View
216
Download
0
Category
Preview:
Citation preview
Permodelan dan Optimisasi Pasar Gas Bumi Jawa Bagian Barat untuk
Memaksimalkan Nilai Social Welfare Konsumen dan Nilai Net Back
Gas Bumi Produsen
F. A. Aji1, W.W. Purwanto1
1. Chemical Engineering Department, Engineering Faculty, Universitas Indonesia, West Java, Indonesia
Email: farisariantoaji@gmail.com
Abstrak
Pengelolaan gas bumi merupakan isu yang penting terkait permintaan dan harga bagi kepentingan negara
maupun konsumen. Penelitian ini bertujuan melakukan optimisasi terhadap fungsi social welfare
mewakili kepentingan konsumen dan fungsi netback produsen mewakili kepentingan negara. Obyek
penelitian ini adalah pasar gas bumi Jawa Bagian Barat dengan permintaan terbesar di Indonesia dan
infrastruktur terintegrasi. Optimisasi multi obyektif digunakan untuk memperoleh titik optimum kedua
fungsi. Formula harga wholesale gas bumi pada titik optimum disusun sebagai fungsi linier terhadap
harga minyak bumi dengan slope α dan konstanta k. Nilai α diperoleh dengan rentang 0,1079 – 0,1589
dengan k pada rentang 3,7 – 5,38.
Modelling and Optimization of Natural Gas Market in West Java Area
to Maximize Consumer Social Welfare Value and Gas Producer Net
Back Value
Abstract
Natural gas utilization is an important issue related to the demand and prices for the benefit of country
and consumers. This study aims to optimize social welfare represents the interests of consumer and
producer netback representing the interests of country. The scope of this research is the natural gas market
in Western Java area having the biggest demand and integrated infrastructure. Multi-objective
optimization is used to obtain the optimum value of both functions. Wholesale price formula of natural
gas at the optimum value is structured as a linear function of the price of crude oil with slope α and
constant k. The values of α obtained in the range of 0.1079 to 0.1589 with k in the range of 3.7 to 5.38.
Keywords: natural gas, social welfare, netback value, multi-objectives optimization
1. Introduction
Natural gas is one of the largest energy resources in Indonesia. This country is one of the
biggest natural utilizer both as producer and consumer. The natural gas produced in
Indonesia in 2012 reach 2.982 BSCF (BPS, 2014) with 1.445 BSCF domestic
consumption (BPPT, 2014). In addition to fulfill domestic demands, natural gas produced
in Indonesia also exported abroad through transmission pipeline and liquefied natural gas
(LNG).
Natural gas demand in domestic market rise significantly this years along with the high
economic growth in Indonesia. The domestic demand projected in 2035 reach 2.679
BSCF consisting of refinery-own use-loses, power generation, commercial,
transportation, household and industry (BPPT, 2014). Meanwhile, the production in that
period is only reach ± 1,600 BSCF resulting deficit of natural gas supply (BPPT, 2014).
Therefore, domestic productions of natural gas have to optimize to fulfill its domestic
demand.
Natural gas market in Western Java area is the biggest market in Indonesia having
integrated infrastructure. In 2013, natural gas utilization in this area reach 36.25% of
national utilization of natural gas. The sources of supply are obtained from local
production in West Java, from South Sumatera through South Sumatera – West Java
(SSWJ) pipeline and from Kalimantan and Papua through LNG.
The price of natural gas is become the most important factor in natural gas utilization.
Currently, the price is still very competitive compared to the energy resources at the same
unit. Natural gas price at consumer gate is influenced by netback value of this energy
resources in producer side. In 2012, the average price of natural gas in Western Java area
amounted to 6.85 USD/MMBTU (PGN, 2012). Besides, the price of high speed diesel
(HSD) reach 30.76 USD/MMBTU (PGN, 2012). However, along with the competition
between domestic product and import product, the willingness to pay of natural gas
consumers become affected because the price of energy abroad is quite low. In certain
level, natural gas price is not accepted by consumers and choosing cheaper energy
resources, such as coal.
