Optimising Market Structure using Market Power Mitigation and
Forward Contract in Electricity Market Restructuring
Dzikri Hakam
Rafael “Manny” Macatangay
40th IAEE International Conference
Singapore, 18-21 June 2017
Centre for Energy, Petroleum and Mineral Law and Policy
University of Dundee
40th IAEE International Conference
Singapore, 18-21 June 2017
Introduction
Research Background
• One of the key components in creating
desirable features for market structure,
regulatory reform and the competitive
electricity market development is “to
create an adequate number of competing
generators to mitigate market power and
to ensure that wholesale markets are
reasonable competitive” (Joskow, 2008)
• Market power always occurs as a crucial
problem in electricity market design
(Borenstein, Bushnell, and Wolak 2002;
Wilson 2002; Wolak 2014). Thus, we
should mitigate the problem carefully
since the cure could be more dangerous
than the problem itself (Joskow 2008).
Consumer Surplus Loss
Transfer Surplus
Producer Surplus Loss
Figure 1. Welfare loss from quantity withholding
40th IAEE International Conference
Singapore, 18-21 June 2017
Introduction
Research gap
• A review of the literature on market power reveals that it is
dominated by corrective approach studies to minimise the
market power after the problem occurs, rather than studies of
preventive approaches to minimise the potential exercising of
market power.
• For countries in the early stages of electricity market
restructuring, a preventive approach to minimise the market
power exercise is crucial to deliver welfare maximisation to the
society, thus providing a possible shortcut on the exhausting
journey towards a competitive electricity market.
40th IAEE International Conference
Singapore, 18-21 June 2017
Introduction
Research Question: Assuming the unique topology of the electricity network, what is
the optimal market structure and generation technology mix in the electricity market
model under specific market strategic behaviours, assumptions and constraints to
minimise the exercise of market power by potential pivotal players?
Specific market
strategic behaviour
(Perfect Competition
and Cournot)
Economic
and Technic
Assumptions
Optimal market structure
and generation mix
technology
Unique
Electricity
Network
Network
Constraints
40th IAEE International Conference
Singapore, 18-21 June 2017
Introduction
Research Aim and Objective
The aim of this research is to optimise the mix and structure of
successor companies in electricity market restructuring
Our objective in this research is to develop a model for estimating
the optimal number and composition of successor companies, given
an initial set of base load, intermediate, or peaking generation plants
in different locations.
Deploying the IEEE generation and transmission test system, we
simulate nodal prices under perfect and Cournot competition, apply
the Residual Supply Index, which is a popular measure of market
power in restructured electricity markets, and assess the implications
of forward contracting.
40th IAEE International Conference
Singapore, 18-21 June 2017
Introduction: Research Scope and Limitations
Main limitations of research
•
•
•
•
•
•
•
•
•
•
Electricity as a commodity.
Interconnected power system.
Perfect competition and imperfect market (Cournot)
Spot market and forward trading.
Market power index calculation using Residual Supply Index.
Transmission congestion model.
Power system contingencies.
DC Load Flow and Kirchhoff law.
Peak load demand.
One power substation equal to one bus/node.
40th IAEE International Conference
Singapore, 18-21 June 2017
Literature review
Why optimise the market : Literature Review from selected studies
SUBOPTIMAL : DAMAGE LOSS
MARKET POWER STUDY
ANTITRUST LAW/POLICY
OPTIMISING MARKET
 Wolak (2014) : Market price subjected to
 Green and Newberry (1992): deadweight
market power
loss £262 million higher compare to 5 equal
 Joskow (2008) : “…Try to deal with potential
companies in UK
market power structurally ex ante rather
 Arrelano (2003): Electricity price increase
than ex post.”
60% compare to competitive benchmark in
 Sheffrin (2001) : market share less than
Chilean market
10% in California crisis
PAPER
 Macatangay (2001): Heart of antitrust
analysis : Market power
 Stigler(1955) : Corrective Vs Preventive
 Joskow (2002) : US Corrective Law
 Green (2009) : EU Corrective approach
(merger policy)
 Joskow (2008) : adequate numbers of
competing generator
 Green (1996) : Sufficient competition for
each type of power plant
 Borenstein (2000); Cunningham (2002): T/L
affect market power
40th IAEE International Conference
Singapore, 18-21 June 2017
Methodology
Research Methods
No
Selected Method
1
• Strategic
Behaviour
2
• System
Modelling
3
• Market power
Index
Si, HHI
• Application
Small
system
4
Selected Study
Cournot
LMP
SFE
Peak
Load
DC Load
Flow
Available
Capacity
PCM, LI
Large scale
40th IAEE International Conference
Singapore, 18-21 June 2017
RSI
Borenstein et al, 2000
Cunningham, 2002
Schweppe et al (1998)
Sheffrin, 2002;
Newberry, 2009; London
Economics, 2007
Macatangay, 1998;
Green, 2007
Methodology
Market power index using Residual Supply Index
𝒌𝑻 − 𝒌𝒊
𝑹𝑺𝑰𝒊 =
𝑸
Q = electricity demand; is metered load plus purchased ancillary services
k i = generation capacity minus contract obligation of firm i
k T = total generation capacity in the market plus total net imports
 Generator’s residual demand curve as market power indicator
 Incorporate market demand
 Suitable for dynamic analysis (hour to hour)
 Applicable for local and integrated market analysis
Screening Sample : Exceeding 110 % for more than 95% of hour in a year
(Sheffrin, 2002).
