[PPT] - Dynamics of Power* LCCC Lund University, Sweden Based on tutorial PowerPoint Presentation

SLIDE 1

Dynamics of Power*

LCCC Lund University, Sweden Based on tutorial & panel lectures at Energy Systems Week, Cambridge UK

Sean P. Meyn

Joint work with: In-Koo Cho, Anupama Kowli, Matias Negrete-Pincetic, Ehsan Shafieeporfaard, Uday Shanbhag, and Gui Wang Coordinated Science Laboratory and the Department of Electrical and Computer Engineering University of Illinois at Urbana-Champaign, USA Thanks to NSF, AFOSR, and DOE / TCIPG

*Dynamik i Makten (i grossistledet elmarknaderna)

May 19, 2011

SLIDE 2

Outline

1 Can You Spot the Competitive Equilibrium? 2 Competitive Equilibria in Dynamic Markets 3 Coping with Uncertainty and Constraints 4 Conclusions 5 References

2 / 40

SLIDE 3

Can You Spot the Competitive Equilibrium? 4am 9am 2pm 7pm

$0 $10,000 $20,000 Stratford Otahuhu Nodal Power Prices per MWh

Spot the Competitive Equilibrium

3 / 40

SLIDE 4

Can You Spot the Competitive Equilibrium?

Competitive Equilibrium

Standard economic setting

Perfect competition Long-run setting with uncertainty: KD(GD) = E

e−γtWD(t) dt
KS(GS) = E
e−γtWS(t), dt
Consumers and suppliers each wish to maximize their individual welfare.

Welfare functions defined with a price-process {P(t) : t ≥ 0}

4 / 40

SLIDE 5

Can You Spot the Competitive Equilibrium?

Competitive Equilibrium

Standard economic setting

Perfect competition Long-run setting with uncertainty: KD(GD) = E

e−γtWD(t) dt
KS(GS) = E
e−γtWS(t), dt
Consumers and suppliers each wish to maximize their individual welfare.

Welfare functions defined with a price-process {P(t) : t ≥ 0}

Price-taking assumption Key assumption of equilibrium theory: The price of power P(t) does not depend on the decisions of the market agents.

4 / 40

SLIDE 6

Can You Spot the Competitive Equilibrium?

Competitive Equilibrium

Efficiency

Efficient Equilibrium Social Planner’s Problem: max K(G) = E

e−γt

WS(t) + WD(t)

dt
5 / 40

SLIDE 7

Can You Spot the Competitive Equilibrium?

Competitive Equilibrium

Efficiency

Efficient Equilibrium Social Planner’s Problem: max K(G) = E

e−γt

WS(t) + WD(t)

dt
Suppose that there exists a price process {P ∗(t)} that forms an

equlibrium: The consumers and suppliers agree, GS = GD = G. Suppose the agreed upon decisions G solve the SPP. Then, the market is called efficient.

5 / 40

SLIDE 8

Can You Spot the Competitive Equilibrium?

Competitive Equilibrium

Efficiency

Efficient Equilibrium Social Planner’s Problem: max K(G) = E

e−γt

WS(t) + WD(t)

dt
Suppose that there exists a price process {P ∗(t)} that forms an

equlibrium: The consumers and suppliers agree, GS = GD = G. Suppose the agreed upon decisions G solve the SPP. Then, the market is called efficient.

Let’s look for examples of efficient equilibria!

5 / 40

SLIDE 9

Can You Spot the Competitive Equilibrium?

Efficient Equilibrium?

California, 2000

Spinning reserve prices PX prices $/MWh

100 150 50 200 250 10 20 30 40 50 60 70 Mon Tues Weds Weds Thurs Fri Sat Sun

California, July 2000

6 / 40

SLIDE 10

Can You Spot the Competitive Equilibrium?

Efficient Equilibrium?

California, 2000

Spinning reserve prices PX prices $/MWh

100 150 50 200 250 10 20 30 40 50 60 70 Mon Tues Weds Weds Thurs Fri Sat Sun

California, July 2000 Enron traders openly discussed manipulating California’s power market during profanity-laced telephone conversations in which they merrily grandmothers” during the state’s energy crunch in 2000-01 ... [AP by Kristen Hays, 06/03/04]

NRON

to package up a big sample of nothing and sell it to a greedy public, Samuel West oozes self-belief; his boss, Ken Lay (Tim Piggott-Smith) and stooge, Andy Fastow (Tom Goodman-Hill) end up smeared with it. But Lucy Prebble's play is rather more than a simple tale ...

Time Out, London 2010

raders

n traders
n traders
wer ma

nia nia’s pow

w

s pow s pow nia’s p er ma s power ma er ma

nv

nv ations elephone co ations tions tions tions tions elephone co elephone elephone c ations vers in which they me elephone ations tions elephone ersa elephone vers vers ersa ring the st ring the st grandmother ing the st ing the st AP by in 2000-01 ... in 2000-01 ... in 2000-01 ... y Kris in 2000-01 ... AP by y Kris [AP [AP

NRON NRON NRON NRON

to pac publi age up a big sample of nothing and sell it age up a big sample of nothing and sell it age up a big sample of nothing and sell it age up a big sample of nothing and sell it age up a big sample of nothing and sell it age up a big sample of nothing and sell it to pac age up a big sample of nothing and sell it age up a big sample of nothing and sell it to pac zes self-belie es self-belie publi West o est o es self-belie publi , Samuel est o est oo , Samuel amuel amuel amuel West o zes self-belie zes self-belie publi est o est o est ooz

zes self-belie

es self-belie

Smith) and s
Smith) and s
Smith) and stoog

toog

oge,

Piggot Piggot iggott-Smith) and s

Smith) and s

A iggott-Smith) and s

Smith) and s
Smith) and s
Smith) and s
Smith) and stoog

A . But L Piggott-Smith) and s Andy Piggot Piggot iggot iggott iggott-Smith) and s iggott-Smith) and s end up smea than a simpl iggott-Smith) and s Piggot iggot iggott Andy iggot iggot end up smear end up smea . But Lu end up smea up smea up smeared with i up smeared with i ed with it. But . But Lu . But . But L . But Lu . But L . But L . But Lu ed with i e tale ... ed with i e tale ... than a simpl than a simple tale ... than a simple tale ... e tale ...