Aside of being one of the energy resources for domestic usage, natural gas become one
of commodity that generate revenue for Indonesia. The revenue generated from oil and
gas sector in APBN-P 2014 is targeted to reach 29.7 billion US Dollar. This amount
contribute to 18.71% of total revenue in APBN-P 2014. The revenue generated by natural
gas is obtained from its sales both in domestically and abroad. Therefore, the higher
netback value of natural gas in production side will give higher revenue for the country.
According to above, it is necessary to develop natural gas market models of Western Java
area to obtain the optimum value of social welfare value representing domestic
consumers’ interest and netback value of producer representing the interest of the country.
The model developed by considering several factors in natural gas value chain.
Optimization is then carried out to get optimum value for both social welfare and netback.
Based on that value, a formula of natural gas price is developed for wholesale market of
natural gas in Western Java area.
2. Material and Methods
2.1 Natural Gas Demand and Supply in Western Java Area
As on Figure 1, the natural gas supply and demand data arranged in a gas balance
according to the fulfillment of the demand for natural gas scenarios developed. The
natural gas demands rise from 2016 to 2030 as projected in Business As Usual (BAU)
growth scheme used. BAU sceme growth is gas demand projection with existing
economic growth.
2.2 Natural Gas Infrastructure in Western Java Area
The existing infrastructure delivering natural gas from suppliers to custormers in Wertern
Java area consist of transmission pipeline, distribution pipeline and LNG Floating Storage
Regasification Unit (FSRU). Each of the transportation facilities have certain throughput
that include or separately from the natural gas price as shown in Table 1.
Figure 1. Natural Gas Balance in West Java Area – A. Scenario 1; B. Scenario 2; C. Scenario 3
Table 1 Existing Natural Gas Infrastructure in West Java Area
Transportation Facility throughput Fee status
South Sumatera – West Java 1
(SSWJ 1) pipeline
Toll fee 1.47 USD/MSCF open access
Pipa SSWJ 2 Toll fee 1.51 USD/MSCF open access
PHE ONWJ – West Java Pipeline N/A N/A upstream dedicated
SES – West Java Pipeline N/A N/A upstream dedicated
Cilamaya – Cilegon Pipeline Toll fee 1.40 USD/MSCF open access
West Java Distribution Pipeline Distribution fee 750 IDR/m3 downstream dedicated
LNG FSRU West Java Regasification cost 3.03 USD/MMBTU -
LNG FSRU Lampung Regasification cost 3.43 USD/MMBTU -
0
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030
MM
SC
FDA LNG Hub Singapura
LNG Masela - New RU
LNG Tangguh Train 3 - New RU
LNG Donggi Senoro - New RU
LNG Tangguh - FSRU Lampung
LNG Badak - FSRU Jawa Barat
Pertamina West Java
SES (CNOOC)
PHE ONWJ
Pertamina EP South Sumatera
Corridor Block (Conoco Phillips)
BAU Demand
0
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030
MM
SC
FD
B
0
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030
MM
SC
FD
C
2.3 Crude Oil Price Projection
The crude oil price used to calculate substitute energy price is projected based on West
Texas Index (WTI) crude oil price projection from U.S. Energy Information
Administration as follow.
Figure 2. Crude Oil Price Projection
2.4 Natural Gas Market Modelling
Natural gas market in Western Java area is modelled as wholesale market consist of a
locus market that supplied from multiple sources of natural gas supply as shown in Figure
3.
Figure 3. Natural Gas Market in West Java Area Model
The demand of Western Java market is obtained from several sources, including existing
gas supply through pipeline transportation, the gas supply through LNG using the existing
0.00
20.00
40.00
60.00
80.00
100.00
120.00
2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030
Cru
de
Oil
Pri
ce (
US
D/b
bl)
infrastructure and gas supply through LNG using new infrastructure to supply LNG from
domestic and import. This model existing and projected natural gas supply in supply side
and projected demand for natural gas market in demand side. The modeling time period
is divided into 3 ranges period, ie 2016 to 2020 (Period I), 2021to 2025 (Period 2) and
2026 to 2030 (period 3).
The transportation scheme from gas sources to Western Java market describe as follow.
