NERI Conference, November 22, 2007 E P O C E P O C Modelling incentives and regulation in wholesale electricity markets Andy Philpott Electric Power Optimization Centre The University of Auckland (www.esc.auckland.ac.nz/epoc) (with acknowlegements to Geoff Pritchard and Golbon Zakeri)
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NERI Conference, November 22, 2007 Modelling incentives and regulation in wholesale electricity markets Andy Philpott Electric Power Optimization Centre.
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NERI Conference, November 22, 2007E
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Modelling incentives and regulation in
wholesale electricity markets
Andy PhilpottElectric Power Optimization Centre
The University of Auckland
(www.esc.auckland.ac.nz/epoc)
(with acknowlegements to Geoff Pritchard and Golbon Zakeri)
NERI Conference, November 22, 2007E
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What is the purpose of this talk?
• New Zealand faces some huge technical challenges in energy supply and delivery.
• This needs lots of research and development into new technology which is where NERI is currently focused.
• But technology is not enough – we need to understand the economic institutions for implementing this technology.
• Our work at EPOC studies how these institutions (e.g. taxes, trading schemes, regulations etc.) work using models.
• These models try to help us design mechanisms that will induce “optimal” behaviour in the agents of wholesale electricity markets – i.e. we study incentives and how they work.
NERI Conference, November 22, 2007E
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Summary
• What is the wholesale electricity market?• Examples of incentive/regulation problems
• Takeaway: new energy technology is necessary but not sufficient without understanding the market mechanisms under which we expect it to be adopted.
NERI Conference, November 22, 2007E
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NZEM is a uniform price auction (e.g. single node)
price
quantity
price
quantity
combined offer stack
demand
p
price
quantity
T1(q) T2(q)
p
NERI Conference, November 22, 2007E
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Example
Capacity 250lossless
Thermal A: 400 @ $45Wind: 100 forecast, @ $0
Thermal B: 400 @ $50Hydro: 200 @ $30, 200 @ $90
Load 500
NERI Conference, November 22, 2007E
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Least-cost dispatch
Capacity 250lossless
Thermal A: 400 @ $45Wind: 100 forecast, @ $0
Thermal B: 400 @ $50Hydro: 200 @ $30, 200 @ $90
Load 500
100
200
250
50
150
NERI Conference, November 22, 2007E
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Least-cost dispatch with nodal prices
Capacity 250lossless
Thermal A: 400 @ $45Wind: 100 forecast, @ $0
Thermal B: 400 @ $50Hydro: 200 @ $30, 200 @ $90
Load 500
100
200
250
50
150$45
$50
(1) Load pays $25000 (=$50*500)(2) Hydro makes profit $4000 and Wind makes profit $4500(3) System operator makes congestion rent of $1250(4) The dispatch has total cost $15250
NERI Conference, November 22, 2007E
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The actual NZEM
• Generators specify supply curves defining prices at which they will generate.
• Curves fixed for each (1/2) hour• Linear programming model runs
every five minutes to determine – who produces how much– electricity flows in grid– spot price of electricity at
each grid exit point around the country (244 of these)
NERI Conference, November 22, 2007E
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NERI Conference, November 22, 2007E
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0
20
40
60
80
100
120
Wholesale electricity pricesFive Minute Wholesale Electricity Prices on 28/08/06 ($/MWh)
Time of Day
Otahuhu
Benmore
6am-9am
3am-6am
Source: comitfree
NERI Conference, November 22, 2007E
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Capacity 250lossless
Thermal A: 400 @ $45Wind: 100 forecast, @ $0
Thermal B: 400 @ $50 Hydro: 200 @ $30, 200 @ $90
Load 500
100
200
250
50
150$45
$50
$89
$89
Example 1: Dispatch with strategic bidding
(1) Load pays $19500 extra (=$39*500)(2) Hydro makes extra $7800 and Thermal B makes extra $1950(3) System operator makes extra congestion rent of $9750(4) The dispatch is exactly the same, with cost $15250
NERI Conference, November 22, 2007E
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Capacity 250lossless
Thermal A: 400 @ $45Wind: 100 forecast, @ $0
Thermal B: 400 @ $50 Hydro: 200 @ $30, 200 @ $90
Load 500
100
200
250
50
150$45
$50
Thermal A: 400 @ $45 149 @ $45
149
249
51
$50
Total cost of dispatch is $15255 which is $5 more than original cost!!