tions in which they me tions ations er ma

penly discussed manipul
wer ma

Enron traders openly discussed manipul California’s power market du telephone conversations in which they me

penly discussed manipul
n traders openly discussed manipul

nia’s pow elephone convers andmothers” during the st in 2000-01 ... [AP

NRON

nia elephone grandmother in 2000-01 ... aders openly discussed manipul s pow

nv
wer ma

nvers vers ing the st [AP by Kris

NRON

kage up a big sample of nothing and sell it

NRON

grandmother in 2000-01 ... elephone andmother elephone con elephone raders nia’s p

n traders

nia

n traders
n traders

nia’ raders wer ma

penly discussed manipul

s pow nia’s pow

nv

nia’s p er ma er ma nversations in which they me wer ma vers er ma in which they me nvers nia’ elephone conv ations elephone co elephone c tions tions tions tions in which they me ersations tions elephone c elephone elephone elephone elephone c elephone c elephone elephone c in 2000-01 ... in 2000-01 ... y K AP by AP b AP grandmother in 2000-01 ... gr in 2000-01 ... in 2000-01 ... during the st andmother in 2000-01 ... in 2000-01 ... in 2000-01 ... y K in 2000-01 ... in 2000-01 ... in 2000-01 ... in 2000-01 ... [AP in 2000-01 ... in 2000-01 ... by K AP by Kris

age up a big sample of nothing and sell it amuel West oozes self-belie age up a big sample of nothing and sell it age up a big sample of nothing and sell it age up a big sample of nothing and sell it age up a big sample of nothing and sell it age up a big sample of nothing and sell it

[AP

NRON

to package up a big sample of nothing and sell it public, Samuel Piggott-Smith) and s , Samuel West oozes self-belie iggott-Smith) and stooge, up smeared with it. But than a simple tale ...

Smith) and stoog

, Samuel iggot Piggot Piggot publi to pac

NRON NRON

age up a big sample of nothing and sell it

NRON

kage up a big sample of nothing and sell it age up a big sample of nothing and sell it age up a big sample of nothing and sell it age up a big sample of nothing and sell it est ooz

zes self-belie

age up a big sample of nothing and sell it

zes self-belie

age up a big sample of nothing and sell it age up a big sample of nothing and sell it age up a big sample of nothing and sell it age up a big sample of nothing and sell it est o age up a big sample of nothing and sell it es self-belie Andy . But Luc age up a big sample of nothing and sell it age up a big sample of nothing and sell it es self-belie Andy Fas Lucy Pr

Time

age up a big sample of nothing and sell it est oo age up a big sample of nothing and sell it est oo est oozes self-belie amuel W West o est o est ooz

zes self-belie

up smea amuel est o es self-belie A

Smith) and st

iggot Andy . But L . But Lu e ... ed with it. But . But L Piggot up smea . But Lu . But

nia’s p elephone elephone c in 2000-01 ...

age up a big sample of nothing and sell it age up a big sample of nothing and sell it est oozes self-belie es self-belie amuel amuel W A than a simpl

raders nia’s p in 2000-01 ...

age up a big sample of nothing and sell it age up a big sample of nothing and sell it up smeared with i than a simple tal e tale ...

ing the st

est oozes self-belie up smeared with i ed with it. But ed with i

“Ripping off those poor grandmothers”

6 / 40

SLIDE 11

Can You Spot the Competitive Equilibrium?

Efficient Equilibrium?

California, 2000

Spinning reserve prices PX prices $/MWh

100 150 50 200 250 10 20 30 40 50 60 70 Mon Tues Weds Weds Thurs Fri Sat Sun

California, July 2000 Enron traders openly discussed manipulating California’s power market during profanity-laced telephone conversations in which they merrily grandmothers” during the state’s energy crunch in 2000-01 ... [AP by Kristen Hays, 06/03/04]

NRON

to package up a big sample of nothing and sell it to a greedy public, Samuel West oozes self-belief; his boss, Ken Lay (Tim Piggott-Smith) and stooge, Andy Fastow (Tom Goodman-Hill) end up smeared with it. But Lucy Prebble's play is rather more than a simple tale ...

Time Out, London 2010

raders

n traders
n traders
wer ma

nia nia’s pow

w

s pow s pow nia’s p er ma s power ma er ma

nv

nv ations elephone co ations tions tions tions tions elephone co elephone elephone c ations vers in which they me elephone ations tions elephone ersa elephone vers vers ersa ring the st ring the st grandmother ing the st ing the st AP by in 2000-01 ... in 2000-01 ... in 2000-01 ... y Kris in 2000-01 ... AP by y Kris [AP [AP

NRON NRON NRON NRON

to pac publi age up a big sample of nothing and sell it age up a big sample of nothing and sell it age up a big sample of nothing and sell it age up a big sample of nothing and sell it age up a big sample of nothing and sell it age up a big sample of nothing and sell it to pac age up a big sample of nothing and sell it age up a big sample of nothing and sell it to pac zes self-belie es self-belie publi West o est o es self-belie publi , Samuel est o est oo , Samuel amuel amuel amuel West o zes self-belie zes self-belie publi est o est o est ooz

zes self-belie

es self-belie

Smith) and s
Smith) and s
Smith) and stoog

toog

oge,

Piggot Piggot iggott-Smith) and s

Smith) and s

A iggott-Smith) and s

Smith) and s
Smith) and s
Smith) and s
Smith) and stoog

A . But L Piggott-Smith) and s Andy Piggot Piggot iggot iggott iggott-Smith) and s iggott-Smith) and s end up smea than a simpl iggott-Smith) and s Piggot iggot iggott Andy iggot iggot end up smear end up smea . But Lu end up smea up smea up smeared with i up smeared with i ed with it. But . But Lu . But . But L . But Lu . But L . But L . But Lu ed with i e tale ... ed with i e tale ... than a simpl than a simple tale ... than a simple tale ... e tale ...

tions in which they me tions ations er ma

penly discussed manipul
wer ma

Enron traders openly discussed manipul California’s power market du telephone conversations in which they me

penly discussed manipul
n traders openly discussed manipul

nia’s pow elephone convers andmothers” during the st in 2000-01 ... [AP

NRON

nia elephone grandmother in 2000-01 ... aders openly discussed manipul s pow

nv
wer ma

nvers vers ing the st [AP by Kris

NRON

kage up a big sample of nothing and sell it

NRON

grandmother in 2000-01 ... elephone andmother elephone con elephone raders nia’s p

n traders

nia

n traders
n traders

nia’ raders wer ma

penly discussed manipul

s pow nia’s pow

nv

nia’s p er ma er ma nversations in which they me wer ma vers er ma in which they me nvers nia’ elephone conv ations elephone co elephone c tions tions tions tions in which they me ersations tions elephone c elephone elephone elephone elephone c elephone c elephone elephone c in 2000-01 ... in 2000-01 ... y K AP by AP b AP grandmother in 2000-01 ... gr in 2000-01 ... in 2000-01 ... during the st andmother in 2000-01 ... in 2000-01 ... in 2000-01 ... y K in 2000-01 ... in 2000-01 ... in 2000-01 ... in 2000-01 ... [AP in 2000-01 ... in 2000-01 ... by K AP by Kris

age up a big sample of nothing and sell it amuel West oozes self-belie age up a big sample of nothing and sell it age up a big sample of nothing and sell it age up a big sample of nothing and sell it age up a big sample of nothing and sell it age up a big sample of nothing and sell it

[AP

NRON

to package up a big sample of nothing and sell it public, Samuel Piggott-Smith) and s , Samuel West oozes self-belie iggott-Smith) and stooge, up smeared with it. But than a simple tale ...