Figure 4. Natural Gas Transportation Scheme to Western Java Area
Western Java market is modelled as wholesale market which apply single price formula
for all gas supply get into this area with exit point in the end of transmission pipeline.
Meanwhile, distribution cost will be incurred in transporting natural gas from
transmission pipeline to end customers through distribution pipeline.
Based on transportation scheme shown in Figure 4, producer netback and consumer social
welfare value are formulated as follow.
Table 2 Producer Netback and Consumer Social Welfare Value Formulation
Nilai Formula
Netback (NB) �� = ���������� + ����
���������� = �1 + ���������� − ������������� + ����� − � !"�������#$%&
�'�
(
�'�
����) = �1 + ���������� − � ! �� − � ! *�� − +!��������)���&
�'�
(
�'�+ ����� − � ! �� − � ! *�� − � !+,��������)��-%
Social Welfare
(SW)
*� = ∑ ∑ �1 + �����/*�� −��� − 0����&�'�(�'� ���
Gas SourcesTransmission
Pipeline
Distribution
Pipeline
End
Customers
Gas SourcesLiquefaction
PlantShipping Regasification
Well head price Throughput End Customer Price
Upstream
Dedicated Pipeline
LNG import
Netback value (NB) of natural gas in Western Java area consist of netback for pipeline
and LNG. NB formulated in producer wellhead that obtained by offsetting wholesale
price with transportation fee from wellhead to Western Java market both for pipeline and
LNG. This value multiplied by the rate of natural gas (V) transported resulting NB as
shown Table 2.
In natural gas transportation through pipeline, transportation fee is using toll fee (TF)
which applicable under current contract (ext) for open access pipeline (oa) and simplified
levelized cost gas pipeline (sLCGP) calculation for upstream dedicated pipeline.
Meanwhile, for transporting natural gas through LNG, the transportation fee consist of
liquefaction cost, shipping cost and regasification cost. Liquefaction cost is calculated
with simplified levelized cost LNG liquefaction (sLCLL), while shipping cost is
calculated with simplified levelized cost LNG shipping (sLCLS). Regasification cost is
distinguished between existing facilities and projected facilities to be buit. Regasification
cost under current contract is used for existing facilities, while projected facilities are
using simplified levelized cost regasification unit (sLCRU).
RC is regasification cost for existing regasification facilities, while lngext representing
notation for current regasification facilities. In the model, it is assumed that the additional
supply for the foreseeable future is obtained through LNG only. Lngnew notation is used
for projected LNG facilities capacity.
Social welfare (SW) calculation is develop based on basic concept used in Gas Trade
Model (GTM) developed by Beltramo and Manne. The value describe as willingness to
pay minus production cost and transportation cost boundered by price and volume traded.
Willingness to pay is modelled as the price of energy substitute of natural gas, diesel oil.
The energy substitute price is modelled as index of crude oil price projected along the
modelling period, while production cost plus transportation cost is modelled in form of
wholesale price plus distribution cost.
In the social welfare equation shown in Table 2, ��� represents wholesale price in year
t, while 0��� represents distribution cost of each supply source i in year t. ��� represents
the rate of natural gas transported from each supply source i in year t. r is discount rate,
t is time period and i is gas supply source. Discount rate r is assumend in constant value
during periode t=1to t=T in the model.
There are three scenarios developed in the model that affect the overall modeling as
shown in the following table.
Table 3. Modelling Scenario
No Scenario
1 Natural gas deficit is fulfilled by domestic LNG supply. If still not sufficient, it will
be met from imported LNG supply.
2 Natural gas deficit is fulfilled by domestic LNG supply and imported LNG supply
with proportion 50% : 50%.
3 Natural gas deficit is fulfilled by 100% imported LNG supply.
The result of the modelling scenario is natural gas balance in Western java area for each
scenario developed.