Reasonable competitive market : 120-150 % (Rahimi and Sheffrin, 2003)
40th IAEE International Conference
Singapore, 18-21 June 2017
Methodology
Residual Supply Index as Market power mitigation
Source: Sheffrin, 2002
40th IAEE International Conference
Singapore, 18-21 June 2017
Data Simulation
Case Study IEEE 30 bus
Initial market configuration
is 13 PPs with total capacity
1,530 MW.
Type
Base
Intermediate
Peaking
PP
Coal PP
Gas
Diesel
𝑐𝑖
30
35
40
𝑑𝑖
0.1
0.15
0.2
354 possible
Configurations
40th IAEE International Conference
Singapore, 18-21 June 2017
Case 1 Load Flow
Case Study IEEE 30 bus
Constrained transmission
No
1
2
3
From 𝑖
9
12
14
To 𝑗
10
13
15
𝑃𝑖𝑗 𝐷𝐶 (MW)
Case 1: Constrained
65
transmission
-65
64
40th IAEE International Conference
Singapore, 18-21 June 2017
1+2
1+8
1+13
1+18
1+23
2+3+15
2+11+30
2+14
2+22
2+27
3+15+11+30
3+15+14
3+15+22
3+15+27
8+13
8+18
8+23
11+30+13
11+30+18
11+30+23
13+14
13+22
13+27
14+22
14+27
18+23
22+23
23+27
1.2
Market Power (RSI) - 10 Firms
1.50
1.45
1.45
1.40
1.40
1.35
1.35
1.30
1.30
1.25
1.25
1.20
1.20
1.15
40th IAEE International Conference
Singapore, 18-21 June 2017
2+8
2+27
Market Power (RSI) - 9 Firms
22+27
18+27
18+22
15+23
15+18
14+23
14+18
13+27
13+22
13+15
11+30+27
11+30+22
11+30+15
11+30+13
8+23
8+18
8+14
8+11+30
3+23
3+18
3+14
3+11+30
Market Power (RSI) - 12 Firms
2+22
2+15
1.3
2+13
1.35
1+27
1.45
1+22
1.45
1+15
1.50
1+8
1.5
1+13
1.4
1+2
23+30
22+30
22+23
18+27
18+22
15+27
15+22
14+30
14+23
14+18
13+30
13+23
13+18
13+14
11+27
11+22
11+15
11+13
8+27
8+22
8+15
8+13
3+30
3+23
3+18
3+14
3+11
2+30
2+23
2+18
2+14
2+11
2+3
1+27
1+22
1+15
1+13
1+8
1+2
Result and Analysis : Case 1
Perfect competition, normal operation (Transmission Constrained)
Market Power (RSI) - 11 Firms
1.40
1.35
1.30
1.25
1.25
1.20
14+22
13+27+22
13+27+14
11+30+23+22
11+30+23+14
11+30+23+13+27
3+15+8+22
3+15+8+14
3+15+8+13+27
3+15+8+11+30+23
2+22
2+14
2+13+27
2+11+30+23
2+3+15+8
1+18+22
1+18+14
1+18+13+27
1+18+11+30+23
1+18+3+15+8
1+18+2
1+18+2
22+23
14+23
14+22
13+27+23
13+27+22
13+27+14
11+30+23
11+30+22
11+30+14
11+30+13+27
8+23
8+22
8+14
8+13+27
8+11+30
3+15+23
3+15+22
3+15+14
3+15+13+27
3+15+11+30
3+15+8
2+23
2+22
2+14
2+13+27
2+11+30
2+8
2+3+15
1+18+23
1+18+22
1+18+14
1+18+13+27
1+18+11+30
1+18+8
1+18+3+15
Result and Analysis : Case 1
Perfect competition, normal operation (Transmission Constrained)
1.45
Market Power (RSI) - 8 Firms
Market Power (RSI) - 7 Firms
1.40
1.60
1.35
1.40
1.20
1.30
1.00
0.80
1.25
0.60
1.20
0.40
1.15
0.20
0.00
1.10
Market Power (RSI) - 6 Firms
Market Power (RSI) - 5 Firms
1.60
1.40
1.20
1.00
0.80
0.60
0.40
0.20
0.00
1.40
1.20
1.00
0.80
0.60
0.40
0.20
0.00
40th IAEE International Conference
Singapore, 18-21 June 2017
Result and Analysis : Case 1
Perfect competition, normal operation (Transmission Constrained)
Optimal Market Structure
RSI
1.600
1.400
1.200
1.000
0.800
RSI
0.600
0.400
0.200
0.000
12
11
10
9
8
7
6
5
4
Number
of Firms
Number of Firms
12
11
10
9
8
7
6
5
4
RSI
1.484
1.483
1.480
1.433
1.388
1.363
1.346
1.244
1.110
Configuration
11Merge30
3Merge15
1Merge18
13Merge27
3+15Merge8
11+30Merge23
14Merge22
1+18Merge2
3+15+8Merge13+27
• The market structure with four players configuration creates a market structure with RSI
below the threshold level.
