure probabilities.
This res
u
lt is
not ratio
nal be
cause it is clear that th
e
m
o
st unreliable co
m
ponent in th
e series structu
r
e
sh
ou
l
d
b
e
th
e hig
h
e
st
r
a
nk
ed at the rank list.
2.
Am
ong t
h
e a
n
a
l
yzed m
e
trics, Criticality Im
p
o
rta
n
ce m
easure and
Fus
s
ell-Vesely’s m
easure
are
the
m
o
st
dynam
i
c
and responsi
v
e. The
com
pone
nts t
h
at occ
u
py si
m
ilar structur
a
l
positions, but have
di
ffe
rent
reliabilities, will be ranked
differen
tly. Generally, these m
e
t
r
ics induce
reasonable conclusions and t
h
ese
can be use
d
to select
the
candida
te com
p
onents for im
prove
m
ent.
3.
Birnbaum
m
e
tr
ic, as well as R
e
liability Achievem
en
t Wort
h for option #1, canno
t recognize the
ranking
of c
o
m
pone
nts
in pa
rallel structure with
signi
ficant
di
ffe
rent reliabilities. This
m
a
y lead to m
i
slead
or
deri
ng
in te
r
m
s of g
u
idin
g t
h
e sy
stem
m
a
intena
nce.
4.
Whe
n
Birnba
um
m
e
tric
is high a
nd the ba
s
i
c co
m
pone
nts
una
vailability already fairly low, one could
th
in
k of
i
n
tr
odu
cing
ex
tr
a
r
e
du
nd
an
cy.
4.
CO
NCL
USI
O
NS
The analysis of the t
h
erm
a
l power
plants
rel
i
ability is usually ba
sed
on si
m
p
le indexes t
h
at do
not
take into account t
h
e criticality of s
o
m
e
failures. T
h
is
crit
icality should
be e
v
aluated on relia
bility concept
s
that conside
r
the effect of
a com
pone
nt
failure
on the
powe
r
plant
perfor
m
a
nce. Althoug
h relia
bility
im
portance m
easure
ha
ve bee
n
de
velo
pe
d f
o
r the p
o
w
er
i
n
dust
r
y
an
d ap
p
lied in transm
ission a
n
d distri
butio
n
system
s, it can be
use
f
ul m
e
trics to ra
nk
com
pone
nt
s re
garding thei
r im
pact on power pla
n
t reliability,
operation
and maintenance. These
anal
yzed m
easures serve as very
usef
ul t
ools
for reliability i
m
provem
e
n
t
com
pone
nts a
n
d as
ve
ry
val
u
able in
fo
rm
ation
f
o
r
deci
si
o
n
-m
akers t
o
e
v
aluate
wh
ere
investm
e
nts co
uld
be
made in
order t
o
im
prove the functioni
ng
and reliability of t
h
e
power
plant
.
In this
pape
r st
ruct
ural schem
a
tic option
s
o
f
con
v
e
n
tional t
h
erm
a
l powe
r
plan
t of
600
MW show th
at
the use
d
im
portance m
easures can
be us
ed as
an effective t
o
ol to asses
s
com
ponent critic
ality in the pha
se of
preparation and design of
new production
capacities.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
SN:
2
088
-87
08
I
J
ECE Vo
l. 6
,
No. 1
,
Febru
a
ry
2
016
: 6
3
–
70
70
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F.
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,
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a
m
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rquez
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2008.
BIOGRAP
HI
ES OF
AUTH
ORS
Smajo Bisanovic receiv
ed the d
e
gree of
Electr
i
cal
Engineer in
1991, MSc degr
ee in 1994
and
PhD degree in 2009 from the Faculty
of Electrical Engin
eer
ing,
Un
iversity
of Sarajevo
, Bosnia
and Herzegov
in
a. He is
as
s
o
cia
t
e profes
s
o
r at th
e F
acult
y of E
l
e
c
tri
cal
Engine
eri
ng, Univers
i
t
y
of Sarajevo, Bosnia and
Herze
govina. His ar
eas of in
terest in
clude operation
,
planning
and
economics of
po
wer s
y
stems an
d
application
of r
e
liability
th
eor
y
to power s
y
s
t
ems.
M
e
rs
iha S
a
m
a
rdzic re
ceiv
e
d a
BS
c degree in
power
elec
tri
cal
engineer
ing for the F
acult
y of
Electrical Eng
i
n
eering
,
Univ
ersity
of Sar
a
jevo
,
Bosnia and
Her
zegovin
a
in
201
4. She
is now
pursuing her
MSc degree
in
the same Faculty
.
Her
res
e
a
r
ch int
e
res
t
s
in
clude
com
puter
simulations and
design an
aly
s
is
applied
to pow
er
s
y
stems.
Dam
i
r Aganovic is received a M
S
c degree in po
wer elec
tri
cal en
gineer
ing from
the Facult
y
of
Electrical
Engin
eering
,
University
of Sarajevo,
B
o
snia and Herzegovina in
2010.
He is currently
purs
u
ing his
P
h
D degree in the s
a
m
e
field at the
s
a
m
e
Univers
ity. He is
an Expe
rt as
s
o
ciat
e for
Power S
y
stem
Operation
Man
a
gem
e
nt
at Pub
lic
Ent
e
rprise
E
l
ektropr
ivreda
o
f
Bosnia
and
Herzegovin
a
. His areas
of in
ter
e
st in
clude
oper
a
tion and p
l
ann
i
ng
of power s
y
s
t
em
s.
Evaluation Warning : The document was created with Spire.PDF for Python.