2.5 Multi-objective Optimization
In order to solve the research problem, multi-objective optimization is used to meet the
trade off between social welvare and netback value as the objective function. f1 is the first
objective function aiming to maximize producer netback value of natural gas in upstream
sector, while f2 is the second objective function aiming to maximize consumer social
welfare value in downstream sector. The method use in the multi-objective optimization
is graphical method. The wholesale price is trialed from 8 USD/MMBTU to 24
USD/MMBTU resulting the curve of netback and social welfare. The intersection
between netback curve and social welfare curve resulting the optimum value for both
objective function. At that point, the value of netback is equal to the value of social
welfare so that the determination of wholesale price at that point not to burden either
consumers or producers.
It is possible to take decision which tend to one of the objective function. Tendency to
producer is shown by increasing netback value, while tendency to consumers is shown by
increasing social welfare value. The decision making process (DM) use weighted method
as follow.
13 = 31. 11 + 32. 12, where w1 + w2 = 1
Weighted factor used in the model is varied at w1 = 0,00; 0,25; 0,50; 0,75; 1,00.
2.6 Wholesale Price Formulation
The wholesale price of hatural gas in Western Java area is formulated as index of crude
oil price as follow.
��� = 6 × !�9:;<=>��=?; + k
Where ��� is wholesale price of natural gas in Western Java area at year t and α is
wholesale price index to crude oil price, while k is constant in USD/MMBTU. The value
of α is obtained in optimum value of netback and social welfare, while k is obtained at
minimum value of netback.
3. Result and Discussion
3.1 Netback and Social Welfare Value
The trade off curve between netback and social welfare resulted from the modelling
shown in Figure 5. Based on the result, it can be seen that the escalation of wholesale
price will increase producer netback value developing a positive linear curve. Along with
period of the modelling, there are degression of netback value caused by throughput
escalation affected by inflation rate.
Additional volume from import didn’t have any effect to netback value because the
import LNG didn’t give any value added to domestic producer. Therefore, the highest
netback value is in scenario 1 compared to other scenario at the same period.
Meanwhile, escalation of wholesale price decrease the consumer social welfare value,
developing a negative linear curve. The escalation of wholesale price give less gap
between wholesale price and energy substitute price as representation of willingness to
pay. Along the period, it can be seen that consumer social welfare value increasing
because of escalation of crude oil price.
3.2 Multi-objective Optimization Result
Based on the result shown in Figure 5, the curve between social welfare value and netback
value has an intersection resulting a wholesale price at optimum value of both function.
The wholesale prise resulted as follow.
Figure 5 Modelling Result – A. Scenario 1; B. Scenario 2; C. Scenario 3
0
10,000
20,000
30,000
40,000
50,000
60,000
0 2 4 6 8 10 12 14 1 6 18 20
MIL
LIO
N U
SD
WHOLESALE PRICE (USD/MMBTU)
A
f1 2016-2020
f1 2021-2025
f1 2026-2030
f2 2016-2021
f2 2021-2025
f2 2026-2030
0
10,000
20,000
30,000
40,000
50,000
60,000
0 2 4 6 8 10 1 2 1 4 16 18 20
MIL
LIO
N U
SD
WHOLESALE PRICE (USD/MMBTU)
B
f1 2016-2020
f1 2021-2025
f1 2026-2030
f2 2016-2020
f2 2021-2025
f2 2026-2030
-10,000
0
10,000
20,000
30,000
40,000
50,000
60,000
0 2 4 6 8 10 12 14 16 18 20 2 2 24
MIL
LIO
N U
SD
WHOLESALE PRICE (USD/MMBTU)
C
f1 2016-2020
f1 2021-2025
f1 2026-2030
f2 2016-2020
f2 2021-2025
f2 2026-2030
Tabel 4 Wholesale Price at Optimum Value
Scenario Period Wholesale Price (USD/MMBTU)
1 2016-2020 11.37
2021-2025 12.52
2026-2030 15.28
2 2016-2020 11.72
2021-2025 13.91
2026-2030 16.68
3 2016-2020 12.26
2021-2025 15.85
2026-2030 20.24
Based on the result shown in Table 5, it seen that wholesale price at optimum value
increasing along the period of modelling. It caused by increasing of substitute energy
price due to projection of crude oil price. The increasing of gas supply using LNG also
become one of factor that increase the wholesale price of natural gas. Additional volume
from import didn’t have any effect to netback value because the import LNG didn’t give
any value added to domestic producer but giving additional value to consumer social
welfare. The intersection of both function resulting higher wholesale price of natural gas.
