Regulated Expansion of
Electricity Transmission
Networks: the effects of
Fluctuating Demand and Wind
Generation
Schill, Rosellón, Egerer
34th IAEE International Conference, Stockholm , June 19-23, 2011
Juan Rosellon, CIDE and DIW Berlin
Outline
•
•
•
•
•
Motivation
The model
Model application
Results
Conclusions and challenges
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2
Motivation
• Starting point: Hogan, Rosellón and Vogelsang
(2010) - “HRV“
– Rosellón and Weigt (2011), and Rosellón, Myslikóvá
and Zenón (2011): “Seminal, but simplified”
• Challenges:
– Demand and prices vary considerably over a day /
over a year
– Increasing importance of fluctuating wind power
– Comparison to other regulatory regimes
• Our approach:
– Include hourly time resolution and appropriate data
– Implement additional regulatory regimes
 How will the HRV model perform?
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3
The model
• MPEC approach (Rosellón and Weigt,
2011)
• Dispatch problem (lower level):


 q n ,t ,
max       pn ,t , (qn ,t , )dqn ,t ,   cs g s , n ,t ,
q , g , ,


sS
1 , 2 , p , tT   nN  0

3 , 4 ,
s.t.
I l ,n
X
n

n
g
s
16 June 2011


1


t 1
 1   s  


(1,l ,t , )
l , t ,
(2,l ,t , )
l , t ,
  Bn ,nn  nn ,t ,  qn ,t ,  0 ( pn ,t , )
n, t ,
 n ,t ,  Pl ,t  0
l ,t
I l ,n
X l ,t
n , s ,t ,
 n ,t ,  Pl ,t  0
nn
g n , s ,t ,  g n , s  0
(4, n , s ,t , )
n, s, t ,
slackn  n ,t ,  0
(5, n ,t , )
n, t ,
4
Maximization Transco Problem
(upper level)



1



max        pn,t , qn,t ,   pn,t , g s,n,t ,   fixpartt   ecl extl ,tt 
t

1
p

tT     nN 
sS
lL tt t


1






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5
Additional equations
• HRV cap on fix part:


