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TRANSMISSION PLANNING AND INVESTMENT IN THE
COMPETITIVE ENVIRONMENTPSERC Seminar Presentation
by
George Gross
Department Of Electrical and Computer Engineering
University of Illinois at Urbana – Champaign
April 5, 2005© 2005, George Gross, UIUC
2© 2005, George Gross, UIUC
OUTLINE
The changed utilization of transmission
Planning in the competitive environment
The sorry state of transmission investment
Key challenges and complexities
An analytic framework for transmission
investment
Illustrative examples
Concluding remarks
3© 2005, George Gross, UIUC
OPEN ACCESS IMPACTS
Power system restructuring fosters the
development of competition in wholesale
electricity markets
Markets bring about changes in the way power
systems are operated and planned
The vertically integrated structure is slowly
disintegrating into many new parts
New structures and players have important roles
and result in decentralized decision making
4© 2005, George Gross, UIUC
THE VERTICALLY INTEGRATED UTILITY INDUSTRY STRUCTURE
customers
self-generation
IPP Generation
Transmission
Distribution
Customer Servicecustomer service
distribution
transmission
generation
5© 2005, George Gross, UIUC
THE VERTICALLY INTEGRATED UTILITY INDUSTRY STRUCTURE
customers
self-generationIPP
Generation
Transmission
Distribution
Customer Service
customer service
distribution
transmission
generation
6© 2005, George Gross, UIUC
VERTICALLY INTEGRATED UTILITY STRUCTURE IS DISINTEGRATING
transmission ownership
customer
service
marketing/
trading
ISO
ancil
lary
servi
ces
markets
generation
distribution wires
generation
transmission
customerservice
distribution
7© 2005, George Gross, UIUC
CENTRALITY OF TRANSMISSION IN RESTRUCTURING
A common thread in the restructuring of electricity around the globe is the unbundling of transmission from the generation and the distribution of sectorsThe role of transmission in evolving wholesale competition in electricity is criticalThe provision of the nondiscriminatory transmission access and services to all market players under the open access transmission regime entails the establishment of independent transmission entities
8© 2005, George Gross, UIUC
PLANNING UNDER COMPETITION
Major shift in the planning paradigm
cessation of the centralized integrated
planning of the past
role of regional planning under the
independent grid operator
unclear responsibility for implementation
under the ownership/control separation
role of decentralized decision making
9© 2005, George Gross, UIUC
PLANNING UNDER COMPETITION
Planning, to the extent it is performed in the new
environment, is an asset management problem
investment under uncertainty
critical importance of effective risk
management
subject to regulations in a continuous state
of flux
10© 2005, George Gross, UIUC
TRANSMISSION USAGE UNDER COMPETITION
Frequent congestion situations result whenever
too many customers compete for transmission
services that the grid is capable of providing
Despite the more intense utilization of the grid by
the many established and new players, develop-
ments in transmission planning have failed to
keep pace with the increases in demand
11© 2005, George Gross, UIUC
THE SORRY STATE OF TRANSMISSION INVESTMENT
As demand increases, significant additions of
new generation are being made in virtually every
region
The reserve margins in capacity are improving
year after year
Transmission investments have failed to keep up
with the increases in demand and the additions
in new generation
12© 2005, George Gross, UIUC
DEMAND AND TRANSMISSION CAPACITY GROWTH
0
5
10
15
20
25
30
1988 – 98 1999 – 09
electricitydemand
transmissioncapacityexpansion
%
Source: EPRI
13© 2005, George Gross, UIUC
THE NERC CAPACITY MARGIN FORECASTS
1999
2000
2001
2002
perc
ent
25
20
15
10
51999 20112001 2003 2005 2007 2009
yearSource: NERC Reliability Assessment, 2002 – 2011
14© 2005, George Gross, UIUC
PROJECTED GENERATION GROWTH IN 1998 – 2007
Each percentage is with respect to the 1998 installed capacity