3.3 Decision Making Process with Tendency to One of Objective Function
The optimum point resulted in optimization process is a point where both function have
the same weight, w1 = w2 = 50%. In decision making process, it is possible to have a
tendency to one of the objective function. The tendency will effect both social welfare
value and netback value as shown in Figure 6.
In Figure 7, it can be seen that tendency to netback value (f1) where w1 > 0,5 resulting
the increasing of netback value and decrease social welfare value and vise versa. It is
happened because the increasing of wholesale price has to be done in order to increasing
netback. The increasing of wholesale price will lower the netback value.
Figure 6 Impact of Weighted Factor to Netback and Social Welfare Value
In the decision making process where one of the objective function reach value of zero
(w1 or w2 = 0 = 0), it will obtain the maximum or minimum prices that limit the
determination of the wholesale price of natural gas. The limit is known as the ceiling price
to the upper limit of the price and the floor price for the lower limit of the price. The
values of floor price and ceiling price for all scenarios at each period are shown in the
following table.
Table 5 Ceiling Price and Floor Price
Scenario Period Floor Price
(USD/MMBTU)
Ceiling Price
(USD/MMBTU)
1 2016-2020 3.77 18.67
2021-2025 4.21 20.83
2026-2030 4.79 24.11
2 2016-2020 3.72 18.67
2021-2025 4.19 20.83
2026-2030 4.88 24.11
3 2016-2020 3.65 18.67
2021-2025 4.15 20.83
2026-2030 5.38 24.11
Floor price is set to protect producers by limiting the decline in wholesale prices
at the point that not giving negative netback to producers. Instead, the ceiling price is set
to protect consumers by limiting the increase in the wholesale price at the point where
that not giving negative social welfare to consumers.
3.4 Wholesale Formula of natural Gas in Western Java Area
Wholesale price formulated in the form of pricing formula linked to crude oil price with
the following basic formulation:
Wholesale Price (WP) = α x crude oil price + k
The α value is calculated based on the wholesale price of natural gas at the optimum point
of netback and social welfare, compared to the average price of oil in the same period.
The value of constant k is determined with the aim to protect the manufacturers, the value
of k is set equal to the floor price for all scenarios in each period. Values α generated in
this study are shown in the following table.
Tabel 6. Slope (α) of Natural Gas Price Formula
Scenario Period k α
1 2016-2020 3.77 0.1079
2021-2025 4.21 0.1039
2026-2030 4.79 0.1121
2 2016-2020 3.72 0.1137
2021-2025 4.19 0.1215
2026-2030 4.88 0.1261
3 2016-2020 3.65 0.1223
2021-2025 4.15 0.1463
2026-2030 5.38 0.1589
To determine the effect of the value of constant k and the slope α to the wholesale price
of natural gas, a sensitivity analysis is performed. The results of the sensitivity can be
seen in Figure 7. It can be seen that the wholesale price of natural gas is more sensitive to
the changes in the slope α compared to the constant changes of constant k. In other words,
changes in slope α will result a more significant decrease or increase in the wholesale
price of natural gas. It need to be considered in the negotiations of wholesale gas pricing
formula determination.