HRV
p
q

p
g

fixpart

t 1
 n,t 1, n,t ,  n,t 1, s ,n,t , 
nN   
sS

 1  RPI  X


HRV
p
q

p
g

fixpart

t
 n,t , n,t ,  n,t , s ,n,t , 
nN   
sS

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6
Model application
• Implementation in GAMS
• Elmod framework for load
flows
• Stylized central European
network
Technology
Nuclear
Variable generation
costs in €/MWh
Zonal lines
Unlimited zonal lines
9
15,120
Hard coal
35
35,064
CCGT
43
16,358
Gas turbine
65
16,286
72
12,584
Hydro
0
9,841
Wind
0
29,790
l1
l7
NL1
Main nodes
Auxilliary nodes
l8
NL2
l11
l2
l4
l9
BE1
64,858
29
NL3
l6
Country borders
Overall available
capacity
Lignite
Oil
Cross border lines
l13
l12
l10
GER
BE2
l3
l16
l14
l15
l17
l5
F
l18
l20
l19
Table 1: Variable generation costs and available capacity
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7
Different cases
Case
Representation of demand
Wind generation
Static
Yearly average
Yearly average
DRes
144 hours, representing six characteristic days of the year
Yearly average
WindRes
144 hours, representing six characteristic days of the year
Fluctuating pattern
90
80
70
F
GW
60
GER
NL1
50
BE1
40
NL3
BE2
30
Hourly reference
demand at
different nodes
16 June 2011
NL2
20
Weekday
Summer
10
Weekend
Summer
Weekday
Winter
Weekend
Winter
Weekday
Shoulder
Weekend
Shoulder
0
1
13
25
37
49
61
73
85
97
109
121
133
hours
Figure 2: Hourly nodal reference demand in DRes and WindRes
8
80
Hourly reference
prices
70
60
€/MWh
50
F
BE
40
NL
GER
30
20
10
Weekday
Summer
0
1
13
Weekend
Summer
25
37
Weekday
Winter
49
61
Weekend
Winter
73
85
Weekday
Shoulder
97
109
Weekend
Shoulder
121
133
hours
Figure 3: Hourly nodal reference prices in DRes and WindRes
200
180
160
140
GW
120
100
80
60
Hourly overall
demand and
wind
pattern
6 October
2010
Weekday
Summer
40
Weekend
Summer
Weekday
Winter
Weekend
Winter
Weekday
Shoulder
Weekend
Shoulder
20
0
1
13
25
37
49
61
73
85
97
109
121
133
hours
Reference demand
Wind generation
Figure 4: Wind generation and overall reference demand in WindRes
9
Results: Static
6
5
GW
4
3
2
1
0
l1
l2
l3
l4
l5
l6
l7
l8
l9
WFMax
l10
HRV
l11
l12
l13
l14
l15
l16
l17
l18
l19
l20
CostReg NoReg
 Network extension: HRV closest to WF-max
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10
Line expansion (Static)
125%
120%
115%
WFMax
MW
HRV
CostReg
NoReg
110%
105%
100%
t0
t1
t2
t3
t4
t5
Figure 6: Time path of overall extension in the Static case
Extension: Germany-Netherlands and France-Belgium
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11
Results: Static vs. DRes
Social
welfare
Producer
rent
Consumer
rent
Congestion
rent
Extension
costs
Transco
profit
Fixed part
WFMax
+1.94
+19.04
-15.57
-1.50
+0.03
-1.50
-
NoReg
+0.13
-1.42
+1.36
+0.19
+0.00
+0.19
-
CostReg
+0.11
-1.43
+1.37
+0.19
+0.01
+0.19
+0.02
HRV
+1.81
+13.08
-11.13
-0.12
+0.02
+1.68
+1.82
Consumer
rent
Congestion
rent
Social
welfare
Producer
rent
Extension
costs
Transco
profit
Fixed part
WFMax
+2.80
+11.13
-5.97
-2.27
+0.08
-2.27
-
NoReg
+1.10
+1.82
-1.13
+0.42
+0.01
+0.41
-
CostReg
+1.06
+1.77
-1.08
+0.41
+0.04
+0.42
+0.04
HRV
+2.25
+6.59
-3.62
-0.68
+0.04
+1.79
+2.51
 Demand fluctuations increase extension in wf-max and HRV
 Opposite effect in noreg and costreg cases!
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Price convergence in DRes
Hourly prices in t5 (Dres, WFMax)
Hourly prices in t5 (Dres, HRV)
90
90
80
80
70
70
GER
GER
60
F
BE1
50
BE2
40
NL1
€/MWh
€/MWh
60
NL2
30
F
BE1
50
BE2
40
NL1
NL2
30
NL3
NL3
20
20
10
10
0
0
1
7
13
19
25
31
37
43
49
55 61
67
73
79
85
91
97 103 109 115 121 127 133 139
1
7
13
19
25
31
37
43
49
55
61
67
73
79
85
91
97 103 109 115 121 127 133 139
Hourly prices in t5 (Dres, NoReg)
Hourly prices in t5 (Dres, CostReg)
90
90
80
80
70
70
GER
BE1
50
BE2
40
NL1
NL2
30
GER
60
F
€/MWh
€/MWh
60
F
BE1
50
BE2
40
NL1
NL2
30
NL3
NL3
20
20
10
10
0
0
1
7
13
19
25
31
37
43
49
55
61
67
73
79
85
91
97 103 109 115 121 127 133 139
1
7
13
19
25
31
37
43
49
55
61
67
73
79
85
91
97 103 109 115 121 127 133 139
Figure 18: Convergence of hourly nodal prices under different regulatory approaches in DRes
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WindRes
Social
welfare
WFMax
Producer
rent
Consumer
rent
Congestion
rent
Extension
costs
Transco
profit
Fixed part
+2.80
+11.13
-5.97
-2.27
+0.08
-2.27
-
+1.10
+1.82
-1.13
+0.42
+0.01
+0.41
-
+1.06
+1.77
-1.08
+0.41
+0.04
+0.42
+0.04
+2.25
+6.59
-3.62
-0.68
+0.04
+1.79
Table 5: Welfare results DRes: Differences to baseline without extension in bn €
+2.51
NoReg
CostReg
HRV
Social
welfare
WFMax
NoReg
CostReg
HRV
Producer
rent
Consumer
rent
Congestion
rent
Extension
costs
Transco
profit
Fixed part
+2.82
+11.46
-6.31
-2.25
+0.08
-2.33
-
+1.09
+1.81
-1.15
+0.44
+0.01
+0.43
-
+1.09
+1.99
-1.30
+0.44
+0.05
+0.44
+0.05
+2.30
+6.80
-3.69
-0.76
+0.04
+1.79
+2.59
Table 6: Welfare results WindRes: Differences to baseline without extension in bn €
 HRV again closer to wf-max than noreg and costreg
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14
Comparison of welfare and
extension results
100%
Ten regulatory periods
Higher extension
costs
More wind
Endogenous line
reactance
80%
60%
40%
20%
HRV
NoReg
es
_e
r
W
in
dR
es
_e
r
DR
_e
r
St
at
ic
W
in
dR
es
_x
4
es
_x
4
DR
es
W
in
dR
es
St
at
ic
_t
10
DR
es
_t
10
W
in
dR
es
_t
10
DR
es
_2
50
DR
es
_5
00
DR
es
_1
00
0
St
at
ic
_x
4
-20%
DR
St
at
ic
0%
CostReg
Figure 17: Social welfare gain of extension compared to WFMax for different model runs
 Fluctuating demand and wind power both increase the gap between
wf-max and the regulatory cases
 HRV much closer to wf-optimum in all cases  robust!
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Conclusions
• Details matter in electricity market modelling:
– Demand: simplified, static approach systematically
underestimates the need for transmission upgrades
– Fluctuating wind: further increases expansion requirements
• HRV is robust against demand and wind fluctuations
– WF: HRV closest to wf-max
– Extension: HRV also leads to second-highest outcomes
– Performance of HRV relative to alternatives increases with more
realistic setting!
• HRV has favourable characteristics for future large-scale
wind integration (high extension)
 further research necessary
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Challenges
• Computationally very intensive
• Data:
– Better reference demands and prices
– More realistic wind power fluctuations
• Strong assumptions:
– Perfect competition in generation
– A single Transco
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