Smith) and stoog

, Samuel iggot Piggot Piggot publi to pac

NRON NRON

age up a big sample of nothing and sell it

NRON

kage up a big sample of nothing and sell it age up a big sample of nothing and sell it age up a big sample of nothing and sell it age up a big sample of nothing and sell it est ooz

zes self-belie

age up a big sample of nothing and sell it

zes self-belie

age up a big sample of nothing and sell it age up a big sample of nothing and sell it age up a big sample of nothing and sell it age up a big sample of nothing and sell it est o age up a big sample of nothing and sell it es self-belie Andy . But Luc age up a big sample of nothing and sell it age up a big sample of nothing and sell it es self-belie Andy Fas Lucy Pr

Time

age up a big sample of nothing and sell it est oo age up a big sample of nothing and sell it est oo est oozes self-belie amuel W West o est o est ooz

zes self-belie

up smea amuel est o es self-belie A

Smith) and st

iggot Andy . But L . But Lu e ... ed with it. But . But L Piggot up smea . But Lu . But

nia’s p elephone elephone c in 2000-01 ...

age up a big sample of nothing and sell it age up a big sample of nothing and sell it est oozes self-belie es self-belie amuel amuel W A than a simpl

raders nia’s p in 2000-01 ...

age up a big sample of nothing and sell it age up a big sample of nothing and sell it up smeared with i than a simple tal e tale ...

ing the st

est oozes self-belie up smeared with i ed with it. But ed with i

“Ripping off those poor grandmothers” Not efficient?

6 / 40

SLIDE 12

Can You Spot the Competitive Equilibrium?

Efficient Equilibrium?

Australia, January 16, 2007 Price (Aus $/MWh) Volume (MW)

Demand Demand

Prices Prices

24:00 23:00 22:00 21:00 20:00 19:00 18:00 17:00 16:00 15:00 14:00 13:00 12:00 11:00 10:00 09:00 08:00 07:00 06:00 05:00 04:00 03:00 02:00 01:00 00:00 24:00 23:00 22:00 21:00 20:00 19:00 18:00 17:00 16:00 15:00 14:00 13:00 12:00 11:00 10:00 09:00 08:00 07:00 06:00 05:00 04:00 03:00 02:00 01:00 00:00

19,000 10,000 1,400 1,200 1,000 800 600 400 200 1,000

1,000
1,500

1,000

1,000

9,000 8,000 10,000 7,000 6,000 5,000 4,000 3,000 2,000 1,000

Tasmania Victoria

7 / 40

SLIDE 13

Can You Spot the Competitive Equilibrium?

Efficient Equilibrium?

Australia, January 16, 2007 Price (Aus $/MWh) Volume (MW)

Demand Demand

Prices Prices

24:00 23:00 22:00 21:00 20:00 19:00 18:00 17:00 16:00 15:00 14:00 13:00 12:00 11:00 10:00 09:00 08:00 07:00 06:00 05:00 04:00 03:00 02:00 01:00 00:00 24:00 23:00 22:00 21:00 20:00 19:00 18:00 17:00 16:00 15:00 14:00 13:00 12:00 11:00 10:00 09:00 08:00 07:00 06:00 05:00 04:00 03:00 02:00 01:00 00:00

19,000 10,000 1,400 1,200 1,000 800 600 400 200 1,000

1,000
1,500

1,000

1,000

9,000 8,000 10,000 7,000 6,000 5,000 4,000 3,000 2,000 1,000

Tasmania Victoria

Fires cause chaos – Is this efficient?

7 / 40

SLIDE 14

Can You Spot the Competitive Equilibrium?

Efficient Equilibrium?

Midwest ISO today: Friday afternoon, March 4, 2011 3:30 p.m.

2000.00

8 / 40

SLIDE 15

Can You Spot the Competitive Equilibrium?

Efficient Equilibrium?

Midwest ISO today: Friday afternoon, March 4, 2011 3:50 p.m.

762.55

9 / 40

SLIDE 16

Can You Spot the Competitive Equilibrium?

Efficient Equilibrium?

Midwest ISO today: Friday afternoon, March 4, 2011 4:15 p.m.

1881.07

10 / 40

SLIDE 17

Can You Spot the Competitive Equilibrium?

Efficient Equilibrium?

Midwest ISO today: Friday afternoon, March 4, 2011 4:30 p.m.

115.68

11 / 40

SLIDE 18

Can You Spot the Competitive Equilibrium?

Efficient Equilibrium?

Texas today: Winter of 2011

5am 10am 3pm 8pm

−500

1000 2000

3000

$/MWh

February 2, 2011

$/MWh

−10 10 20 40 60

80

5am 10am 3pm 8pm

Power Prices in Texas

January 31, 2011

12 / 40

SLIDE 19

Can You Spot the Competitive Equilibrium?

Efficient Equilibrium?

Texas today: Winter of 2011

5am 10am 3pm 8pm

−500

1000 2000

3000

$/MWh

February 2, 2011

$/MWh

−10 10 20 40 60

80

5am 10am 3pm 8pm

Power Prices in Texas

January 31, 2011

There will be multiple autopsies of the causes for the latest power breakdowns ... Who profited

ff this near-meltdown and what can be done to incentivize power producers to maintain

adequate reserve capacity for emergencies rather than waiting for emergency windfalls? – HOUSTON CHRONICLE, Feb 12, 2011 New report hits ERCOT, electricity deregulation: A report released Monday concludes that electric deregulation has cost Texas residential consumers more than $11 billion in higher rates... – Dallas Morning News, Feb 14, 2011

12 / 40

SLIDE 20

Can You Spot the Competitive Equilibrium?

Efficient Equilibrium?

Texas today: Winter of 2011

What do the experts say?

5am 10am 3pm 8pm

−500 1000 2000 3000

$/MWh

February 2, 2011

$/MWh

−10 10 20 40 60 80

5am 10am 3pm 8pm

Power Prices in Texas

January 31, 2011

13 / 40

SLIDE 21

Can You Spot the Competitive Equilibrium?

Efficient Equilibrium?

Texas today: Winter of 2011

What do the experts say?