Figure 7 Sensitivity Analisis of Constant k and Slope α to Wholesale Gas Price – A. Scenario 1; B. Scenario 2; C. Scenario 3 – I. Period 2016-2020; II. Period
2021-2025; III. Period 2026-2030
150%
150%
50%
50%
7.00 9.00 11.00 13.00 15.00 17.00 19.00
konstanta k
slope α
Wholesale Price (USD/MMBTU)
A-I
150%
150%
50%
50%
7.00 9.00 11.00 13.00 15.00 17.00 19.00
konstanta k
slope α
Wholesale Price (USD/MMBTU)
A-II
150%
150%
50%
50%
9.00 11.00 13.00 15.00 17.00 19.00 21.00
konstanta k
slope α
Wholesale Price (USD/MMBTU)
A-III
150%
150%
50%
50%
7.00 9.00 11.00 13.00 15.00 17.00 19.00
konstanta k
slope α
Wholesale Price (USD/MMBTU)
B-I
150%
150%
50%
50%
7.00 9.00 11.00 13.00 15.00 17.00 19.00 21.00
konstanta k
slope α
Wholesale Price (USD/MMBTU)
B-II
150%
150%
50%
50%
9.00 11.00 13.00 15.00 17.00 19.00 21.00 23.00
konstanta k
slope α
Wholesale Price (USD/MMBTU)
B-III
150%
150%
50%
50%
7.00 9.00 11.00 13.00 15.00 17.00 19.00
konstanta k
slope α
Wholesale Price (USD/MMBTU)
C-I
150%
150%
50%
50%
7.00 9.00 11.00 13.00 15.00 17.00 19.00 21.00 23.00
konstanta k
slope α
Wholesale Price (USD/MMBTU)
C-II
150%
150%
50%
50%
11.00 16.00 21.00 26.00 31.00
konstanta k
slope α
Wholesale Price (USD/MMBTU)
C-III
4. Conclusion
Producer netback value from period to period decreased related to the increase in
throughput which affected by the inflation rate constant. The additional portion of LNG
imports volume giving an impairment in producer netback valueas because imports do
not provide added value for domestic producers. Social welfare value from period to
period increase influenced by the increase in projected crude oil price as an index of
energy substitution price.
The wholesale prices at the optimum point f1 and f2 higher from period to period. This is
caused by increasing of substitute energy prices associated with crude oil price projection
whose price continues to rise. In addition, it is also influenced by the increase in
transportation costs associated with inflation. The portion of the gas supply through LNG
growing along the period also become one of the factors increasing the wholesale price
of natural gas. The increase in the portion of the volume of LNG imports caused the
wholesale price of natural gas also increased because additional volume of imports did
not provide additional value to netback but still provide additional value to social welfare.
So that the intersection of the second objective function resulting a higher wholesale price.
At the optimum point between the social welfare of consumers and producers of natural
gas netback value, the wholesale price of natural gas is obtained which is then formulated
related to oil prices. Wholesale price formula of natural gas at the optimum point is
structured as a linear function of the price of crude oil price with slope α and the constant
k. α values is obtained in the range of 0.1079 to 0.1589 with k in the range of 3.7 to 5.38.
Reference
Arlen, Jennifer. (1986). Research Handbook on the Economics of Torts. Edward Elgar Publishing
Limited: Glos, UK.
Badan Pengkajian dan Penerapan Teknologi. (2014). Indonesia Energy Outlook 2014. Jakarta:
www.bppt.go.id
Badan Perencanaan Pembangunan Nasional. (2012). Laporan Akhir Kajian Percepatan Pembangunan
Industri Gas Bumi. Jakarta: www.bappenas.co.id
Beltramo, M.A., Manne, Allan S. dan Wyant, John P. (1986). A North American Gas Trade Model
(GTM). Energy Journal - Cambridge Ma then Cleveland Oh.
Bhattacharyya, S. C. (2011). Energy Economics. London: Springer.
BP Migas. (2009). Pedoman Tata Kerja No. 29/PTK/VII/2009 Penunjukan Penjual dan Penjualan Gas
Bumi/LNG/LPG Bagian Negara. Jakarta: www.skkmigas.go.id
BPH Migas. (2012). Infrastruktur Gas Jawa Bagian Barat. Jakarta: www.bphmigas.go.id
BPH Migas. (2013). Peraturan BPH Migas Nomor 8 tahun 2013: Penetapan Tarif
Pengangkutan Gas Bumi Melalui Pipa. Jakarta: www.bphmigas.go.id.
BPH Migas. (2014). Harga Gas Bumi Rumah Tangga dan Pelanggan Kecil Wilayah Jakarta. Jakarta:
www.bphmigas.go.id.
Caramia, M. dan Dell’Olmo, P. (2008). Multi-objective Management in Freight Logistics Increasing
Capacity, Service Level and Safety with Optimization Algorithms. London: Springer-Verlag.
