Currently, as a universal clean energy, natural gas plays a greater role in industrial and civil energy consumption than it has previously. Any insufficient supply scenario has a severe impact due to the increasing use of power plants, chemical engineering, industrial production, and public sectors. It is essential to develop a methodology for analyzing gas supply insufficiencies that are caused by pipeline network malfunctions. This paper introduces a systematic method for evaluating the natural gas supply reliability based on the pipeline network. Primarily, the reliability of each unit in the pipeline network is derived from multi-variant distribution principles to initiate topological structure analysis carried out in the real pipeline network. Afterwards, the Monte Carlo simulation shows the random status of the topological network based on preconcerted failure distributions of facilities and pipes rather than estimating the reliability directly. Because the current transmission capacity is possibly excessive relative to the transmission task, both designed capacity and current supply capacity require stochastic simulations. After stochastic simulations of the market demand, a feasible random transmission requirement and a certain structure of the topological network are obtained from random simulations to calculate the total transmission capacity. Ultimately, according to the supply insufficiency level, there are deployable measures that could eliminate this influence.

1.
CNPC Economics & Technology Research Institute
,
Domestic and International Oil & Gas Industry Development Report
(
China National Petroleum Corporation
,
Beijing, People's Republic of China
,
2015
).
2.
Y.
Setiadi
,
T. T.
Tanyimboh
, and
A. B.
Templeman
, “
Modelling errors, entropy and the hydraulic reliability of water distribution systems
,”
Adv. Eng. Software
36
,
780
788
(
2005
).
3.
G. C. K.
Leung
,
A.
Cherp
,
J.
Jewell
, and
Y.-M.
Wei
, “
Securitization of energy supply chains in China
,”
Appl. Energy
123
,
316
326
(
2014
).
4.
M. S.
Javed
,
R.
Raza
,
I.
Hassan
 et al, “
The energy crisis in Pakistan: A possible solution via biomass-based waste
,”
J. Renewable Sustainable Energy
8
(
4
),
043102
(
2016
).
5.
H.
Weihe
, “
Reliability of large-scale natural gas pipeline network
,”
Acta Petrolei Sin.
34
,
401
404
(
2013
).
6.
A. J.
Brito
and
A. T.
de Almeida
, “
Multi-attribute risk assessment for risk ranking of natural gas pipelines
,”
Reliab. Eng. Syst. Saf.
94
,
187
198
(
2009
).
7.
S.
Yong
,
M.
Lin
, and
M.
Jon
, “
A practical approach for reliability prediction of pipeline systems
,”
Eur. J. Oper. Res.
198
,
210
214
(
2009
).
8.
A.
Amirat
,
A.
Mohamed-Chateauneuf
, and
K.
Chaoui
, “
Reliability assessment of underground pipelines under the combined effect of active corrosion and residual stress
,”
Int. J. Pressure Vessels Piping
83
,
107
117
(
2006
).
9.
A. P.
Teixeira
,
C.
Guedes Soares
,
T. A.
Netto
, and
S. F.
Estefen
, “
Reliability of pipelines with corrosion defects
,”
Int. J. Pressure Vessels Piping
85
,
228
237
(
2008
).
10.
L. Y.
Xu
and
Y. F.
Cheng
, “
Reliability and failure pressure prediction of various grades of pipeline steel in the presence of corrosion defects and pre-strain
,”
Int. J. Pressure Vessels Piping
89
,
75
84
(
2012
).
11.
G.
Quercia
,
D.
Chan
, and
K.
Luke
, “
Weibull statistics applied to tensile testing for oil well cement compositions
,”
J. Pet. Sci. Eng.
146
,
536
544
(
2016
).
12.
Z.
Shenwei
and
Z.
Wenxing
, “
Cost-based optimal maintenance decisions for corroding natural gas pipelines based on stochastic degradation models
,”
Eng. Struct.
74
,
74
85
(
2014
).
13.
P.
Xing-yu
,
Y.
Dong-chi
,
L.
Guang-chuan
,
Y.
Jian-sheng
, and
H.
Sha
, “
Overall reliability analysis on oil/gas pipeline under typical third-party actions based on fragility theory
,”
J. Nat. Gas Sci. Eng.
34
,
993
1003
(
2016
).