change in %40 and higher20 to 40
0 to 20Source: EPRI
15© 2005, George Gross, UIUC
HISTORICAL TRANSMISSION SYSTEM INVESTMENT
Source: E. Hirst, “U.S. Transmission Capacity: Present Status and Future Prospects,” June 2004
16© 2005, George Gross, UIUC
TRANSMISSION MAINTENANCE SPENDING
tota
l spe
ndin
g
17© 2005, George Gross, UIUC
230 kV AND ABOVE TRANSMISSION
2003 2004-2008 2009-2013
< .49% / yr
207.9
213.5
218.2
+2.2%
+2.7%
thou
sand
s of
mile
s
Source: NERC 2004
18© 2005, George Gross, UIUC
SEVERE STRESSING OF THE GRID
Large number of new and existing playersProliferation in the number of transactionsIncreasing load demandSimultaneous accommodation of pool and bilateral transactions Markedly different and more intense utilization of the grid than in the way that it was planned and designedLow level of investment in transmission improvement
19© 2005, George Gross, UIUC
SEVERE STRESSING OF THE GRID
Severe stressing of the grid leads to frequent
congestion situations with customers competing
for the scarce and heavily constrained transmis-
sion services
The transmission-bottleneck-caused congestion
situations significantly impact both the reliability
and the economics of electricity supply
20© 2005, George Gross, UIUC
TRANSMISSION BOTTLENECKS: WESTERN INTERCONNECTION
size of transmission paths
< 1 GW
1 GW ≤ ≤ 3 GW
> 3 GW
50% and greaterpercentage of hours congested
40% to 49%30% to 39%20% to 29%10% to 19%
Source: DoE National Transmission Grid Study, May 2002
21© 2005, George Gross, UIUC
TRANSMISSION BOTTLENECKS: EASTERN INTERCONNECTION
size of transmission paths
< 1 GW
1 GW ≤ ≤ 3 GW
> 3 GW
Source: DoE National Transmission Grid Study, May 2002
80% and greaterpercentage of hours congested
60% to 79%40% to 59%20% to 39%10% to 19%
22© 2005, George Gross, UIUC
CONGESTION IMPACTS
Decreased reliability
Reduced competition
Increased consumer prices
Creation of enhanced opportunities for market
power exercise
Increased infrastructure vulnerability
23© 2005, George Gross, UIUC
CONGESTION : ECONOMIC SIGNALS
LMPs provide short-term congestion signals
The translation of LMPs into long-term
investment signals is complicated
LMPs create the need for the effective
integration of financial hedging instruments:
FTRs and flowgate rights
24© 2005, George Gross, UIUC
TRANSMISSION EXPANSION
Network expansion is by its very nature a very
complex multi-period and multi-objective optimi-
zation problem
Its nonlinear nature and the inherent uncertainty
in future developments constitute major compli-
cations
25© 2005, George Gross, UIUC
TRANSMISSION INVESTMENT : KEY BARRIERS
Transmission is a regulated service: tariffs are
cost based and not value based
Uncertainty about the recovery of transmission
investments due to
long-term revenue stream needs
lack of clarity in regulatory pricing policy
26© 2005, George Gross, UIUC
TRANSMISSION INVESTMENT : KEY BARRIERS
conflicting goals of federal and state
regulators
Difficulty of recovering investment costs due to
free rider problem
Organizational complexities in the new industry
structure
27© 2005, George Gross, UIUC
COMPLICATIONS IN TRANSMISSION EXPANSION
Every transmission improvement impacts the
transfer capabilities in the interconnected
network covering a large geographic region
Each transmission investment affects market
participants differently
Free rider problem creates a problem in the
investment recovery
Lumpiness of transmission investments is a key
complication
28© 2005, George Gross, UIUC
COMPLICATIONS IN TRANSMISSION EXPANSION
A long-time horizon with the sequence of
appropriate decisions needs to be considered
Economies of scale encourage overbuilding
Imperfect electrical markets provide
opportunities for market power exercise
29© 2005, George Gross, UIUC
COMPLICATIONS IN TRANSMISSION EXPANSION
Short-run marginal costing information from the
hourly LMPs need to be translated into long-run
marginal cost for investment decisions
FTR/FGR integration into the investment
decision is needed
The explicit consideration of wide ranges of
