Lecture at Cambridge Energy Systems Week 2013 Abstract and video here, http://www.newton.ac.uk/programmes/SCS/seminars/2013042409301.html The talk is similar to the Montreal tutorial. Important additions: 1) Please take the quiz at the start of the lecture - answers at the end, 2) MISO is seeing success with their alternatives to real time prices for incentivizing responsive generation. Much more information may be found at my homepage and the c^3 website, http://ccc.centers.ufl.edu/

1. Control of the grid in 2020
and how economics can help us
Energy Systems Week
Isaac Newton Institute Cambridge, U.K.
April 2013
Sean P. Meyn
Prabir Barooah, Ana Buˇsi´c, In-Koo Cho, Anupama Kowli
Matias Negrete-Pincetic, Ehsan Shafieeporfaard, Uday Shanbhag, and Gui Wang
Electrical and Computer Engineering
University of Florida
Thanks to NSF, AFOSR, and DOE / TCIPG

2. Control of the grid in 2020
and how economics can help us
Electrical and Computer Engineering
University of Florida
Energy Systems Week
Isaac Newton Institute Cambridge, U.K.

3. Control of the grid in 2020
and how economics can help us
Electrical and Computer Engineering
University of Florida
Energy Systems Week
Isaac Newton Institute Cambridge, U.K.
45 minute drive from home in Gainesville

4. Control of the grid in 2020
and how economics can help us
Electrical and Computer Engineering
University of Florida
Energy Systems Week
Isaac Newton Institute Cambridge, U.K.
Co-author Prashant Mehta - first encounter with young Manatee

5. What is the Value of Power?
A short quiz
5 / 66

6. What is the Value of Power?
A short quiz
the value of power depends
upon location and context
$69.36
$70.86
$75.19
$69.29
$29.36
5 / 66

7. What is the Value of Power?
A short quiz
Wind generation
for one day in the
Pacific Northwest
Price is $20/MWh
0
2000
4000
6000
8000
April 6
MW
1600 MW average output
6 / 66

8. What is the Value of Power?
A short quiz
Wind generation
for one day in the
Pacific Northwest
Price is $20/MWh
0
2000
4000
6000
8000
April 6
MW
1600 MW average output
Value = 1600 MW x 24 hours x $20/MWh = $768,000 ?
7 / 66

9. What is the Value of Power?
A short quiz
Zero net power
Price is $20/MWh
−800
−600
-1000
−400
−200
0
200
400
600
800
April 3 April 4 April 5 April 6 April 7 April 8 April 9
MW
8 / 66

10. What is the Value of Power?
A short quiz
Zero net power
Price is $20/MWh
−800
−600
-1000
−400
−200
0
200
400
600
800
April 3 April 4 April 5 April 6 April 7 April 8 April 9
MW
Value = 0 MW x 7 days x $20/MWh = $0 ?
9 / 66

11. What is the Value of Power?
A short quiz
Zero net power
Price is $20/MWh
Answers to be submitted at the end of lecture
−800
−600
-1000
−400
−200
0
200
400
600
800
April 3 April 4 April 5 April 6 April 7 April 8 April 9
MW
10 / 66

12. Markets for Differentiated Electric Power Products
Conclusions in advance
Traditional fossil fuels will be history to our great grandchildren
11 / 66

13. Markets for Differentiated Electric Power Products
Conclusions in advance
We need renewable energy, but how do we create a new energy
infrastructure to support this?
11 / 66

14. Markets for Differentiated Electric Power Products
Conclusions in advance
We need renewable energy, but how do we create a new energy
infrastructure to support this?
Some required elements:
11 / 66

15. Markets for Differentiated Electric Power Products
Conclusions in advance
We need renewable energy, but how do we create a new energy
infrastructure to support this?
Some required elements:
Electricity must treated as a service and not a commodity: Gas
turbine generation provides regulatory service. So could HVAC
Smart Grid programs have helped to create a framework for greater
service differentiation
Real time control will be an essential element to combat volatility and
ensure reliability
11 / 66