• Merger step taken by power producer to create optimal market structure was determined
not only by generation technology mix in firms but also determined by installed capacity
post-merger.
• Creating optimal electricity market structure using RSI and merger analysis is an approach to
creating competition between generation technology in particular firm, and also to spread
big size (pivotal) power plant among competitive players.
40th IAEE International Conference
Singapore, 18-21 June 2017
Case 2 Load Flow
Case Study IEEE 30 bus
Unconstrained transmission
40th IAEE International Conference
Singapore, 18-21 June 2017
Result and Analysis : Case 2
Perfect competition, Transmission unconstrained
Optimal Market Structure
RSI
1.600
1.400
1.200
1.000
0.800
RSI
0.600
0.400
0.200
0.000
12
11
10
9
8
7
6
5
4
Number
of Firms
Number of Firms
12
11
10
9
8
7
6
5
4
RSI
1.483
1.482
1.479
1.431
1.386
1.362
1.347
1.244
1.110
Configuration
11Merge30
3Merge15
1Merge18
13Merge27
3+15Merge8
11+30Merge23
14Merge22
1+18Merge2
3+15+8Merge13+27
• Due to transmission congestion, local power producers with low marginal cost in a specific
region could not maximise its cheap power transfer to other areas. This network constraints
resulted in market power, higher electricity price, and lower welfare.
• The transmission congestions in the three congested lines are not severe. Thus, the optimal
market structure in case 1 (constrained) and case 2 (unconstrained) are similar. There are no
differences in firm’s configuration although there is a slight deviation in market power index
between the two cases.
40th IAEE International Conference
Singapore, 18-21 June 2017
Case 3 Load Flow
Case Study IEEE 30 bus
Contingency N-1
Line 9-10 fault
40th IAEE International Conference
Singapore, 18-21 June 2017
Result and Analysis : Case 3
Contingency n-1: Transmission line fault on line 9-10
Optimal Market Structure
RSI
1.800
1.600
1.400
1.200
1.000
RSI
0.800
0.600
0.400
0.200
0.000
12
11
10
9
8
7
6
5
4
Number
of Firms
Number of Firms
12
11
10
9
8
7
6
5
4
RSI Configuration
1.569
27Merge30
1.569
1Merge3
1.601
15Merge18
1.539
8Merge11
1.479
1+3Merge27+30
1.478
22Merge23
1.435
13Merge14
1.313
2Merge15+18
1.164
8+11Merge13+14
• The transmission line fault on line 9-10 causes power system bottleneck.
• The system outages occur when the load flow exceeds its transfer limit and
damage the cable.
• Different merge pattern in case 3 (Contingency N-1) compared to case 1 and
case 2.
40th IAEE International Conference
Singapore, 18-21 June 2017
Result and Analysis : Case 4
Cournot modelling in network Unconstrained
Number of Firms
12
11
10
9
8
7
6
5
4
RSI
1.593
1.590
1.585
1.535
1.519
1.457
1.405
1.332
1.223
Configuration
15Merge30
1Merge18
3Merge15+30
13Merge27
8Merge11
22Merge23
3+15+30Merge14
1+18Merge2
8+11Merge13+27
• Numerical simulation in Cournot case study creates a slightly different optimal market
structure compared to perfect competition scenario.
• The minimum player needed to create reasonable competitive electricity market is four
players with RSI 1.223.
• Market configuration with player participation below 4 resulted in potential market power
exercise that below the index threshold 1.2.
40th IAEE International Conference
Singapore, 18-21 June 2017
Result and Analysis : Forward Contract
Cournot modelling in network Unconstrained
• Cournot model is a suitable model
to analysed market equilibrium
incorporating forward contract as a
portion of installed capacity.
• By applying contract coverage, the
electricity market resulted in lower
market power exercise.
• We
can
create
competitive
electricity market above the market
power index threshold with less
player participant by applying the
forward contract as an instrument
to reduce market power level.
Contract Coverage and Market Power
RSI
1.85
1.80
1.75
1.70
1.65
1.60
Contract
1.55
0%
10%
20%
40th IAEE International Conference
Singapore, 18-21 June 2017
30%
40%
50%
60%
70%
80%
90%
100%
Discussions
Contributions and future research
• This research applied a preventive approach, rather than a corrective approach,
in creating optimal successor companies prior to electricity market
restructuring.
• This study employs a multi-disciplinary approach, e.g. microeconomic, power
engineering, law and policy, and math.
• The insights gained for generating an efficient number of competing generators
in the early steps of electricity market restructuring under a large-scale network,
specific strategic market behaviours, specific power system constraints, and
market power mitigation.
• The modelling and conceptual algorithm in this research could be implemented
trans-nationally in electricity markets that remain in a state of monopoly,
considering the uniqueness of the power system topology.
