NERI Conference, November 22, 2007 Modelling incentives and regulation in wholesale electricity markets Andy Philpott Electric Power Optimization Centre

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)


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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.


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Summary

• What is the wholesale electricity market?• Examples of incentive/regulation problems

– Generator offering– Transmission planning– Wind power– Emissions trading

• Takeaway: new energy technology is necessary but not sufficient without understanding the market mechanisms under which we expect it to be adopted.


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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


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Example

Capacity 250lossless

Thermal A: 400 @ $45Wind: 100 forecast, @ $0

Thermal B: 400 @ $50Hydro: 200 @ $30, 200 @ $90

Load 500


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Least-cost dispatch



Thermal B: 400 @ $50Hydro: 200 @ $30, 200 @ $90

Load 500

100

200

250

50

150


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Least-cost dispatch with nodal prices



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


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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)


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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


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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


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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


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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?


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J.F. Nash Jr., Equilibrium points in n-person games, Proc Nat. Acad. Sci. USA, 36 (1950) 48-49.


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If generators offer at marginal cost


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


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If generators withhold strategically



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



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Example of Cournot-Nash equilibrium



Load = 500 - p

Load = 500 - p

300

300

$200

$200

Total load = 1000-2pp = 500-(a+b)/2





0

100

200

300

400

500

b

100 200 300 400 500a

(300,300) Capacity 1000lossless


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Price = $200

Example of Cournot-Nash equilibrium



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


No flow in the line


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What if the line has zero capacity?



Load = 500 - p

Load = 500 - p

Each load = 500-pp = 500-a


b

a

(500-a-50)ahas maximum at a = 225

(500-b-50)b has maximum at b = 225

Capacity 0lossless


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Load = 500 - p

Load = 500 - p

Each load = 500-pp = 500-a


225

225

(500-a-50)ahas maximum at a = 225

(500-b-50)b has maximum at b = 225

$275

$275

Capacity 0lossless


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Price = $275




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.


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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”

NZ Electricity Commission 2006, Grid Investment Test.


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AKL

CNI

SI

Northland/AucklandDemand

2010 – 2288 MW2015 – 2631 MW2020 – 2987 MW

Strategic GeneratorsHuntly + E3P (1413 MW)Otahuhu B (390 MW)

Lower North Island and South IslandDemand

2010 – 3211 MW2015 – 3492 MW2020 – 3721 MW

Strategic GeneratorsTaranaki CC (365 MW)Waitaki Hydro (2718 MW)Clutha Hydro (1000MW)

Central North IslandDemand

2010 – 1794 MW2015 – 1954 MW2020 – 2109 MW

Strategic GeneratorsWaikato Hydro (776 MW)

New Zealand example (Downward 2007)


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Minimum Transfer Capacities (CNI - SI)

0

100

200

300

400

500

600

700

800

2010 2015 2020

Year

Capacity (MW)

Required CapacityFlow In Equilibrium

Minimum Transfer Capacities (AKL - CNI)

0

200

400

600

800

1000

1200

1400

1600

2010 2015 2020

Year

Capacity (MW)

Required CapacityFlow In Equilibrium

New Zealand example

Source: Anthony Downward, EPOC


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Incentives for wind generation



Thermal B: 400 @ $50Hydro: 200 @ $30, 200 @ $90

Load 500

Source: Geoff Pritchard, EPOC WW2007


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Least-cost dispatch



Thermal B: 400 @ $50Hydro: 200 @ $30, 200 @ $90

Load 500

The best solution, on the assumption that the wind forecast is accurate.

100

200

250

50

150



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Wind above forecast


Thermal A: 400 @ $45Wind: 120 actual, @ $0

Thermal B: 400 @ $50Hydro: 200 @ $30, 200 @ $90

Load 500

100

200

250

50

150

spill 20

Wind is spilled – cheap energy is lost.



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Wind below forecast



Thermal B: 400 @ $50Hydro: 200 @ $30, 200 @ $90

Load 500

Wind shortfall is made up with expensive water.

80

220

230

50

150



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Are better forecasts needed?

Electricity Commission WGIP report June 2007


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A flexible dispatch



Thermal B: 400 @ $50Hydro: 200 @ $30, 200 @ $90

Load 500

100

175

225

100

125

• Spare capacity on transmission line.• Spare capacity in cheap hydro offer.