16. Markets for Differentiated Electric Power Products
Conclusions in advance
Traditional fossil fuels will be history to our great grandchildren
We need renewable energy, but how do we create a new energy
infrastructure to support this?
Some required elements:
Electricity must treated as a service and not a commodity: Gas
turbine generation provides regulatory service. So could HVAC
Smart Grid programs have helped to create a framework for greater
service differentiation
Real time control will be an essential element to combat volatility and
ensure reliability
Real time prices have little or no value here:
This is supported by theory and history.
11 / 66

17. Outline
1 Controlling the Grid
2 Smart Grid in 2012
3 Some Science
4 Conclusions & Suggestions
5 References
12 / 66

18. Controlling the Grid
India
Complex and highly interconnected control system
B
D
A
C
Kanpur, Uttar Pradesh
IIT Mumbai, Maharashtra
Kharagpur,West Bengal
New Delhi, Delhi
Delhi-Kolkata Hwy and AH 4,535 km, 66 hours
A
B
C
D
13 / 66

19. Controlling the Grid
Power Grid India
Complex and highly interconnected control system
www.ee.iitb.ac.in/~anil/
50 55 60 65 70 75 80 85 90
50.3
50.4
50.5
50.6
50.7
Frequency
secs
Kanpur, Uttar Pradesh
IIT Mumbai, Maharashtra
Kharagpur,West Bengal
New Delhi, Delhi
Delhi-Kolkata Hwy and AH 4,535 km, 66 hours
A
B
C
D
Relay problem near the Taj Mahalen.wikipedia.org/wiki/2012_India_blackouts
A disturbance in Agra appears to spread instantly to Mumbai and Calcutta.
14 / 66

20. Controlling the Grid
Power Grid India
Complex and highly interconnected control system
www.ee.iitb.ac.in/~anil/ July 30, 2012 Blackouten.wikipedia.org/wiki/2012_India_blackouts
8 º
12 º
16 º
20 º
23.5 º
24 º
28 º
32 º
36 º
68 º 72 º 76 º 80 º 84 º 88 º 92 º 96 º
Chennai
Hyderabad
Bhubaneshwar
Kolkata
Raipur
Dehradun
Shimla
Srinagar
Aizwal
Imphal
Kohima
Guwahati
Shillong
Agartala
ItanagarGangtok
Patna
Ranchi
Mumbai
Bhopal
Jaipur
Lucknow
Panaji
Bangalore
Thiruvananthapuram
Gandhinagar
New Delhi
Chandigarh
Silvasaa
Pondicherry (Puducherry) Port Blair
Diu
Kavarati
Tamil
Nadu
Karnataka
Lakshadweep
Islands
Andaman
&
Nicobar
Islands
Goa
Gujarat
Haryana Uttaranchal
Nagaland
Manipur
Tripura
Sikkim
Meghalaya
Assam
Mizoram
Arunachal
Pradesh
Punjab
Rajasthan
Chhattisgarh
Orissa
Bihar
Jharkhand
Dadra & Nagar Haveli
Pondicherry (Karaikal)
Pondicherry (Yanam)
Pondicherry (Mahe)
Daman & Diu
West
Bengal
Himachal
Pradesh
Madhya Pradesh
Uttar Pradesh
Jammu & Kashmir
Maharashtra
Andhra
Pradesh
Kerala
Mi 100 200 300
Km 100 200 300 400
States and Union Territories
Map of India
National Capital
State Capital
Union Territory Capital
Mumbai
Kanpur
Frequency
0 2 4 6 8 10 12 14 16 18 20
49.2
49.6
49.4
49.8
50
50.2
15 / 66