40th IAEE International Conference
Singapore, 18-21 June 2017
Optimising Market Structure using Market Power Mitigation and
Forward Contract in Electricity Market Restructuring
This research is fully sponsored by Indonesia Endowment Fund
for Education (LPDP) and supported by PLN
Centre for Energy, Petroleum and Mineral Law and Policy
University of Dundee
40th IAEE International Conference
Singapore, 18-21 June 2017
Dzikri Firmansyah Hakam
Work Experience :
• Halliburton, International Oil Service Company
• Indonesia Energy and Mineral Resources Ministry, Electricity
Directorate
• PT. PLN P3B Sumatra, Power System Dispatch Centre
• CG Transformer, Multinational Transformer Manufacturer
• PT. PLN Head Office, Oil and Gas Division, Indonesia State Owned
Electricity Company (Present)
Education:
• B.E. Power Engineering, Institut Teknologi Bandung
• MSc International Oil and Gas Management, CEPMLP, University of
Dundee
• PhD Researcher, CEPMLP, University of Dundee
40th IAEE International Conference
Singapore, 18-21 June 2017
Introduction
Presentation Structure
1. Introduction
2.Literature
Review
3. Methodology
4. Result and
Analysis
• Research Background, Gap, Questions
• Research Aim and objective
• Research Scope and imitations
• Suboptimal market structure: Damage Loss
• Market power study
• Antitrust law and policy
• Optimising electricity market structure
• Conceptual Framework
• Research Method
• Algorithm
• Data Simulation
• Case 1: nodal, Normal operation, congested trans
• Case 2: nodal, Unconstrained transmission
• Case 3: nodal, Contingency n-1, trans fault line 9-10
• Case 4: Cournot, Unconstrained Network
5. Conclusion
40th IAEE International Conference
Singapore, 18-21 June 2017
Introduction : Research Background
Successor Companies : the companies created from the
breakdown of monopoly Generation Company.
Monopoly GENCO
Wholesale
Market
Retail
Market
Purchasing
Agency
Monopoly
Successor Companies
Source : Adapted from Hunt and Shuttleworth (1996) and Kirschen and Strbac (2004)
40th IAEE International Conference
Singapore, 18-21 June 2017
Introduction
Research focus : GenCo Breakdown in electricity market reform
GenCo
GenCo
TransCo
TransCo
DisCo
DisCo
Distribution
Consumer
Consumer
Consumer
Own Generator
IPP
Model 1. Monopoly
Wholesale Purchasing
Agency
Model 2. Purchasing Agency
Source : Hunt and Shuttleworth (1996) and Kirschen and Strbac (2004)
40th IAEE International Conference
Singapore, 18-21 June 2017
IPP
Introduction
Research focus : GenCo Breakdown in electricity market reform
GenCo
GenCo
GenCo
GenCo
GenCo
Consumer
DisCo
DisCo
Consumer
GenCo
GenCo
Wholesale Market
Transmission System
Wholesale Market
Transmission System
DisCo
GenCo
Large
Consumer
Retailer
Retailer
Large
Consumer
Retail Market
Distribution System
Consumer
Model 3. Wholesale Market
Retailer
Consumer
Consumer
Consumer
Model 4. Retail market
Source : Hunt and Shuttleworth (1996) and Kirschen and Strbac (2004)
40th IAEE International Conference
Singapore, 18-21 June 2017
Introduction
Research challenges
SUMATRA POWER SYSTEM (2015)
Krueng Raya
Banda Aceh
Sigli
Bireueun
Jantho
Lhokseumawe
P.Labu
Seulawah Geo
Idie
PLTA
Peusangan
Talang Cut
Takengon
PLTU
P.Susu
Langsa
Meulaboh
P.Brandan
Binjai
Th.2011