5am 10am 3pm 8pm

−500 1000 2000 3000

$/MWh

February 2, 2011

$/MWh

−10 10 20 40 60 80

5am 10am 3pm 8pm

Power Prices in Texas

January 31, 2011

...long-term contracts could reduce market power... ...the

larger the proportion of total demand auctioned in advance, the lower are both the contract and the average spot price of energy... –M. Soledad Arellano and Pablo Serra, 2010

13 / 40

SLIDE 22

Can You Spot the Competitive Equilibrium?

Efficient Equilibrium?

Texas today: Winter of 2011

What do the experts say?

5am 10am 3pm 8pm

−500 1000 2000 3000

$/MWh

February 2, 2011

$/MWh

−10 10 20 40 60 80

5am 10am 3pm 8pm

Power Prices in Texas

January 31, 2011

...long-term contracts could reduce market power... ...the

larger the proportion of total demand auctioned in advance, the lower are both the contract and the average spot price of energy... –M. Soledad Arellano and Pablo Serra, 2010

...forward markets do not mitigate market power... ...forward

markets systematically enhance market power in some symmetric capacity-constrained markets...” –Frederic Murphy and Yves Smeers, 2010

13 / 40

SLIDE 23

Can You Spot the Competitive Equilibrium?

Efficient Equilibrium?

New Zealand today: March 25, 2011

A typical day in the New Zealand power market on the N. Island

Stratford Otahuhu

http://www.electricityinfo.co.nz/

50 100

Nodal Power Prices in NZ: $/MWh

4am 9am 2pm 7pm 14 / 40

SLIDE 24

Can You Spot the Competitive Equilibrium?

Efficient Equilibrium?

New Zealand today: March 26, 2011

$25 million dollars extracted by the generators in just six hours

Stratford Otahuhu

http://www.electricityinfo.co.nz/ 4am 9am 2pm 7pm

10,000 20,000

Nodal Power Prices in NZ: $/MWh

15 / 40

SLIDE 25

Can You Spot the Competitive Equilibrium?

Efficient Equilibrium?

New Zealand today: March 26, 2011

$25 million dollars extracted by the generators in just six hours

Stratford Otahuhu

http://www.electricityinfo.co.nz/ 4am 9am 2pm 7pm

10,000 20,000

Nodal Power Prices in NZ: $/MWh

Efficient?

Energy consultant Bryan Leyland said the high wholesale prices showed how dysfunctional the electricity market is. Jacking the prices up sends no worthwhile signal to anyone — it is nothing to do with a shortage of generating capacity, he said. It just exposes the nonsense of it all.

15 / 40

SLIDE 26

Can You Spot the Competitive Equilibrium?

Efficient Equilibrium?

New Zealand today: March 26, 2011

$25 million dollars extracted by the generators in just six hours

Stratford Otahuhu

http://www.electricityinfo.co.nz/ 4am 9am 2pm 7pm

10,000 20,000

Nodal Power Prices in NZ: $/MWh

Efficient!

Preliminary view of NZ Electrical Authority: Genesis was not guilty

f “manipulative”, ... or “deceptive” conduct.

16 / 40

SLIDE 27

Can You Spot the Competitive Equilibrium?

Efficient Equilibrium?

New Zealand today: March 26, 2011

$25 million dollars extracted by the generators in just six hours

Stratford Otahuhu

http://www.electricityinfo.co.nz/ 4am 9am 2pm 7pm

10,000 20,000

Nodal Power Prices in NZ: $/MWh

Efficient!

Preliminary view of NZ Electrical Authority: Genesis was not guilty

f “manipulative”, ... or “deceptive” conduct. However, high prices threatened to

undermine confidence in, and ... damage the integrity and reputation of the wholesale electricity market

3:59 PM Friday May 6, 2011 www.nzherald.co.nz 16 / 40

SLIDE 28

Can You Spot the Competitive Equilibrium?

Efficient Equilibrium?

It’s not just about power!

Retail prices of onions in India

Indian Rupee per kg

Source: Ministry of Consumer Afgairs

Jan Mar May July Sep Nov Jan Mar May July Sep Nov Jan

40 50 30 10

10

20 Chennai Delhi Mumbai Patna 2009 2010 2011

Delhi Mumbai

Rs. 60
Rs. 55
Rs. 50
Rs. 44
Rs. 37
Rs. 43
Rs. 25
Rs. 13
Rs. 14
Rs. 9
Rs. 15.5
Rs. 29

Dec 20 Dec 27 Jan 10 Jan 24 Feb 7 Feb 11

Sharp Rise & Sharp Fall

India’s ban on onion exports to Nepal ... caused wholesale price to jump 50% in a week. – NepaliEconomy.com, Jan 3, 2011 Soaring onion prices pushed food inflation again to a double-digit mark... – Indian Express, Feb 12, 2011 In India, onion prices are as politically sensitive as mortgage rates are in

Australia. ... rising cost of the staple has helped change governments in

India. – Fidelity International, Jan 2011

17 / 40

SLIDE 29

Competitive Equilibria in Dynamic Markets

Purchase Price $/MWh Previous week Spinning reserve prices PX prices $/MWh 100 150 50 200 250 10 20 30 40 50 60 70

Texas: February 2, 2011 California: July 2000 Illinois: July 1998 Ontario: November, 2005

1000 2000 3000 4000 5000 Mon Tues Weds Thurs Fri Mon Tues Weds Weds Thurs Fri Sat Sun Tues Weds Thurs

Time 3 6 9 12 15 18 21 3 6 9 12 15 18 21 3 6 9 12 15 18 21

Demand in MW Last Updated 11:00 AM Predispatch 1975.11 Dispatch 19683.5 Hourly Ontario Energy Price $/MWh Last Updated 11:00 AM Predispatch 72.79 Dispatch 90.82

2000 21000 18000 15000 1500 1000 500 Forecast Prices Forecast Demand

5am 10am 3pm 8pm

−500

1000 2000

3000

$/MWh Average price is usually $30

$/MWh

Competitive Equilibria in Dynamic Markets

18 / 40

SLIDE 30

Competitive Equilibria in Dynamic Markets

Electricity Markets Today

Two coupled markets

Day-ahead market (DAM): Cleared one day prior to the production and delivery of energy: The ISO generates a schedule of generators to supply specific levels of power for each hour over the next 24 hour period.

Facilitates the scheduling of generating units, and allows for hedging against uncertainty

19 / 40

SLIDE 31

Competitive Equilibria in Dynamic Markets

Electricity Markets Today

Two coupled markets

Day-ahead market (DAM): Cleared one day prior to the production and delivery of energy: The ISO generates a schedule of generators to supply specific levels of power for each hour over the next 24 hour period.