21. Controlling the Grid
Power Grid India
Complex and highly interconnected control system
www.ee.iitb.ac.in/~anil/ July 30, 2012 Blackouten.wikipedia.org/wiki/2012_India_blackouts
8 º
12 º
16 º
20 º
23.5 º
24 º
28 º
32 º
36 º
68 º 72 º 76 º 80 º 84 º 88 º 92 º 96 º
Chennai
Hyderabad
Bhubaneshwar
Kolkata
Raipur
Dehradun
Shimla
Srinagar
Aizwal
Imphal
Kohima
Guwahati
Shillong
Agartala
ItanagarGangtok
Patna
Ranchi
Mumbai
Bhopal
Jaipur
Lucknow
Panaji
Bangalore
Thiruvananthapuram
Gandhinagar
New Delhi
Chandigarh
Silvasaa
Pondicherry (Puducherry) Port Blair
Diu
Kavarati
Tamil
Nadu
Karnataka
Lakshadweep
Islands
Andaman
&
Nicobar
Islands
Goa
Gujarat
Haryana Uttaranchal
Nagaland
Manipur
Tripura
Sikkim
Meghalaya
Assam
Mizoram
Arunachal
Pradesh
Punjab
Rajasthan
Chhattisgarh
Orissa
Bihar
Jharkhand
Dadra & Nagar Haveli
Pondicherry (Karaikal)
Pondicherry (Yanam)
Pondicherry (Mahe)
Daman & Diu
West
Bengal
Himachal
Pradesh
Madhya Pradesh
Uttar Pradesh
Jammu & Kashmir
Maharashtra
Andhra
Pradesh
Kerala
Mi 100 200 300
Km 100 200 300 400
States and Union Territories
Map of India
National Capital
State Capital
Union Territory Capital
Mumbai
Kanpur
Frequency
0 2 4 6 8 10 12 14 16 18 20
49.2
49.6
49.4
49.8
50
50.2
In this talk I focus on engineering, and on U.S. energy policy
15 / 66

22. Controlling the Grid
Electric Power Grids
Phase angles depend on
transmission,
grid dynamics,
and
shocks to the grid
Angle Contour Map
FNET Web Display
Electric power grids are large, complex systems governed by physical
laws and constraints, and, impacted by many sources of dynamics and
uncertainty
Reliability, efficiency and environment are the key drivers in power
system operations and planning
16 / 66

23. Controlling the Grid
Electric Power Grids
Phase angles depend on
transmission,
grid dynamics,
and
shocks to the grid
Angle Contour Map
FNET Web Display
Latest shock to hit U.S.?
16 / 66

24. Controlling the Grid
Electric Power Grids
Phase angles depend on
transmission,
grid dynamics,
and
shocks to the grid
Angle Contour Map
FNET Web Display
Latest shock to hit U.S.? Government mandates for renewables!
16 / 66

25. Controlling the Grid
Growth of Renewables
Renewable Energy Consumption in the U.S.
Quads
16
13
14
10
8
4
6
3
0
1950 1960 1970 1980 1990 2000 2010 2020 2030
*One quadrillion (1,000,000,000,000,000) British thermal units (Btus).
17 / 66

26. Controlling the Grid
Growth of Renewables
Along with highly nonrenewable energy in the U.S.
Renewable Energy Consumption in the U.S.
Quads
16
13
14
10
8
4
6
3
0
1950 1960 1970 1980 1990 2000 2010 2020 2030
Annual natural gas well starts and production in Pennsylvania
wells started
2005
3,500
2,500
3,000
1,500
500
0
1,000
2,000
2006 2007 2008 2009 2010 2011 2012
7.0
5.0
6.0
4.0
3.0
1.0
2.0
0.0
billion cubic feet per day
horizontal wells non-horizontal wells gas production
*One quadrillion (1,000,000,000,000,000) British thermal units (Btus).
17 / 66

27. Controlling the Grid
Controlling the Grid
The Grid as a Control System
Dynamics are everywhere
Supply and demand are volatile
18 / 66

28. Controlling the Grid
Controlling the Grid
The Grid as a Control System
Dynamics are everywhere
Supply and demand are volatile
Transmission lines are subject to dynamics and constraints
18 / 66

29. Controlling the Grid
Controlling the Grid
The Grid as a Control System
Dynamics are everywhere
Supply and demand are volatile
Transmission lines are subject to dynamics and constraints
Traditional generators have non convex and dynamic costs
18 / 66