Blang Pidie
ACEH
225,3 MW
P.Geli
Namorambe
Kuta Cane
PLTGU
Belawan
P.Pasir
Mabar Belawan
KIM
Glugur
Titi Kuning
Labuhan
Sei.Rotan
PLTU
Sumut
Lamhotma
Perbaungan
Denai
T.Morowa
Brastagi
Galang
Kisaran
G.Para
Th.2010
Sidikalang
P.Siantar
Porsea
Sabulusalam
PLTA
Asahan 3
Peak Load: 1653,5 MW
- Model the large scale
power system to
granular model,
compare with real time
load flow
- Calculate all possible
power plant
merger/combination
- Line connection
determines market
boundaries and market
power exercise
Sipan HPP
PLTU
L.Angin
Labuhan Bilik
Malaka
R.Prapat
Tarutung
Simangkok
PLTP
Sarula
TNB
Malaysia
Aek Kanopan
Tele
North Sumatra
SUMUT
1325,3 MW
K.Tanjung
T.Tinggi
Tapak Tuan
Bagan Siapi-api
PLTA
Asahan I
Dumai
K.Pinang
RIAU
438,5 MW
G.Tua
Sibolga
Duri
Panyabungan
Bagan Batu
Garuda
Sakti
Pd. Sidempuan
S.Pangarayan
Teluk
Lembu
Bangkinang
New Garuda
Sakti
Th.2011
Th.2010
Simpang 4
Payakumbuh
Kulim
Kt.Panjang
HPP
P.Kerinci
Tembilahan
Pd. Luar
Maninjau HPP
Singkarak
HPP
Lubuk Alung
Pariaman
Pd.Panjang
Ombilin
Indarung
Solok
S.Haru
Middle Sumatra
Bungus
JAMBI
227,0 MW
T.Kuantan
PIP
Pauh Limo
Rengat
Th.2010
Batusangkar
Salak
PLTU
Cirenti
Kiliranjao
PLTU
Sumbar Pessel
Payo
Selincah
Aur Duri
Muara Bulian
Muara bungo
Peak Load: 1093,5 MW
S.Penuh
S.Lilin
Sarolangun
Bangko
SUMBAR
430,0 MW
SUMSEL
696,4 MW
Bayung Lincir
Kambang
Merangin HPP
PLTU
Banyuasin
Tl.Kelapa
PLTG Kaji
Mukomuko
BENGKULU
98,8 MW
Musi HPP
Bukit
Asam
Mariana
Simpang 3
Prabumulih
PLTG
G.Megang
Lahat
Curup
Sukamerindu
Excess Power
PERTAMINA+PUSRI
(2001)
Keramasan
Bangko
Tengah
Lubuk Linggau
Borang
Betung
PLTU Musi Rawas
Tes HPP
1. PLTG Apung
2. PLTG Ex Pulo Gadung
3. IPP Palembang Timur
Kayu Agung
Th.2012
PLTU
Banjarsari
Gumawang
Pagar
Alam
S. Pematang
Sp. Banyak
Baturaja
Menggala
B.Umpu
Manna
South Sumatra
Peak Load: 1395,6 MW
Sukadana
Bukit Kemuning
B.Agung
Krui
Besai HPP
B.Tegi HPP
Ulubelu Geo
40th IAEE International Conference
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Metro
Tegineneng
Adijaya
Natar
Sukarame
Tl. Betung
Pagelaran
Kota Agung
LAMPUNG
600,4 MW
Sribawono
Kotabumi
Tl. Ratai
Sutami
New Tarahan
Tarahan
Kalianda
Bakauheni
Th.2012
Sistem
JAWA
Methodology
Conceptual framework
40th IAEE International Conference
Singapore, 18-21 June 2017
Methodology: Algorithm
Conceptual algorithm for optimal market structure
Step 1: Power system modelling
INPUT DATA *
Power System
modelling
Identify Market constraints:
Transmission limit,
generation capacity
Define market
characteristics: Line,
load, energy mix, RM
Determine Market Equilibrium : Price and Quantity
Determine RSI
Step 2. Calibration
40th IAEE International Conference
Singapore, 18-21 June 2017
Isolated
system :
Separated
market,
individual
demand
Solve for
each
isolated
market
Interconnected : Market
combining, demand
aggregation
Methodology: Algorithm
Conceptual algorithm for optimal market structure
Step 2: Data calibration
Step 1
Calibration :
Data from ISO/TSO/
dispatch centre
- Demand
- Generation
- Power transfer
Choose suitable values of 𝛼 ,𝛽 , c and d.
Compute q, Q and T for each node and line
Evaluate the results.
Compare with load flow realisation; adjust
reactance, 𝛼 ,𝛽 , c and d.
Reach a
best
accuracy
YES
NO
Step 3. Power plant merger analysis