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Wind above forecast



Thermal B: 400 @ $50Hydro: 200 @ $30, 200 @ $90

Load 500

120

155

245

100

125

Surplus wind is matched to hydro decrease.



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Wind below forecast



Thermal B: 400 @ $50Hydro: 200 @ $30, 200 @ $90

Load 500

80

195

205

100

125

Lack of wind is matched by hydro.



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Optimizing dispatch as a stochastic LP

Generators offer to sell quantities qi , ask prices pi ,regulation margins ri

We find dispatches xi and Zi to

minimize (pi xi + Epi riZi xipi riZi xi )

(expected cost of power, at offered prices, including re-dispatch)

so that– demand is met (at both 1st and 2nd stages)– transmission network is operated within capacity

– (xi , Zi ) satisfy plant constraints



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Example

Hydro 2: 40 @ $40 (+/- $5)

Wind: capacity 40, @ $0scenarios 0, 10, 20, 30probabilities 0.5, 0.2, 0.2, 0.1

Load 60

• Ensemble forecast for wind. Most likely scenario is 0. • Hydros compete on both energy and regulation.• What to dispatch?

Hydro 1: 40 @ $39 (+/- $2)



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Optimal hedged dispatch (initial)

Hydro 2: 40 @ $40 (+/- $5)


Load 60

• Hydros dispatched “out of order” to keep regulation cost down.

Hydro 1: 40 @ $39 (+/- $2)10

30

20



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Optimal hedged re-dispatch

Hydro 2: 40 @ $40 (+/- $5)


Load 60

• Hydro 1 wins the regulation business.

Hydro 1: 40 @ $39 (+/- $2)0, 10, 20, 3040, 30, 20, 10

20



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Initial dispatch prices

• – the marginal cost of an additional unit of load in the initial dispatch.

• This is an appropriate price at which to trade energy, where that energy was present in the initial dispatch.

• Applies to:– inflexible load and generation– some flexible and intermittent generation



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Re-dispatch prices

• R – the marginal cost of an additional unit of load in a re-dispatch.

• This is an appropriate price at which to trade energy, where that energy was added in a re-dispatch.

• Applies to:– some flexible and intermittent generation (both hydro & wind)



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Example: initial dispatch prices

Hydro 2: 40 @ $40 (+/- $5)


Load 60

• Marginal additional load would be met by Hydro 2.

• The quantities xi are sold @ $40; load pays $40.

Hydro 1: 40 @ $39 (+/- $2)10

30

20$40



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Example: re-dispatch prices

Hydro 2: 40 @ $40 (+/- $5)


Load 60

• 1st scenario: Wind buys back 10 @ $41; Hydro 1 sells 10 @ $41• 2nd scenario: no re-dispatch• 3rd scenario: Wind sells 10 @ $37; Hydro 1 buys back 10 @ $37• 4th scenario: Wind sells 20 @ $37; Hydro 1 buys back 20 @ $37

Hydro 1: 40 @ $39 (+/- $2)0, 10, 20, 3040, 30, 20, 10

20

$41, $41, $37, $37

10 30



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Average selling prices

Hydro 2: 40 @ $40 (+/- $5)


Load 60

Hydro 1: 40 @ $39 (+/- $2)0, 10, 20, 3040, 30, 20, 10

20

$41, $41, $37, $37

Average selling price achieved

= (expected revenue) / (expected generation)

• Wind: $38.11• Hydro 1: $40.55• Hydro 2: $40



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A price for uncertainty

• 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.


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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…


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Example: Least-cost dispatch



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


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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.


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Cournot-Nash equilibrium


Hydro B: 500 @ $50

Load = 500 - p

Load = 500 - p

300

300

$200

$200

Total load = 1000-2pp = 500-(a+b)/2





0

100

200

300

400

500

b

100 200 300 400 500a

(300,300) Capacity 1000lossless


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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




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.


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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.


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The last word is incentives

Robert Aumann Nobel Prize LectureDecember 8, 2005


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The End

Documents

NERI Conference, November 22, 2007 Modelling incentives and regulation in wholesale electricity markets Andy Philpott Electric Power Optimization Centre