(1) Load pays no extra money(2) System operator congestion rent goes down by $1250 to $0(3) Wind makes $500 more, Thermal A makes $745 more…
Example 2: Dispatch with strategic withholding
NERI Conference, November 22, 2007E
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• Strategic behaviour by firms can result in higher prices and a wealth transfer between agents.
• Strategic behaviour by firms can result in dispatch inefficiency.
• Prices that do not truly represent the cost of shortage can lead to inefficiencies in the wider economy.
• Dispatch inefficiency is a deadweight loss ($5 in example)
• Q: How bad can it get?
• Q: How do we prevent it?
What can we learn from this example?
NERI Conference, November 22, 2007E
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J.F. Nash Jr., Equilibrium points in n-person games, Proc Nat. Acad. Sci. USA, 36 (1950) 48-49.
NERI Conference, November 22, 2007E
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If generators offer at marginal cost
Capacity 1000lossless
Thermal A: 500 @ $50
Thermal B: 500 @ $50
Load = 500 - p
Load = 500 - p
Expect the price to be $50
a=450
b=450
Line contains no flow.
Thermals make no profit.
Load has high welfare.b
a
NERI Conference, November 22, 2007E
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If generators withhold strategically
Thermal A: 500 @ $50
Thermal B: 500 @ $50
Load = 500 - p
Load = 500 - p
Total load = 1000-2pp = 500-(a+b)/2
A solves:max (p-50)a
B solves:max (p-50)b
b
a
(500-(a+b)/2-50)ahas maximum at a = 450-b/2
(500-(a+b)/2-50)b has maximum at b = 450-a/2
Capacity 1000lossless
NERI Conference, November 22, 2007E
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Example of Cournot-Nash equilibrium
Thermal A: 500 @ $50
Thermal B: 500 @ $50
Load = 500 - p
Load = 500 - p
300
300
$200
$200
Total load = 1000-2pp = 500-(a+b)/2
A solves:max (p-50)a
B solves:max (p-50)b
(500-(a+b)/2-50)ahas maximum at a = 450-b/2
(500-(a+b)/2-50)b has maximum at b = 450-a/2
0
100
200
300
400
500
b
100 200 300 400 500a
(300,300) Capacity 1000lossless
NERI Conference, November 22, 2007E
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Price = $200
Example of Cournot-Nash equilibrium
Thermal A: 500 @ $50
Thermal B: 500 @ $50
Load = 500 - p
Load = 500 - p
300
300
$200
$200
0
100
200
300
400
500
100 200 300 400 500a
Thermals each make profit of $45000.
Load decreases welfare by $56250.
Deadweight loss is $11250 x 2
Capacity 1000lossless
No flow in the line
NERI Conference, November 22, 2007E
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What if the line has zero capacity?
Thermal A: 500 @ $50
Thermal B: 500 @ $50
Load = 500 - p
Load = 500 - p
Each load = 500-pp = 500-a
A solves:max (p-50)a
b
a
(500-a-50)ahas maximum at a = 225
(500-b-50)b has maximum at b = 225
Capacity 0lossless
NERI Conference, November 22, 2007E
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What if the line has zero capacity?
Thermal A: 500 @ $50
Thermal B: 500 @ $50
Load = 500 - p
Load = 500 - p
Each load = 500-pp = 500-a
A solves:max (p-50)a
225
225
(500-a-50)ahas maximum at a = 225
(500-b-50)b has maximum at b = 225
$275
$275
Capacity 0lossless
NERI Conference, November 22, 2007E
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Price = $275
What if the line has zero capacity?