30. Controlling the Grid
Controlling the Grid
The Grid as a Control System
Dynamics are everywhere
Supply and demand are volatile
Transmission lines are subject to dynamics and constraints
Traditional generators have non convex and dynamic costs
Desires of Consumers & Suppliers, Error
Energy & Volatility
Power Consumption
Quality of Life
Power GridControl
HC
Σ
+
−
18 / 66

31. Controlling the Grid
Controlling the Grid
So many resources to control!
Dynamics are everywhere
Supply and demand are volatile
Transmission lines are subject to dynamics and constraints
Traditional generators have non convex and dynamic costs
Desires of Consumers & Suppliers, Error
Energy & Volatility
Power Consumption
Quality of Life
Power GridControl
HC
Σ
+
−
Actuators
1
0
2
3
4
Regulation(MW)
5minutesfromPJM
TwoWeeksBPA(GW)
−1000
0
1000
Hydro,NaturalGas
Flexiblemanufacturing
HVAC
Batteries
Capacitors
Flywheels
Actuators
Hydro,NaturalGas Batteries
Capacitors Flywheels
Flexiblemanufacturing Brickbaking
HVAC Waterpumping
19 / 66

32. Controlling the Grid
Controlling the Grid
So many resources to control!
Dynamics are everywhere
Supply and demand are volatile
Transmission lines are subject to dynamics and constraints
Traditional generators have non convex and dynamic costs
Desires of Consumers & Suppliers, Error
Energy & Volatility
Power Consumption
Quality of Life
Power GridControl
HC
Σ
+
−
Actuators
1
0
2
3
4
Regulation(MW)
5minutesfromPJM
TwoWeeksBPA(GW)
−1000
0
1000
Hydro,NaturalGas
Flexiblemanufacturing
HVAC
Batteries
Capacitors
Flywheels
Actuators
Hydro,NaturalGas Batteries
Capacitors Flywheels
Flexiblemanufacturing Brickbaking
HVAC Waterpumping
How do we harness these actuators?
19 / 66

33. Controlling the Grid
Controlling the Grid
Smart Grid Myopia?
Dynamics are everywhere
Supply and demand are volatile
Transmission lines are subject to dynamics and constraints
Traditional generators have non convex and dynamic costs
Desires of Consumers & Suppliers, Error
Energy & Volatility
Power Consumption
Quality of Life
Power GridControl
HC
Σ
+
−
Actuators
1
0
2
3
4
Regulation(MW)
5minutesfromPJM
TwoWeeksBPA(GW)
−1000
0
1000
Hydro,NaturalGas
Flexiblemanufacturing
HVAC
Batteries
Capacitors
Flywheels
$$$
Actuators
Hydro,NaturalGas Batteries
Capacitors Flywheels
Flexiblemanufacturing Brickbaking
HVAC Waterpumping
Money and consumer response in the loop ???
20 / 66

34. Controlling the Grid
Controlling the Grid
Smart Grid Myopia?
Dynamics are everywhere
Supply and demand are volatile
Transmission lines are subject to dynamics and constraints
Traditional generators have non convex and dynamic costs
Desires of Consumers & Suppliers, Error
Energy & Volatility
Power Consumption
Quality of Life
Power GridControl
HC
Σ
+
−
Actuators
1
0
2
3
4
Regulation(MW)
5minutesfromPJM
TwoWeeksBPA(GW)
−1000
0
1000
Hydro,NaturalGas
Flexiblemanufacturing
HVAC
Batteries
Capacitors
Flywheels
$$$
Actuators
Hydro,NaturalGas Batteries
Capacitors Flywheels
Flexiblemanufacturing Brickbaking
HVAC Waterpumping
Money and consumer response in the loop ??? No way!
20 / 66

35. Controlling the Grid
Controlling the Grid
Smart Grid Vision
Dynamics are everywhere
Supply and demand are volatile
Transmission lines are subject to dynamics and constraints
Traditional generators have non convex and dynamic costs
Desires of Consumers & Suppliers, Error
Energy & Volatility
Power Consumption
Quality of Life
Power GridControl
HC
Σ
+
−
1
0
2
3
4
Regulation(MW)
5minutesfromPJM
TwoWeeksBPA(GW)
−1000
0
1000
Actuators
Hydro,NaturalGas Batteries
Capacitors Flywheels
Flexiblemanufacturing Brickbaking
HVAC Waterpumping
Our community can solve this, thank you!!
21 / 66