14.
Interstate Natural Gas Association of America
,
Interstate Natural Gas Pipeline Efficiency
(
Interstate Natural Gas Association of America
,
Washington, DC
,
2010
).
15.
American National Standard Institute, ASME B31G-2009,
Manual for Determining the Remaining the Strength of Corroded Pipelines
(American National Standard Institute, Washington, DC, USA,
2009
).
16.
O.
Yevkin
, “
An efficient approximate Markov chain method in dynamic fault tree analysis
,”
Qual. Reliab. Eng. Int.
32
,
1509
1520
(
2016
).
17.
S.
Anjuman
,
S.
Rehan
, and
T.
Solomon
, “
Risk analysis for oil & gas pipelines: A sustainability assessment approach using fuzzy based bow-tie analysis
,”
J. Loss Prev. Process Ind.
25
,
505
523
(
2012
).
18.
Y. K.
Lin
and
C. F.
Huang
, “
Reliability of a multi-state computer network through k minimal paths within tolerable error rate and time threshold
,”
Qual. Reliab. Eng. Int.
32
,
1393
1405
(
2016
).
19.
W.
Kanyapat
and
W.
Paramote
, “
Reliability optimization of topology communication network design using an improved ant colony optimization
,”
Comput. Electr. Eng.
35
,
730
747
(
2009
).
20.
S.
Rimkevicius
,
A.
Kaliatka
,
M.
Valincius
,
G.
Dundulis
,
R.
Janulionis
,
A.
Grybenas
, and
I.
Zutautaite
, “
Development of approach for reliability assessment of pipeline network systems
,”
Appl. Energy
84
,
22
33
(
2012
).
21.
J.
Mehdi
,
J. K.
Guest
, and
T.
Igusa
, “
Reliability-based topology optimization of trusses with stochastic stiffness
,”
Struct. Saf.
43
,
41
49
(
2013
).
22.
M. L.
Seung
and
H. P.
Dong
, “
An efficient method for evaluating network-reliability with variable link-capacities
,”
IEEE Trans. Reliab.
50
,
374
379
(
2001
).
23.
R.
Noorossana
, “
System reliability with multiple failure modes and time scales
,”
Qual. Rel. Int.
32
,
1109
1126
(
2016
).
24.
V.
Yorucu
, “
Price modeling of imported natural gas in Turkey
,”
J. Renewable Sustainable Energy
8
(
1
),
013111
(
2016
).
25.
W.
Shuang
,
T.
Dazhen
,
L.
Song
,
C.
Hao
, and
W.
Haiyong
, “
Coalbed methane adsorption behavior and its energy variation features under supercritical pressure and temperature conditions
,”
J. Pet. Sci. Eng.
146
,
726
734
(
2016
).
26.
W.
Jinglong
,
Z.
Ningsheng
,
C.
Junbin
, and
W.
Yingru
, “
Data analysis of the real-time pressure and temperature along the wellbore in intelligent well Lei 632 with commingling production in LH oilfield
,”
J. Pet. Sci. Eng.
138
,
18
30
(
2016
).
27.
M.
Valinčius
,
I.
Žutautaitė
,
G.
Dundulis
,
S.
Rimkevičius
,
R.
Janulionis
, and
R.
Bakas
, “
Integrated assessment of failure probability of the district heating network
,”
Reliab. Eng. Syst. Saf.
113
,
314
322
(
2015
).
28.
F.
Muwei
,
W.
Yang
,
K.
Wenhui
, and
G.
Jing
, “
The reliability estimation of simplified natural gas pipeline compressor stations based on statistical principles
,” in
International Pipeline Conference
,
Calgary, Alberta, Canada
,
25–30 September 2016
.
29.
L.
Yuxing
and
Y.
Guangzhen
,
The Design and Management of Gas Transmission Pipeline
(
Chine University of Petroleum Press
,
Beijing, People's Republic of China
,
2009
).
30.
F.
Pukelsheim
, “
The three sigma rule
,”
Am. Stat.
48
,
88
91
(
1994
).
31.
M.
Holweg
, “
The genealogy of lean production
,”
J. Oper. Manage.
25
(
2
),
420
437
(
2007
).
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