40th IAEE International Conference
Singapore, 18-21 June 2017
Methodology: Algorithm
Conceptual algorithm for optimal market structure
Step 3 and 4: Power plant merger analysis and market screening
Step 2
Identify Initial Generation
structure
Step 3
Power Plant
Merger
Analysis
Determine possible
market structure
Perform multi plant monopoly
analysis, cost combining
Optimal market structure
Determined the highest RSI
YES
Step 4
Market
Power
Assessment
40th IAEE International Conference
Singapore, 18-21 June 2017
NO
RSI >
1.2
Potential market
power exercise
Methodology
DC Load flow according to Kirchhoff Law
200 MW
100 MW
Electricity Inflow = Electricity Outflow
100 + 250 + 200 = 300 + 200 + 50
50 MW
300 MW
NODE
250 MW
200 MW
Export/Outflow (negative)
Import/Inflow (positive)
• Node as Substation, City,
Country or Continent
• Net power transfer = Inflow Outflow
• Power Transfer influences
market power index
40th IAEE International Conference
Singapore, 18-21 June 2017
Theoretical Model
Nodal pricing : Objective function and constraints
Objective
𝑚𝑎𝑥
𝑞𝑑𝑖
𝑃𝑖 𝑞𝑑𝑖 𝑞𝑑𝑖 −
𝑖
𝑀𝐶𝑖 𝑞𝑠𝑖
𝑖
𝑞𝑠𝑖 −
𝑖
𝑞𝑑𝑖 = 0
Electricity demand balance
𝑖
𝑃𝑇𝐷𝐹 𝑞𝑠𝑖 − 𝑞𝑑𝑖 ≤ 𝑇𝑙
𝑙
Constraints
Welfare maximisation
−𝑇𝑙 ≤
Transmission constraint
DC Load Flow
𝑃𝑇𝐷𝐹( 𝑞𝑠𝑖 − 𝑞𝑑𝑖
𝑙
𝑞𝑠𝑖 ≤ 𝑞𝑠𝑖
𝑞𝑑𝑖 > 0
𝑞𝑠𝑖 > 0
40th IAEE International Conference
Singapore, 18-21 June 2017
Generation constraint
Non negativity
Theoretical Model
Model 1: One node, 1 LSE, 4 power plants ala Cournot
“Market power as a function of demand and marginal cost”
G1
G3
G2
G4
Marginal cost
𝑀𝐶𝑖 𝑞𝑠𝑖 = 𝑐𝑖 + 𝑑𝑖 𝑞𝑠𝑖 ; 𝑖 = 1, … , 𝐼
Linear demand
𝑝𝑖 𝑞𝑑𝑖 = 𝑎𝑖 − 𝑏𝑖 𝑞𝑑𝑖 ; 𝑖 = 1, … , 𝐼
A
Total demand
𝑃(𝑄 = 𝛼 − 𝛽𝑄
LSE
Solve FOC (First Order
Condition) for
Cournot Matrix equation:
2𝛽 + 𝑑1
𝛽
𝛽
𝛽
𝛽
2𝛽 + 𝑑2
𝛽
𝛽
40th IAEE International Conference
Singapore, 18-21 June 2017
𝛽
𝛽
2𝛽 + 𝑑3
𝛽
𝛽
𝛽
𝛽
2𝛽 + 𝑑4
𝑞1
𝛼 − 𝑐1
𝑞2
𝛼 − 𝑐2
=
𝑞3
𝛼 − 𝑐3
𝑞4
𝛼 − 𝑐4
Theoretical Model
Model 2: Two node, 2 LSE, 4 power plants ala Cournot Isolated
“No Transmission line : Solve for each isolated power system”
G2
G1
G4
G3
Solve Node A:
2𝛽𝐴 + 𝑑1
𝛽𝐴
A
B
Solve Node B:
2𝛽𝐵 + 𝑑3
𝛽𝐵
LSE 1
𝑞1𝐴
𝛼𝐴 − 𝑐1
𝛽𝐴
= 𝛼 −𝑐
2𝛽𝐴 + 𝑑2 𝑞2𝐴
𝐴
2
𝑞3𝐵
𝛼𝐵 − 𝑐3
𝛽𝐵
= 𝛼 −𝑐
2𝛽𝐵 + 𝑑4 𝑞4𝐵
𝐵
4
LSE 2
𝑥1𝐴 𝑥2𝐴 − 𝛽𝐴 2
𝑅𝑆𝐼𝐴 = 1 − 𝑘𝑚𝑎𝑥
𝑥1𝐴 𝑦2𝐴 + 𝑥2𝐴 𝑦1𝐴 − 𝛽𝐴 (𝑦1𝐴 + 𝑦2𝐴
𝑥3𝐵 𝑥4𝐵 − 𝛽𝐵 2
𝑅𝑆𝐼𝐵 = 1 − 𝑘𝑚𝑎𝑥
𝑥3𝐵 𝑦4𝐵 + 𝑥4𝐵 𝑦3𝐵 − 𝛽𝐵 𝑦3𝐵 + 𝑦4𝐵
40th IAEE International Conference
Singapore, 18-21 June 2017
Theoretical Model
Model 3: Two node, 2 LSE, 4 power plants Cournot Interconnected
“Line connection determines market boundaries, thus influences the
market power index”
G2
G1
A
T
2𝛽𝐴𝐵 + 𝑑1
𝛽𝐴𝐵
𝛽𝐴𝐵
𝛽𝐴𝐵
B
LSE 2
LSE 1
Solve FOC
Cournot :
G4
G3
𝛽𝐴𝐵
2𝛽 + 𝑑2
𝛽𝐴𝐵
𝛽𝐴𝐵
𝛽𝐴𝐵
𝛽𝐴𝐵
2𝛽𝐴𝐵 + 𝑑3
𝛽𝐴𝐵
40th IAEE International Conference
Singapore, 18-21 June 2017
𝛽𝐴𝐵
𝛽𝐴𝐵
𝛽𝐴𝐵
2𝛽𝐴𝐵 + 𝑑4
𝑞1𝐴𝐵
𝛼𝐴𝐵
𝑞2𝐴𝐵
𝛼𝐴𝐵
=
𝑞3𝐴𝐵
𝛼𝐴𝐵
𝑞4𝐴𝐵
𝛼𝐴𝐵
− 𝑐1
− 𝑐2
− 𝑐3
− 𝑐4
Theoretical Model
Model 4 : Merger Analysis
Node
a
Firm 1-2
Firm 1-2
Firm 3
Firm 4
1
2
3
4
b
Firm 1-3
Firm 2
Firm 1-3
Firm 4
Market Structure
c
d
Firm 1-4
Firm 1
Firm 2
Firm 2-3
Firm 3
Firm 2-3
Firm 1-4
Firm 4
e
Firm 1
Firm 2-4
Firm 3
Firm 2-4
f
Firm 1
Firm 2
Firm 3-4
Firm 3-4
Firm 1
Firm 1
A
Firm 3
G4
Firm 2
G3
G2
G1
T
B
Firm 2
G2
G1
A
T
B
Configuration b
Configuration a
LSE 1
Firm 3
G4
G3
LSE 2
LSE 1
40th IAEE International Conference