Facilitates the scheduling of generating units, and allows for hedging against uncertainty

Real-time market (RTM): As supply and demand are not perfectly predictable, the RTM plays the role of fine-tuning this resource allocation process RTM is the focus here

19 / 40

SLIDE 32

Competitive Equilibria in Dynamic Markets

RTM Model

Dynamic model for reserves

Cho & Meyn model:

Math model explains volatile prices in power markets. SIAM News, Robinson. 2005.

R(t) = Available power − Demand = G(t) − D(t) D(t) = Actual demand − Forecast

For computation: Deviation in demand D is modeled as Brownian motion

G(t): Deviation in on-line capacity from day-ahead market

20 / 40

SLIDE 33

Competitive Equilibria in Dynamic Markets

RTM Model

Dynamic model for reserves

Cho & Meyn model:

Math model explains volatile prices in power markets. SIAM News, Robinson. 2005.

R(t) = Available power − Demand = G(t) − D(t) D(t) = Actual demand − Forecast

For computation: Deviation in demand D is modeled as Brownian motion

G(t): Deviation in on-line capacity from day-ahead market Economic Friction Generation cannot increase instantaneously: For all t ≥ 0 and t′ > t, G(t′) − G(t) t′ − t ≤ ζ

20 / 40

SLIDE 34

Competitive Equilibria in Dynamic Markets

RTM Model

Dynamic model for reserves

Cho & Meyn model:

Math model explains volatile prices in power markets. SIAM News, Robinson. 2005.

R(t) = Available power − Demand = G(t) − D(t) D(t) = Actual demand − Forecast

For computation: Deviation in demand D is modeled as Brownian motion

G(t): Deviation in on-line capacity from day-ahead market Economic Friction Generation cannot increase instantaneously: For all t ≥ 0 and t′ > t, G(t′) − G(t) t′ − t ≤ ζ In recent work we also impose lower bounds on generation, as well as network constraints.

20 / 40

SLIDE 35

Competitive Equilibria in Dynamic Markets

Market Analysis: A beautiful world...

Perfect competition

Dynamic market equilibria under the most ideal circumstances:

21 / 40

SLIDE 36

Competitive Equilibria in Dynamic Markets

Market Analysis: A beautiful world...

Perfect competition

Dynamic market equilibria under the most ideal circumstances: Price manipulation is excluded

21 / 40

SLIDE 37

Competitive Equilibria in Dynamic Markets

Market Analysis: A beautiful world...

Perfect competition

Dynamic market equilibria under the most ideal circumstances: Price manipulation is excluded

No “ENRON games” – no “market power”

21 / 40

SLIDE 38

Competitive Equilibria in Dynamic Markets

Market Analysis: A beautiful world...

Perfect competition

Dynamic market equilibria under the most ideal circumstances: Price manipulation is excluded

No “ENRON games” – no “market power”

Externalities are disregarded

No government mandates

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SLIDE 39

Competitive Equilibria in Dynamic Markets

Market Analysis: A beautiful world...

Perfect competition

Dynamic market equilibria under the most ideal circumstances: Price manipulation is excluded

No “ENRON games” – no “market power”

Externalities are disregarded

No government mandates

When wind generation is included, the consumers own and operate these resources

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SLIDE 40

Competitive Equilibria in Dynamic Markets

Market Analysis: A beautiful world...

Perfect competition

Dynamic market equilibria under the most ideal circumstances: Price manipulation is excluded

No “ENRON games” – no “market power”

Externalities are disregarded

No government mandates

When wind generation is included, the consumers own and operate these resources What does an efficient equilibrium look like?

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SLIDE 41

Competitive Equilibria in Dynamic Markets

Market Analysis

Second Welfare Theorem

Efficient Equilibrium max K(G) = E

e−γt

WS(t) + WD(t)

dt
.

s.t. GS(t) = GD(t) for all t

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SLIDE 42

Competitive Equilibria in Dynamic Markets

Market Analysis

Second Welfare Theorem

Efficient Equilibrium max K(G) = E

e−γt

WS(t) + WD(t)

dt
.

s.t. GS(t) = GD(t) for all t Special case: Welfare functions are piecewise linear,

WS(t) := P(t)GS(t) − cGS(t) WD(t) := v min(D(t), GD(t)) − cbo max(0, −RD(t)) − P(t)GD(t)

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SLIDE 43

Competitive Equilibria in Dynamic Markets

Market Analysis

Second Welfare Theorem

Efficient Equilibrium max K(G) = E

e−γt

WS(t) + WD(t)

dt
s.t.

GS(t) = GD(t) for all t Key component of equilibrium theory: Perfect competition Price-taking assumption: The price of power P(t) in the RTM is assumed to be exogenous (it does not depend on the decisions of the market agents).

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SLIDE 44

Competitive Equilibria in Dynamic Markets

Market Analysis

Second Welfare Theorem

Second Welfare Theorem ⇐ ⇒ Lagrangian Decomposition max K(G) = max

GS E

e−γt

WS(t) + λ(t)GS(t)

dt
+ max

GD E

e−γt

WD(t) − λ(t)GD(t)

dt
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SLIDE 45

Competitive Equilibria in Dynamic Markets

Market Analysis

Second Welfare Theorem

Second Welfare Theorem ⇐ ⇒ Lagrangian Decomposition max K(G) = max

GS E

e−γt

WS(t) + λ(t)GS(t)

dt
+ max

GD E

e−γt

WD(t) − λ(t)GD(t)

dt
Assume: Social planner’s problem has a solution,

and there is no duality gap.

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SLIDE 46

Competitive Equilibria in Dynamic Markets

Market Analysis

Second Welfare Theorem

Second Welfare Theorem ⇐ ⇒ Lagrangian Decomposition max K(G) = max

GS E

e−γt

WS(t) + λ(t)GS(t)

dt
+ max

GD E

e−γt

WD(t) − λ(t)GD(t)

dt
Assume: Social planner’s problem has a solution,

and there is no duality gap. Then P ∗(t) = P(t) + λ∗(t) provides an efficient equilibrium.

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SLIDE 47

Competitive Equilibria in Dynamic Markets

Market Analysis

Second Welfare Theorem

Second Welfare Theorem ⇐ ⇒ Lagrangian Decomposition max K(G) = max

GS E

e−γt

WS(t) + λ(t)GS(t)

dt
+ max

GD E

e−γt

WD(t) − λ(t)GD(t)

dt
Assume: Social planner’s problem has a solution,

and there is no duality gap. Then P ∗(t) = P(t) + λ∗(t) provides an efficient equilibrium. What does an efficient equilibrium look like?

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SLIDE 48

Competitive Equilibria in Dynamic Markets

What does an efficient equilibrium look like?

Answer: Marginal value

Equilibrium price The equilibrium price process is a function of equilibrium reserves: P ∗(t) = p∗(Re(t))

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SLIDE 49

Competitive Equilibria in Dynamic Markets

What does an efficient equilibrium look like?