Thermal A: 500 @ $50
Thermal B: 500 @ $50
Load = 500 - p
Load = 500 - p
225
225
$275
$275
0
100
200
300
400
500
100 200 300 400 500a
Thermals each make profit of $50625.
Deadweight loss is $25312.50 x 2
Capacity 0lossless
The transmission line has significant value in encouraging competition even though it might never transport any electricity.
NERI Conference, November 22, 2007E
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Does this matter in practice?
Clause 10 of the Grid Investment Test states:
“Competition Benefits may be included in the market benefits of a proposed investment or alternative project if the Board reasonably considers this appropriate, provided the competition benefits can be separately identified and calculated”
• Prices earned by less predictable wind generation are lower on average.
• Prices earned by flexible generation are higher on average.
• Prices paid by less predictable loads are higher on average.
• New wind generation that decreases variation will increases price for all.
• Revenue adequate dispatch model means that wind backup can be suitably rewarded.
NERI Conference, November 22, 2007E
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Emissions trading
• NZ ETS is a cap-and-trade scheme.• How can generators act strategically in this setting?• Little work done here, but see e.g. Chen, Hobbs et al 2007.• Example conjecture: withholding generation decreases
emissions so that emission permits become cheaper, and so are acquired by competitive firms who will increase output in equilibrium.
• Alternative is a carbon tax.• Example conjecture: A $20/MWh carbon tax on thermal plant
just increases the consumer’s price by $20/MWh with windfall to hydro.
• Try this out with a very stylized example…
NERI Conference, November 22, 2007E
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Example: Least-cost dispatch
Capacity 1000lossless
Thermal A: 500 @ $50
Hydro B: 500 @ $50
Load = 500 - p
Load = 500 - p
Expect the price to be $50
a=450
b=450
Line contains no flow.
Thermals make no profit.
Load has high welfare.b
a
$50
$50
NERI Conference, November 22, 2007E
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Least-cost dispatch with CO2 tax
Hydro B: 500 @ $50
Load = 500 - p
Load = 500 - p
Thermal A: 500 @ $50plus $20 CO2 tax
Capacity 1000
500
360
70
$70
$70
Price increases by $20. The carbon tax has been transferred to consumers. Hydro B makes $10000 profit.
NERI Conference, November 22, 2007E
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Cournot-Nash equilibrium
Thermal A: 500 @ $50
Hydro B: 500 @ $50
Load = 500 - p
Load = 500 - p
300
300
$200
$200
Total load = 1000-2pp = 500-(a+b)/2
A solves:max (p-50)a
B solves:max (p-50)b
(500-(a+b)/2-50)ahas maximum at a = 450-b/2
(500-(a+b)/2-50)b has maximum at b = 450-a/2
0
100
200
300
400
500
b
100 200 300 400 500a
(300,300) Capacity 1000lossless
NERI Conference, November 22, 2007E
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Cournot-Nash equilibrium with CO2 tax
Thermal A: 500 @ $50plus $20 CO2 tax
Hydro B: 500 @ $50
Load = 500 - p
Load = 500 - p
$206.66
$206.66
Total load = 1000-2pp = 500-(a+b)/2
A solves:max (p-50+20)a
B solves:max (p-50)b
(500-(a+b)/2-70)ahas maximum at a = 430-b/2
(500-(a+b)/2-50)b has maximum at b = 450-a/2
Capacity 1000
0
100
200
300
400
500
b
100 200 300 400 500a
(273,313)
313
273
20
Price increases by only $6.66.
NERI Conference, November 22, 2007E
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The takeaways
• Markets are intended to provide incentives for agents to make optimal decisions.
• Understanding these is essential to formulating energy policy.
• For a poor market design, strategic behaviour might make decisions inefficient.
• Regulation is intended to restore some efficiency.• Nash equilibrium models are indispensible in
understanding whether incentives and or regulation will deliver the desired outcomes.