36. Smart Grid in 2012
0 4am 9am 2pm 7pm
$0
$10,000
$20,000
Stratford
Otahuhu
Nodal Power Prices
per MWh
Smart Grid 2012
22 / 66

37. Smart Grid in 2012
EIA 2011 Study
Smart grid legislative and regulatory policies and case studies
Many success stories:
Millions of smarter meters installed all over the globe
PNNL study: Automation of water heaters and other appliances
provided ancillary service in the Olympic peninsula
Large buildings such as hotels, and energy-intensive companies such
as IBM, Google, and ALCOA have contracts in place to help stabilize
the grid, encouraged by FERC Ruling 745∗
∗
Market-Based Demand Response Compensation Rule:
Electric utilities and retail market operators are now
required to pay demand response resources the market
price (LMP) for energy
23 / 66

38. Smart Grid in 2012
EIA 2011 Study
Smart grid legislative and regulatory policies and case studies
Many success stories:
Millions of smarter meters installed all over the globe
PNNL study: Automation of water heaters and other appliances
provided ancillary service in the Olympic peninsula
Large buildings such as hotels, and energy-intensive companies such
as IBM, Google, and ALCOA have contracts in place to help stabilize
the grid, encouraged by FERC Ruling 745∗
∗
Market-Based Demand Response Compensation Rule:
Electric utilities and retail market operators are now
required to pay demand response resources the market
price (LMP) for energy
What is FERC’s score on the quiz?
23 / 66

39. Smart Grid in 2012
Increasing Leverage of Flexibility
Constellation Energy & NJP&L: Awards gift cards and rate reductions to residents
for control of air conditioners; company sells flexibility as ancillary service.
www.eia.gov/analysis/studies/electricity/pdf/smartggrid.pdf, December 12, 2011
Energy department to launch new energy innovation hub
focused on advanced batteries and energy storage.
www.energy.gov, February 7, 2012
Honeywell And Hawaiian Electric To Use Demand Response
To Integrate Renewables And Reduce Fossil Fuel Dependence.
www.honeywell.com, February 2, 2012
Axion Power’s PowerCube Battery Energy Storage
System Integrated Into PJM Utility Grid.
www.axionpower.com, November 22, 2011
First ’small-scale’ demand-side projects in PJM
providing frequency regulation.
www.sacbee.com, November 21, 2011
24 / 66

40. Smart Grid in 2012
Building Thermal Dynamics
For control of the grid
Feedforward control architecture; an add-on to the existing control system
25 / 66

41. Smart Grid in 2012
Building Thermal Dynamics
For control of the grid
Feedforward control architecture; an add-on to the existing control system
GridRegulationSignal
Desires of Consumers & Suppliers, Error
Error
Happy
Consumers
Energy & Volatility
Feedforward power deviation
Power GridGrid Control
HC
+
−
Σ Σ
Actuator
HVAC
−1000
0
1000
PI
Building
Control
25 / 66

42. Smart Grid in 2012
Building Thermal Dynamics
Feedforward control architecture; an add-on to the existing control system
How to we prevent a fight between our control system and theirs?
26 / 66

43. Smart Grid in 2012
Building Thermal Dynamics
Feedforward control architecture; an add-on to the existing control system
How to we prevent a fight between our control system and theirs?
Feedforward control viewed as a disturbance by the existing HVAC PI controller?
26 / 66

44. Smart Grid in 2012
Building Thermal Dynamics
Feedforward control architecture; an add-on to the existing control system
How to we prevent a fight between our control system and theirs?
Feedforward control viewed as a disturbance by the existing HVAC PI controller?
Solution: Restrict to a BW that is unseen by PI control-freaks
26 / 66