Answer: Marginal value

Equilibrium price The equilibrium price process is a function of equilibrium reserves: P ∗(t) = p∗(Re(t)) P ∗(t) = p∗(Re(t)) is the marginal value of power to the consumer

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SLIDE 50

Competitive Equilibria in Dynamic Markets

What does an efficient equilibrium look like?

Answer: Marginal value

Equilibrium price The equilibrium price process is a function of equilibrium reserves: P ∗(t) = p∗(Re(t)) P ∗(t) = p∗(Re(t)) is the marginal value of power to the consumer For linear cost/utility, marginal value is piecewise constant, p∗(re) = (v + cbo)I{re < 0}

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SLIDE 51

Competitive Equilibria in Dynamic Markets

Market Equilibrium

Price dynamics

v + c

bo

r∗

Prices Reserves Normalized demand

P ∗(t) = p∗(Re(t)): The marginal value of power to the consumer

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SLIDE 52

Competitive Equilibria in Dynamic Markets

Market Equilibrium

Price dynamics

v + c

bo

r∗

Prices Reserves Normalized demand

P ∗(t) = p∗(Re(t)): The marginal value of power to the consumer

Smoother prices obtained when cost/utility are strictly convex

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SLIDE 53

Competitive Equilibria in Dynamic Markets

Familiar, right?

Real-world price dynamics

Purchase Price $/MWh Previous week Spinning reserve prices PX prices $/MWh 100 150 50 200 250 10 20 30 40 50 60 70

Texas: February 2, 2011 California: July 2000 Illinois: July 1998 Ontario: November, 2005

1000 2000 3000 4000 5000 Mon Tues Weds Thurs Fri Mon Tues Weds Weds Thurs Fri Sat Sun Tues Weds Thurs

Time 3 6 9 12 15 18 21 3 6 9 12 15 18 21 3 6 9 12 15 18 21

Demand in MW Last Updated 11:00 AM Predispatch 1975.11 Dispatch 19683.5 Hourly Ontario Energy Price $/MWh Last Updated 11:00 AM Predispatch 72.79 Dispatch 90.82

2000 21000 18000 15000 1500 1000 500 Forecast Prices Forecast Demand

5am 10am 3pm 8pm

−500

1000 2000

3000

$/MWh Average price is usually $30

$/MWh

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SLIDE 54

Competitive Equilibria in Dynamic Markets

Sustainable business?

Marginal value of electricity may be v + cbo = $100,000/MWh!

Purchase Price $/MWh Previous week Spinning reserve prices PX prices $/MWh 100 150 50 200 250 10 20 30 40 50 60 70

Texas: February 2, 2011 California: July 2000 Illinois: July 1998 Ontario: November, 2005

1000 2000 3000 4000 5000 Mon Tues Weds Thurs Fri Mon Tues Weds Weds Thurs Fri Sat Sun Tues Weds Thurs

Time 3 6 9 12 15 18 21 3 6 9 12 15 18 21 3 6 9 12 15 18 21 Demand in MW Last Updated 11:00 AM Predispatch 1975.11 Dispatch 19683.5 Hourly Ontario Energy Price $/MWh Last Updated 11:00 AM Predispatch 72.79 Dispatch 90.82

2000 21000 18000 15000 1500 1000 500 Forecast Prices Forecast Demand 5am 10am 3pm 8pm

−500

1000 2000

3000

$/MWh Average price is usually $30 $/MWh

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SLIDE 55

Competitive Equilibria in Dynamic Markets

Sustainable business?

Marginal value of electricity may be v + cbo = $100,000/MWh!

Purchase Price $/MWh Previous week Spinning reserve prices PX prices $/MWh 100 150 50 200 250 10 20 30 40 50 60 70

Texas: February 2, 2011 California: July 2000 Illinois: July 1998 Ontario: November, 2005

1000 2000 3000 4000 5000 Mon Tues Weds Thurs Fri Mon Tues Weds Weds Thurs Fri Sat Sun Tues Weds Thurs

Time 3 6 9 12 15 18 21 3 6 9 12 15 18 21 3 6 9 12 15 18 21 Demand in MW Last Updated 11:00 AM Predispatch 1975.11 Dispatch 19683.5 Hourly Ontario Energy Price $/MWh Last Updated 11:00 AM Predispatch 72.79 Dispatch 90.82

2000 21000 18000 15000 1500 1000 500 Forecast Prices Forecast Demand 5am 10am 3pm 8pm

−500

1000 2000

3000

$/MWh Average price is usually $30 $/MWh

However,

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SLIDE 56

Competitive Equilibria in Dynamic Markets

Sustainable business?

Marginal value of electricity may be v + cbo = $100,000/MWh!

Purchase Price $/MWh Previous week Spinning reserve prices PX prices $/MWh 100 150 50 200 250 10 20 30 40 50 60 70

Texas: February 2, 2011 California: July 2000 Illinois: July 1998 Ontario: November, 2005

1000 2000 3000 4000 5000 Mon Tues Weds Thurs Fri Mon Tues Weds Weds Thurs Fri Sat Sun Tues Weds Thurs

Time 3 6 9 12 15 18 21 3 6 9 12 15 18 21 3 6 9 12 15 18 21 Demand in MW Last Updated 11:00 AM Predispatch 1975.11 Dispatch 19683.5 Hourly Ontario Energy Price $/MWh Last Updated 11:00 AM Predispatch 72.79 Dispatch 90.82

2000 21000 18000 15000 1500 1000 500 Forecast Prices Forecast Demand 5am 10am 3pm 8pm

−500

1000 2000

3000

$/MWh Average price is usually $30 $/MWh

However, Theorem 2: In this equilibrium, the average price is precisely the marginal cost c.

Proof: Lagrangian relaxation of initial condition.

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SLIDE 57

Competitive Equilibria in Dynamic Markets

Sustainable business?

Marginal value of electricity may be v + cbo = $100,000/MWh!

Purchase Price $/MWh Previous week Spinning reserve prices PX prices $/MWh 100 150 50 200 250 10 20 30 40 50 60 70

Texas: February 2, 2011 California: July 2000 Illinois: July 1998 Ontario: November, 2005

1000 2000 3000 4000 5000 Mon Tues Weds Thurs Fri Mon Tues Weds Weds Thurs Fri Sat Sun Tues Weds Thurs

Time 3 6 9 12 15 18 21 3 6 9 12 15 18 21 3 6 9 12 15 18 21 Demand in MW Last Updated 11:00 AM Predispatch 1975.11 Dispatch 19683.5 Hourly Ontario Energy Price $/MWh Last Updated 11:00 AM Predispatch 72.79 Dispatch 90.82

2000 21000 18000 15000 1500 1000 500 Forecast Prices Forecast Demand 5am 10am 3pm 8pm

−500

1000 2000

3000

$/MWh Average price is usually $30 $/MWh

However, Theorem 2: In this equilibrium, the average price is precisely the marginal cost c.