Chyong, Chi Kong dan Hobbs, Benjamin F. (2014). Strategic Eurasian natural gas market model for
energy security and policy analysis: Formulation and application to South Stream. Energy
Economics, volume 44, p.198–211.
Direktorat Jenderal Minyak dan Gas. (2012). Infrastruktur Gas Pulau Jawa. Jakarta: www.esdm.go.id
Direktorat Jenderal Minyak Dan Gas Bumi. (2014). Kebijakan Alokasi Gas Bumi Untuk Dalam Negeri.
Jakarta: www.esdm.go.id.
Gas Market Study Task Force. (2013). SKM Gas Market Modelling. Melbourne: www.globalskm.com
Hartley, Peter dan Medlock III, Kenneth B. (2005). The Baker Institute World Gas Trade Model.
California: Stanford University.
Humphrey, Gerald. (2011). Current State & Outlook for the LNG Industry. Rice Global E&C Forum.
International Energy Agency. (2012). Gas Pricing and Regulation. www.iea.org.
International Gas Union. (2011). Wholesale Gas Price Formation - A global Review of Drivers and
Regional Trends. www.igu.org.
Investopedia. (2015). Consumer Surplus. http://www.investopedia.com/terms/c/consumer_ surplus.asp
Investopedia. (2015). Netback. http://www.investopedia.com/terms/n/netback.asp.
Jensen, James T.. (2012). International Natural Gas Pricing - A Challenge to Economic Modeling. A
Presentation to the Energy Information Administration. Washington
Kementrian Dalam Negeri Republik Indonesia. (2006). Peraturan Presiden No. 5 tahun 2006: Kebijakan
Energi Nasional. Jakarta: www.kemendagri.go.id.
Kementrian Energi dan Sumber Daya Mineral. (2010). Keputusan Menteri ESDM No.
0225.K/11/MEM/2010 tentang Rencana Induk Jaringan Transmisi dan Distribusi Gas Bumi
Nasional tahun 2010-2025. Jakarta: www.esdm.go.id.
Kementrian Energi dan Sumber Daya Mineral. (2010). Peraturan Menteri ESDM No. 03 Tahun 2010:
Alokasi dan Pemanfaatan Gas Bumi untuk Pemenuhan Kebutuhan Dalam Negeri. Jakarta:
www.esdm.go.id.
Kementerian Energi dan Sumber Daya Mineral. (2014). Peta Jalan Kebijakan Gas Bumi Nasional 2014-
2030. Jakarta: http://www.esdm.go.id.
Kumar, D. Nagesh. (2014). Optimization Methods: Linear Programming – Graphical Method. Lecture
Note. IISc: Bangalore.
Lewis, Richard. (2014). Gas Wholesale Supply and Pricing. Australian Institute of Energy Seminar.
Maulidiana, Mira. (2007). Permodelan Rantai Nilai LNG untuk Mengoptimalkan Nilai Gas bagi
Kepentingan dalam Negeri. Tesis S2, Program Studi Teknik Kimia, Fakultas Teknik, Universitas
Indonesia
Manuhutu, Chasty. (2007). Pemodelan Pasar Kompetitif ASEAN +3 untuk Perumusan Strategi Ekspor
Gas Bumi Indonesia. Tesis S2, Program Studi Teknik Kimia, Fakultas Teknik, Universitas
Indonesia.
Miettinen, Kaisa dan Deb, Kalyanmoy. (2008). Multiobjective Optimization: Interactive and Evolutionary
Approach. Springer Science & Business Media.
Perusahaan Gas Negara. (2012). Our Pricing Structure. Jakarta: www.pgn.co.id
Perusahaan Gas Negara. (2014). Natural Gas Outlook PGN 2014. Jakarta.
PricewaterhouseCoopers. (2011). Oil and Gas in Indonesia - Investment and Taxation Guide. Jakarta.
Putrohari, Rovicky. (2009). Skema Kontrak Bagi Hasil Produksi Migas Indonesia. Jakarta:
rovicky.wordpress.com
Rogres, Howard V. dan Stern, Jonathan. (2014). Challenges to JCC Pricing in Asian LNG Markets.
Oxford Institute for Energy Studies.
Recommended