uncertainty in all aspects, including regulatory,
environmental and player behavior, is required
30© 2005, George Gross, UIUC
ANALYTIC FRAMEWORK
A four-layer structure consisting of
physical
commodity market
financial
investment
layers
The interrelationships between layers represen-
ted through information flows
31© 2005, George Gross, UIUC
THE FRAMEWORK STRUCTURE
commodity market layer
financial market layer
investment layer
physical network layer
32© 2005, George Gross, UIUC
PHYSICAL NETWORK LEVEL
33© 2005, George Gross, UIUC
THE PHYSICAL LAYER
Represents the physical flows in the
transmission network including real power line
flows, nodal injections and physical
network/operational constraints
Models congestion and allows the evaluation of
congestion impacts on the transmission
customers/market participants
34© 2005, George Gross, UIUC
THE COMMODITY MARKET LAYER
35© 2005, George Gross, UIUC
THE COMMODITY MARKET LAYER
Models the purchases/sales in both the day-
ahead hourly and the bilateral transaction
markets
Represents the RTO decision making process to
establish feasible transmission schedules
Interacts with the physical layer and the
financial layer through information transfers
36© 2005, George Gross, UIUC
THE FINANCIAL LAYER
37© 2005, George Gross, UIUC
THE FINANCIAL LAYER
Models the financial instruments used to
provide hedging against congestion changes
Models Financial Transmission Rights (FTR)
and flowgate rights
Represents the salient aspects of rights
issuance and trading
38© 2005, George Gross, UIUC
TRANSMISSION INVESTMENT LAYER
39© 2005, George Gross, UIUC
TRANSMISSION INVESTMENT LAYER
Models the transmission investment decision making process and determines the
locationquantitytiming
of the transmission assetsEvaluates the impacts of the investment decisions on the investor, system operator and the transmission customers and assesses their financial aspects
40© 2005, George Gross, UIUC
THE INFORMATION FLOWS
financial market layer
commodity market layer
physical network layer
LMPs
system states
SFTresult
investment layer
social welfare
topology change
market outcomes
feasible FTR
desired FTR
41© 2005, George Gross, UIUC
RTO TRANSMISSION PLANNING PROBLEM FORMULATION
Maximize aggregate social welfare:
pool
bilateral contracts
subject to:
power flow balance equations
line flow equations
generator and demand limits
line flow limits
42© 2005, George Gross, UIUC
BASIC PROBLEM FORMULATION
( ) ( )
max
( ) ( )N W
b b s s w wh n n n n
n 0 w 1
s b T0 0 0 0 0
s b
d
p p t
p p p b
p p p B
B A f
τ
τ
β β α
θ µ
θ µ
θ λ
= =
= − +
− + = ↔
− + = ↔
≤ ↔
∑ ∑S
s.t.
∑8760
1
S S hh
max=
=
Note: all parameters and variables are hourly quantities
43© 2005, George Gross, UIUC
EVALUATION OF METRICS
$/MWh
MWh/h
consumer surplus
producer surplus
Bρ
Sρ
congestion rents
market effi-
ciencyloss
dead-weight
loss
44© 2005, George Gross, UIUC
APPROPRIATE METRICS FOR TRANSMISSION INVESTMENT
RTO metrics:
social welfare: aggregated value
loss of efficiency: decrease in social
welfare due to transmission constraints
congestion rents: money collected by the
system operator because of congestion
45© 2005, George Gross, UIUC
APPROPRIATE METRICS FOR TRANSMISSION INVESTMENT
Producer metrics:
producer surplus: difference between what
the producer collects from the system and
the real costs
redispatch costs: difference in the produ-
cers’ costs with and without congestion
46© 2005, George Gross, UIUC
APPROPRIATE METRICS FOR TRANSMISSION INVESTMENT
Consumer metrics:
consumer surplus: difference between the
demand bids and the demand payments
load payment costs: difference in demand
payments with and without congestion
47© 2005, George Gross, UIUC
THREE – BUS SYSTEM EXAMPLE
One-hour horizon
Lossless network
Quadratic functions for the costs and benefits
No bilateral transactions
48© 2005, George Gross, UIUC
NETWORK TOPOLOGY
1S
3S
1B
2S
2B
3B
lossless system
21
~
~
3
~
49© 2005, George Gross, UIUC
NETWORK DESCRIPTION
line l = (i, j) with
i j
1 2 0.1 300
1 3 0.1 300
2 3 0.1 300
x
( p.u.)