Proof: Lagrangian relaxation of initial condition.

Is this a sustainable business?

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SLIDE 58

Coping with Uncertainty and Constraints

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SLIDE 59

Coping with Uncertainty and Constraints

Network Constraints

Entropic prices

What is marginal value? It is not always obvious. With the introduction of network constraints,

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SLIDE 60

Coping with Uncertainty and Constraints

Network Constraints

Entropic prices

What is marginal value? It is not always obvious. With the introduction of network constraints, Prices can go well beyond marginal value Prices can go well below zero

See [Wang et. al., 2011]

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SLIDE 61

Coping with Uncertainty and Constraints

Network Constraints

Entropic prices

What is marginal value? It is not always obvious. With the introduction of network constraints, Prices can go well beyond marginal value Prices can go well below zero

See [Wang et. al., 2011]

Without price-caps, Australia might look like an efficient equilibrium:

Price (Aus $/MWh) Price (Aus $/MWh) Volume (MW) Volume (MW)

Demand Demand Prices Prices

24:00 23:00 22:00 21:00 20:00 19:00 18:00 17:00 16:00 15:00 14:00 13:00 12:00 11:00 10:00 09:00 08:00 07:00 06:00 05:00 04:00 03:00 02:00 01:00 00:00 24:00 23:00 22:00 21:00 20:00 19:00 18:00 17:00 16:00 15:00 14:00 13:00 12:00 11:00 10:00 09:00 08:00 07:00 06:00 05:00 04:00 03:00 02:00 01:00 00:00

19,000 10,000 1,400 1,200 1,000 800 600 400 200 1,000

1,000
1,500

1,000

1,000

9,000 8,000 10,000 7,000 6,000 5,000 4,000 3,000 2,000 1,000

Tasmania Victoria

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SLIDE 62

Coping with Uncertainty and Constraints

The Value of Volatile Resources

What is the impact of wind, solar, or tidal generation?

Requires consideration of coupled RTM and DAM. In summary:

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SLIDE 63

Coping with Uncertainty and Constraints

The Value of Volatile Resources

What is the impact of wind, solar, or tidal generation?

Requires consideration of coupled RTM and DAM. In summary: cv

0.1 0.2 0.3 0.4 k = 0 k = 5 k = 10 k = 15 k = 20

Optimal Reserve Level

20 40 60 80 100 120 140 x 10

3

Optimal reserves rise:

Optimal reserves increase with in- creasing penetration k, or coefficient

f variation cv.

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SLIDE 64

Coping with Uncertainty and Constraints

The Value of Volatile Resources

What is the impact of wind, solar, or tidal generation?

Requires consideration of coupled RTM and DAM. In summary: cv

0.1 0.2 0.3 0.4 k = 0 k = 5 k = 10 k = 15 k = 20

Optimal Reserve Level

20 40 60 80 100 120 140 x 10

3

Optimal reserves rise:

Optimal reserves increase with in- creasing penetration k, or coefficient

f variation cv.

⇒ Social welfare falls with wind.

[Value of Volatile Resources, CDC, 2010]

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SLIDE 65

Coping with Uncertainty and Constraints

The Value of Volatile Resources

Distribution of welfare (consumers command wind resources)

With increased volatility: Consumer welfare falls, supplier welfare rises:

0.1 0.2 0.3 0.4 0.1 0.2 0.3 0.4

x 10

6

Supplier Welfare

k = 0 k = 5 k = 10 k = 15 k = 20

x 10

6

Consumer Welfare

10 5 15 k = 0 k = 5 k = 10 k = 15 k = 20 3 4 5

cv

Penetration k, coefficient of variation cv.

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SLIDE 66

Conclusions

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SLIDE 67

Conclusions

Economics and Kontroll

Distributed control and prices

The current RTM paradigm is doomed to fail:

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SLIDE 68

Conclusions

Economics and Kontroll

Distributed control and prices

The current RTM paradigm is doomed to fail: ⊲ In the competitive equilibrium nirvana: Volatile prices combined with low average-prices will halt investment.

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SLIDE 69

Conclusions

Economics and Kontroll

Distributed control and prices

The current RTM paradigm is doomed to fail: ⊲ In the competitive equilibrium nirvana: Volatile prices combined with low average-prices will halt investment. ⊲ In the real world? Strategic behavior can lead to a new crisis each year!

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SLIDE 70

Conclusions

Economics and Kontroll

Distributed control and prices

The current RTM paradigm is doomed to fail: ⊲ In the competitive equilibrium nirvana: Volatile prices combined with low average-prices will halt investment. ⊲ In the real world? Strategic behavior can lead to a new crisis each year! However,

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SLIDE 71

Conclusions

Economics and Kontroll

Distributed control and prices

The current RTM paradigm is doomed to fail: ⊲ In the competitive equilibrium nirvana: Volatile prices combined with low average-prices will halt investment. ⊲ In the real world? Strategic behavior can lead to a new crisis each year! However, No one of us has all the answers!

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SLIDE 72

Conclusions

Economics and Kontroll

Distributed control and prices

The current RTM paradigm is doomed to fail: ⊲ In the competitive equilibrium nirvana: Volatile prices combined with low average-prices will halt investment. ⊲ In the real world? Strategic behavior can lead to a new crisis each year! However, No one of us has all the answers! Collaboration is required — Between researchers in economics, systems sciences, statistical sciences, and power engineers.

How could two smart people come to such different conclusions? I had to get to the bottom of this. –MacKay 2009

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SLIDE 73

Conclusions

Economics and Kontroll

Distributed control and prices

The current RTM paradigm is doomed to fail: ⊲ In the competitive equilibrium nirvana: Volatile prices combined with low average-prices will halt investment. ⊲ In the real world? Strategic behavior can lead to a new crisis each year! However, No one of us has all the answers! Collaboration is required — Between researchers in economics, systems sciences, statistical sciences, and power engineers.

How could two smart people come to such different conclusions? I had to get to the bottom of this. –MacKay 2009

A gentle debate. Please, no shouting!

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SLIDE 74

Conclusions

Economics and Kontroll

Economics for an Entropic Grid

How to create policies to protect participants on both sides of the market, while creating incentives for R&D on renewable energy? Our community must consider long-term planning and policy, along with traditional systems operations

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SLIDE 75

Conclusions

Economics and Kontroll

Economics for an Entropic Grid

How to create policies to protect participants on both sides of the market, while creating incentives for R&D on renewable energy? Our community must consider long-term planning and policy, along with traditional systems operations Planning and Policy, includes Markets & Competition

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SLIDE 76

Conclusions

Economics and Kontroll

Economics for an Entropic Grid

How to create policies to protect participants on both sides of the market, while creating incentives for R&D on renewable energy? Our community must consider long-term planning and policy, along with traditional systems operations Planning and Policy, includes Markets & Competition Evolution?