Singapore, 18-21 June 2017
LSE 2
Theoretical Model
Model 4 : Merger Analysis
Firm 1
Firm 3
G3
Firm 2
G2
G1
A
Firm 2
G4
Firm 1
G1
A
B
T
G2
Firm 2
G1
A
Configuration d
LSE 2
Firm 2
T
Firm 3
Firm 2
G2
G4
G3
G4
A
B
T
B
Configuration f
Configuration e
LSE 1
LSE 2
LSE 1
Firm 2
G1
Firm 3
G3
G2
B
T
Configuration c
LSE 1
G3
Firm 3
G4
LSE 2
LSE 1
40th IAEE International Conference
Singapore, 18-21 June 2017
LSE 2
Data Simulation : Generation and demand
Installed capacity and node demand
n
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
𝑘𝑖
(MW)
100
200
50
0
0
0
0
130
0
0
120
0
120
160
100
𝑞𝑑𝑖
(MW)
10
0
20
0
85
0
50
25
0
190
0
50
20
50
50
n
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
(MW)
𝑘𝑖
0
0
100
0
0
0
150
150
0
0
0
120
0
0
30
40th IAEE International Conference
Singapore, 18-21 June 2017
𝑞𝑑𝑖
(MW)
9
0
35
17
60
34
0
85
9
9
0
0
27
35
0
Data Simulation :
Transmission line characteristics
from 𝑖
1
1
2
3
2
2
4
5
6
6
6
6
9
9
4
12
12
12
12
14
16
to 𝑗
2
3
4
4
5
6
6
7
7
8
9
10
11
10
12
13
14
15
16
15
17
𝑋𝑖𝑗 (p.u)
0.06
0.19
0.17
0.04
0.2
0.18
0.04
0.12
0.08
0.04
0.21
0.56
0.21
0.11
0.26
0.14
0.26
0.13
0.2
0.2
0.19
𝑇𝑙 (MW)
130
130
65
130
130
90
90
140
130
132
96
96
65
65
65
65
64
132
64
64
100
from 𝑖
15
18
19
10
10
10
10
21
15
22
23
24
25
25
28
27
27
29
8
6
to 𝑗
18
19
20
20
17
21
22
22
23
24
24
25
26
27
27
29
30
30
28
28
40th IAEE International Conference
Singapore, 18-21 June 2017
𝑋𝑖𝑗 (p.u)
0.22
0.13
0.07
0.21
0.08
0.07
0.15
0.02
0.2
0.18
0.27
0.33
0.38
0.21
0.4
0.42
0.6
0.45
0.2
0.06
𝑇𝑙 (MW)
100
100
132
64
64
64
64
64
64
96
100
64
130
65
65
64
64
18
32
32
Result and Analysis : Case 2
Perfect competition, Transmission unconstrained
Market Power (RSI) - 12 Firms
Market Power (RSI) - 11 Firms
1.5
1.50
1.45
1.45
1.4
1.40
1.35
1.35
1.30
1.3
1.25
1.25
1.20
23-30
22-30
22-23
18-27
18-22
15-27
15-22
14-30
14-23
14-18
13-30
13-23
13-18
13-14
11-27
11-22
11-15
8-27
11-13
8-22
8-15
8-13
3-30
3-23
3-18
3-14
3-11
2-30
2-23
2-18
2-14
2-3
2-11
1-27
1-22
1-15
1-8
1-13
1-2
1.2
Market Power (RSI) - 10 Firms
Market Power (RSI) - 9 Firms
1.50
1.45
1.45
1.40
1.40
1.35
1.35
1.30
1.30
1.25
1.25
1.20
1+2
1+8
1+13
1+18
1+23
2+3+15
2+11+30
2+14
2+22
2+27
3+15+11+30
3+15+14
3+15+22
3+15+27
8+13
8+18
8+23
11+30+13
11+30+18
11+30+23
13+14
13+22
13+27
14+22
14+27
18+23
22+23
23+27
1.20
1.15
40th IAEE International Conference
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14+22
13+27+22
13+27+14
11+30+23+22
11+30+23+14
11+30+23+13+27
3+15+8+22
3+15+8+14
3+15+8+13+27
3+15+8+11+30+23
2+22
2+14
2+13+27
2+11+30+23
2+3+15+8
1+18+22
1+18+14
1+18+13+27
1+18+11+30+23
1+18+3+15+8
1+18+2
1+18+2
22+23
14+23
14+22
13+27+23
13+27+22
13+27+14
11+30+23
11+30+22
11+30+14
11+30+13+27
8+23
8+22
8+14
8+13+27
8+11+30
3+15+23
3+15+22
3+15+14
3+15+13+27
3+15+11+30
3+15+8
2+23
2+22
2+14
2+13+27
2+11+30
2+8
2+3+15
1+18+23
1+18+22
1+18+14
1+18+13+27
1+18+11+30
1+18+8
1+18+3+15
Result and Analysis : Case 2
Perfect competition, Transmission unconstrained
1.40
Market Power (RSI) - 8 Firms
Market Power (RSI) - 7 Firms
1.35
1.60
1.40
1.30
1.20
1.00
1.25
0.80
1.20
0.60
0.40
1.15
0.20
0.00
1.10
Market Power (RSI) - 6 Firms
Market Power (RSI) - 5 Firms
1.60
1.40
1.20
1.00
0.80
0.60
0.40
0.20
0.00
1.40
1.20
1.00
0.80
0.60
0.40
0.20