f max
(MW )ll
50© 2005, George Gross, UIUC
OFFER REPRESENTATION
Cost function:
Offer function:
( ) ( )=2
0.5C i i i i i is s s s s sP P Pβ γ+
( )σ =i i i i is s s s sP Pβ γ+
51© 2005, George Gross, UIUC
OFFER DATA
iβ
($/MWh )
γ
[($/MWh )2h]
( p )max
(MWh/h )
1 3.0 0.001 1000
2 4.5 0.005 1000
3 4.0 0.003 1000
si si si
52© 2005, George Gross, UIUC
OFFER PARAMETERS
$/MWhgenerator
offer
β si
γ si
MWh/h
53© 2005, George Gross, UIUC
BID REPRESENTATION
Benefit function:
Bid function:
⎛ ⎞ ⎛ ⎞⎜ ⎟ ⎜ ⎟⎝ ⎠ ⎝ ⎠
=2
0.5B j j j j j jb b b b b bP P Pβ γ+
⎛ ⎞⎜ ⎟⎝ ⎠
=j j j j jb b b b bv P Pβ γ+
54© 2005, George Gross, UIUC
BID DATA
iβ
($/MWh )
γ
[($/MWh )2h]
( p )max
(MWh/h )
1 13 0.0150 1000
2 23 0.0200 1000
3 16 0.0150 1000
bj bj bj
55© 2005, George Gross, UIUC
BID PARAMETERS
$/MWh
demandbidβ bj
γ bj
MWh/h
56© 2005, George Gross, UIUC
PRE – EXPANSION RESULTS
metric value in $
total producer surplus 761.98
total consumer surplus
congestion rents
social welfare
6632.01
520.67
7914.66
total production = 1056.57 MW
57© 2005, George Gross, UIUC
POST – EXPANSION RESULTS
metric value in $
total producer surplus 880.24
total consumer surplus
congestion rents
social welfare
7150.03
163.83
8194.10
total production = MW 1092.60
58© 2005, George Gross, UIUC
PRE – AND POST – COMPARISON
pre-expansion post-expansion
consumerpower demanded
(MW)
surplus
($)
power demanded
(MW)
surplus
($)
1 293.75 1294.34 273.44 1121.52
2 426.92 3645.27 440.00 3872.00
3 335.90 1692.41 379.17 2156.51
379.17104.17308.19320.513
440.0090.00101.26142.312
273.44898.44352.54593.751
surplus
($)
power generated
(MW)
surplus
($)
power generated
(MW)producer
post-expansionpre-expansion
59© 2005, George Gross, UIUC
PRE – AND POST – COMPARISON
metric pre-expansion post-expansion
total producer surplus ($) 761.98 880.24
6632.01 7150.03
163.83
8194.10
1092.60
520.67
7914.66
1056.57
total consumer surplus ($)
congestion rents ($)
social welfare ($)
total production (MW)
60© 2005, George Gross, UIUC
MULTI – PERIOD ANALYSIS
physical network physical network
commodity market commodity market
financial market layer
financial market layer
investment layer
social welfare social welfare
operational period Hoperational period 1
topology
changetopology change
. . .
. . .
. . .
. . .