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SLIDE 77

Conclusions

Economics and Kontroll

Economics for an Entropic Grid

How to create policies to protect participants on both sides of the market, while creating incentives for R&D on renewable energy? Our community must consider long-term planning and policy, along with traditional systems operations Planning and Policy, includes Markets & Competition Evolution? Too slow!

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SLIDE 78

Conclusions

Economics and Kontroll

Economics for an Entropic Grid

How to create policies to protect participants on both sides of the market, while creating incentives for R&D on renewable energy? Our community must consider long-term planning and policy, along with traditional systems operations Planning and Policy, includes Markets & Competition Evolution? Too slow! What we need is Intelligent Design

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SLIDE 79

Conclusions

Economics and Kontroll

Economics for an Entropic Grid

⊲ Real-world issues: Incorporate dynamics and uncertainty in a strategic setting

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SLIDE 80

Conclusions

Economics and Kontroll

Economics for an Entropic Grid

⊲ Real-world issues: Incorporate dynamics and uncertainty in a strategic setting ⊲ Beyond efficiency: The economic notion of efficiency disregards issues such as reliability, emissions, public acceptance, or public safety.

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SLIDE 81

Conclusions

Economics and Kontroll

Economics for an Entropic Grid

⊲ Real-world issues: Incorporate dynamics and uncertainty in a strategic setting ⊲ Beyond efficiency: The economic notion of efficiency disregards issues such as reliability, emissions, public acceptance, or public safety. ⊲ Long-term incentives: How to create policies to protect participants on both sides of the market, while creating incentives for R&D on renewable energy?

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SLIDE 82

Conclusions

Economics and Kontroll

Economics for an Entropic Grid

⊲ Real-world issues: Incorporate dynamics and uncertainty in a strategic setting ⊲ Beyond efficiency: The economic notion of efficiency disregards issues such as reliability, emissions, public acceptance, or public safety. ⊲ Long-term incentives: How to create policies to protect participants on both sides of the market, while creating incentives for R&D on renewable energy? Approach: Follow the example of highway engineering Analysis of strategic behavior will be possible, if agent behavior is suitably constrained

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SLIDE 83

Conclusions

Economics and Kontroll

Economics for an Entropic Grid

⊲ Real-world issues: Incorporate dynamics and uncertainty in a strategic setting ⊲ Beyond efficiency: The economic notion of efficiency disregards issues such as reliability, emissions, public acceptance, or public safety. ⊲ Long-term incentives: How to create policies to protect participants on both sides of the market, while creating incentives for R&D on renewable energy? Approach: Follow the example of highway engineering Analysis of strategic behavior will be possible, if agent behavior is suitably constrained The economic security of the region is at stake: We need well-designed lanes and speed limits in the energy highway!

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SLIDE 84

Conclusions

Concluding Remarks

An Entropic Grid may emerge as a result of many of the proposed Smart Grid initiatives Decision & control, simulation & learning provide tools that will help to design an intelligent grid

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SLIDE 85

Conclusions

Concluding Remarks

An Entropic Grid may emerge as a result of many of the proposed Smart Grid initiatives Decision & control, simulation & learning provide tools that will help to design an intelligent grid We must move beyond the traditional static competitive equilibrium analysis We must move beyond the traditional myopic goal of economic efficiency, taking into account “externalities” such as sustainability and reliability

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SLIDE 86

Conclusions

Concluding Remarks

An Entropic Grid may emerge as a result of many of the proposed Smart Grid initiatives Decision & control, simulation & learning provide tools that will help to design an intelligent grid We must move beyond the traditional static competitive equilibrium analysis We must move beyond the traditional myopic goal of economic efficiency, taking into account “externalities” such as sustainability and reliability The best architecture for tomorrow’s energy highway? This is the central open question.

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SLIDE 87

Conclusions

Concluding Remarks

An Entropic Grid may emerge as a result of many of the proposed Smart Grid initiatives Decision & control, simulation & learning provide tools that will help to design an intelligent grid We must move beyond the traditional static competitive equilibrium analysis We must move beyond the traditional myopic goal of economic efficiency, taking into account “externalities” such as sustainability and reliability The best architecture for tomorrow’s energy highway? This is the central open question. Its solution opens many exciting research challenges!

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SLIDE 88

Conclusions

Thanks!

Celebrating with Dutch Babies after finishing part of this work

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SLIDE 89

References

Control Techniques

FOR

Complex Networks

Sean Meyn

Pre-publication version for on-line viewing. Monograph available for purchase at your favorite retailer More information available at http://www.cambridge.org/us/catalogue/catalogue.asp?isbn=9780521884419

Markov Chains and Stochastic Stability

S. P. Meyn and R. L. Tweedie

August 2008 Pre-publication version for on-line viewing. Monograph to appear Februrary 2009

π(f) < ∞ ∆V (x) ≤ −f(x) + bIC(x) P n(x, · ) − πf → 0 sup

C

Ex[SτC(f)] < ∞

References

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SLIDE 90

References

G. Wang, M. Negrete-Pincetic, A. Kowli, E. Shafieepoorfard, S. Meyn, and U. Shanbhag.

Dynamic competitive equilibria in electricity markets. In A. Chakrabortty and M. Illic, editors, Control and Optimization Theory for Electric Smart Grids. Springer, 2011.

M. Negrete-Pincetic and S. Meyn. Intelligence by design for the entropic grid. In IEEE PES

11: Power Energy Society General Meeting, 2011.

G. Wang, A. Kowli, M. Negrete-Pincetic, E. Shafieepoorfard, and S. Meyn.

A control theorist’s perspective on dynamic competitive equilibria in electricity markets. In

Proc. 18th World Congress of the International Federation of Automatic Control (IFAC),

Milano, Italy, 2011.

S. Meyn, M. Negrete-Pincetic, G. Wang, A. Kowli, and E. Shafieepoorfard. The value of

volatile resources in electricity markets. In Proc. of the 10th IEEE Conf. on Dec. and Control, Atlanta, GA, 2010. I.-K. Cho and S. P. Meyn. Efficiency and marginal cost pricing in dynamic competitive markets with friction. Theoretical Economics, 5(2):215–239, 2010.

M. Chen, I.-K. Cho, and S. Meyn. Reliability by design in a distributed power transmission
network. Automatica, 42:1267–1281, August 2006.

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