0.00
40th IAEE International Conference
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1+3+2
1+3+11
1+3+14
1+3+18
1+3+23
2+8
2+13
2+15
2+22
2+27+30
8+13
8+15
8+22
8+27+30
11+14
11+18
11+23
13+14
13+18
13+23
14+15
14+22
14+27+30
15+22
15+27+30
18+23
22+23
23+27+30
1.5
1.45
1.4
1.25
1.65
1.25
1+2
1+8
1+13
1+15
1+22
1+27+30
2+8
2+13
2+15
2+22
2+27+30
3+11
3+14
3+18
3+23
8+11
8+14
8+18
8+23
11+13
11+15
11+22
11+27+30
13+15
13+22
13+27+30
14+18
14+23
15+18
15+23
18+22
18+27+30
22+27+30
23+30
22+30
22+23
18+27
18+22
15+27
15+22
14+30
14+23
14+18
13+30
13+23
13+18
13+14
11+27
11+22
11+15
11+13
8+27
8+22
8+15
8+13
3+30
3+23
3+18
3+14
3+11
2+30
2+23
2+18
2+14
2+11
2+3
1+27
1+22
1+15
1+13
1+8
1+2
Result and Analysis : Case 3
Contingency n-1: Transmission line fault on line 9-10
1.6
Market Power (RSI) - 12 Firms
1.60
Market Power (RSI) - 11 Firms
1.55
1.55
1.50
1.45
1.40
1.35
1.35
1.3
1.30
1.25
Market Power (RSI) - 10 Firms
1.60
Market Power (RSI) - 9 Firms
1.60
1.55
1.55
1.50
1.50
1.45
1.45
1.40
1.40
1.35
1.35
1.30
1.30
1.25
1.20
40th IAEE International Conference
Singapore, 18-21 June 2017
1+3+27+30+2
15+18+22+23
14+22+23
14+15+18
13+22+23
13+15+18
13+14
8+11+22+23
8+11+15+18
8+11+14
8+11+13
2+22+23
2+15+18
2+14
2+13
2+8+11
1+3+27+30+22+23
1+3+27+30+15+18
1+3+27+30+14
1+3+27+30+13
1+3+27+30+8+11
1+3+2
23+27+30
22+27+30
22+23
15+18+27+30
15+18+23
15+18+22
14+27+30
14+23
14+22
14+15+18
13+27+30
13+23
13+22
13+15+18
13+14
8+11+27+30
8+11+23
8+11+22
8+11+15+18
8+11+14
8+11+13
2+27+30
2+23
2+22
2+15+18
2+14
2+13
2+8+11
1+3+27+30
1+3+23
1+3+22
1+3+15+18
1+3+14
1+3+13
1+3+8+11
Result and Analysis : Case 3
Contingency n-1: Transmission line fault on line 9-10
1.50
Market Power (RSI) - 8 Firms
Market Power (RSI) - 7 Firms
1.45
1.60
1.40
1.40
1.20
1.00
1.35
0.80
0.60
1.30
0.40
0.20
1.25
0.00
1.20
Market Power (RSI) - 6 Firms
Market Power (RSI) - 5 Firms
1.60
1.40
1.20
1.00
0.80
0.60
0.40
0.20
0.00
1.40
1.20
1.00
0.80
0.60
0.40
0.20
0.00
40th IAEE International Conference
Singapore, 18-21 June 2017
Result and Analysis : Case 4
Cournot modelling in network unconstrained
Market Power (RSI) - 9 Firms
1.55
1.50
1.45
1.40
1.35
1.30
1.25
1.20
40th IAEE International Conference
Singapore, 18-21 June 2017
Result and Analysis : Case 4
Cournot modelling in network unconstrained
Market Power (RSI) - 5 Firms
1.40
1.20
1.00
0.80
0.60
0.40
0.20
0.00
40th IAEE International Conference
Singapore, 18-21 June 2017
Model application: large scale power system
Case: Indonesia power system (Sumatra system)
ACEH
SUMUT
South Sumatra
Subsystem
RIAU
SUMBAR
Mid Sumatra
Subsystem
JAMBI
SUMSEL
South Sumatra
Subsystem
40th IAEE International Conference
Singapore, 18-21 June 2017
BENGKULU
Future
research
LAMPUNG
Future
research
Model application: large scale power system
Case: Indonesia power system (Java Bali system)
TANJUNG
JATI
BEKASI
SURALAYA
CILEGON
GRESIK
MUARA
TAWAR
CIBATU
KEMBANGAN
NGIMBANG
NEW
UJUNGBERUNG
MANDIRANCAN
SURABAYA
BARAT
CAWANG
UNGARAN
SAGULING
CIBINONG
BALARAJA
DEPOK
Jakarta-Banten
Subsystem
SOUTH
BANDUNG
CIRATA
GANDUL
PEDAN
TASIK
West Java
Subsystem
Central Java
Subsystem
40th IAEE International Conference
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GRATI
KEDIRI
PAITON
East Java
Subsystem