SFT
LMPs LMPsfeasible
FTR
desired FTR
market outcomes
market outcomessystem
statessystem states
feasible FTR
market outcomes
market outcomes
61© 2005, George Gross, UIUC
IEEE RTS SEVEN – BUS NETWORK EXAMPLE
Study horizon of one year; typical week day
and week end day for each of four seasons
Lossless network
Quadratic functions representation for costs
and benefits
No bilateral transactions
Hourly computations
62© 2005, George Gross, UIUC
STUDY SCENARIOS
Reference scenario: the pre-expansion system
Scenario 1: addition of line ( 3 , 4 )
Scenario 2: addition of line ( 5 , 6 )
Scenario 3: addition of lines ( 3 , 4 ) and ( 5 , 6 )
63© 2005, George Gross, UIUC
NETWORK TOPOLOGY
B1
B3
B2
B4
B6 B7
B5
S1
S2
S3S4
S5
bus 1 bus 2
bus 3
bus 4
bus 5
bus 6 bus 7
~
~
~
~
~
64© 2005, George Gross, UIUC
NETWORK DESCRIPTION
line l = ( i, j ) with
i j
1 2 0.0576 300
1 3 0.0920 200
2 4 0.0586 300
3 4 0.1008 150
3 6 0.1720 300
4 5 0.0625 300
5 6 0.1610 300
5 7 0.0850 300
6 7 0.0856 200
xl ( p.u. ) f l ( p.u. )max
65© 2005, George Gross, UIUC
OFFER DATA
i β γ ( p )max
1 3.5 0.002 1000
2 5.0 0.005 1000
3 4.5 0.003 1000
4 3.8 0.004 1000
5 3.8 0.004 1000
si si si
66© 2005, George Gross, UIUC
BID DATA
i β γ ( p )max
1 20 0.015 1000
2 21 0.018 1000
3 50 0.022 1000
4 20 0.010 1000
5 28 0.017 1000
6 20 0.016 1000
7 27 0.015 1000
bj bj bj
67© 2005, George Gross, UIUC
ANNUAL RTO METRICS
social welfare
loss of efficiency
congestion rentsscenario
( k$ )
reference 305,101.73 6,679.58 7,664.69
1 308,204.19 3,577.12 8,715.52
2 305,975.03 5,806.28 4,939.40
3 308,799.57 2,981.74 5,179.23
68© 2005, George Gross, UIUC
ANNUAL PRODUCER AND CONSUMER METRICS
producer surplus
consumer surplus
27,0073.95
27,1984.71
27,2329.14
27,3615.14
scenario( k$ )
reference 27,363.09
1 27,503.96
2 28,706.49
3 30,005.20
69© 2005, George Gross, UIUC
AGGREGATE METRICS FOR A SUMMER WEEKDAY
$$
$ $
70© 2005, George Gross, UIUC
NODAL PRICES FOR A SUMMER WEEKDAY
nodal prices, reference scenario nodal prices, scenario 1
nodal prices, scenario 2 nodal prices, scenario 3
$/M
Wh/
h
$/M
Wh/
h
$/M
Wh/
h
$/M
Wh/
h
71© 2005, George Gross, UIUC
NODAL PRICE DIFFERENCES FOR A SUMMER WEEKDAY
nodal price differences, scenario 1
nodal price differences, scenario 2 nodal price differences, scenario 3
$/M
Wh/
h
$/M
Wh/
h
$/M
Wh/
h
$/M
Wh/
h
nodal price differences, reference scenario
72© 2005, George Gross, UIUC
SEVEN – BUS SYSTEM RESULTS
Best overall solution is scenario 3 with the lines
( 3, 4 ) and ( 5, 6 ) added in scenario 3
Scenario 1 results in the highest congestion
results
Scenarios 2 and 3 are characterized by flat nodal
price differences and lower average LMPs than
in the reference scenario
73© 2005, George Gross, UIUC
CONCLUDING REMARKS
Multi-layer analytic framework for transmission
expansion planning
Framework capability to deal with the complex
issues in transmission investment
Appropriate metrics to determine the best
investment policy
Scenario analysis allows the identification of
optimal strategy and investigation of what if
questions
74© 2005, George Gross, UIUC
FUTURE WORK
Transmission service pricing on a value rather
than cost basis
Formulation of effective incentives for transmis-
sion investment
The formulation and solution of the individual
investor problem