45. Smart Grid in 2012
Building Thermal Dynamics
Feedforward control architecture; an add-on to the existing control system
How to we prevent a fight between our control system and theirs?
Feedforward control viewed as a disturbance by the existing HVAC PI controller?
Solution: Restrict to a BW that is unseen by PI control-freaks
Power to Fan Speed
Power to Temperature
Magnitude(dB)
Frequency (Hz) 10010−3 1
600
1
4
0
−20
20
−40
−60
Bandwidth for Ancillary Service
from Commercial Buildings
Within this frequency band,
Current HVAC control systems do not attempt to reject disturbances
Temperature is insensitive to fan-speed variations
26 / 66

46. Smart Grid in 2012
One Million Pools in Florida
For ancillary service on a slower time-scale
−600
−400
−200
0
200
400
600
Day 1 Day 2 Day 3 Day 4 Day 5 Day 6 Day 7
MW
27 / 66

47. Smart Grid in 2012
EIA 2011 Study
Smart grid legislative and regulatory policies and case studies
Many success stories ... and failures
Residential consumers have high expectations,
Predictable cost savings
They may distrust those tampering with their appliances.
They distrust meters they believe interfere with appliances.
28 / 66

48. Smart Grid in 2012
EIA 2011 Study
Smart grid legislative and regulatory policies and case studies
Many success stories ... and failures
Residential consumers have high expectations,
Predictable cost savings
They may distrust those tampering with their appliances.
They distrust meters they believe interfere with appliances.
Moreover, the value of ancillary service obtained via demand response may
be reduced because of uncertainty of the level of consumer response.
28 / 66

49. Smart Grid in 2012
EIA 2011 Study
Smart grid legislative and regulatory policies and case studies
Many success stories ... and failures
Residential consumers have high expectations,
Predictable cost savings
They may distrust those tampering with their appliances.
They distrust meters they believe interfere with appliances.
Moreover, the value of ancillary service obtained via demand response may
be reduced because of uncertainty of the level of consumer response.
... yet, prices to devices are coming our way!∗
∗
Terry Boston, CEO PJM, ISGT 2012
28 / 66

50. Smart Grid in 2012
EIA 2011 Study
Smart grid legislative and regulatory policies and case studies
Moreover, the value of ancillary service obtained via demand response may
be reduced because of uncertainty of the level of consumer response.
... yet, prices to devices are coming our way!∗
∗
Terry Boston, CEO PJM, ISGT 2012
My concern: real-time pricing not TOU or contracts
28 / 66

51. Smart Grid in 2012
EIA 2011 Study
Case studies ... very little to say on real-time prices
"The active participation of final demand in the wholesale market is essential to managing
the greater intermittency of renewable resources and in limiting the ability of wholesale
electricity suppliers to exercise unilateral market power. A demand that is able to reduce its
consumption in real-time in response to higher prices limits the ability of suppliers
to exercise unilateral market power in a formal wholesale market such as the California ISO"
(http://www.stanford.edu/group/fwolak/cgi-
bin/sites/default/files/files/little_hoover_testimony_wolak_sept_2011.pdf) -F. Wolak
"Virtually all economists agree that the outcome [of the California crisis] was exacerbated by the inability of the demand side of the
market to respond to real or artificial supply shortages. This realization prompted my research stream on real-time electricity
pricing." - S. Borenstein
My concern: real-time pricing not TOU or contracts
29 / 66

52. Smart Grid in 2012
Midwest ISO Today
Wednesday morning, April 10, 2013
Real-time prices early morning in the Midwest, as I prepare this lecture:
10 April 2013 06:15 10 April 2013 06:20 10 April 2013 07:30
10 April 2013 07:35 10 April 2013 07:50 10 April 2013 08:35
30 / 66

53. Smart Grid in 2012
Midwest ISO Today
Wednesday mid-morning, April 10, 2013
Real-time prices mid-morning in the Midwest as I prepare this lecture:
10 April 2013 10:15 10 April 2013 10:30 10 April 2013 10:35
10 April 2013 11:30 10 April 2013 11:35 10 April 2013 12:05
31 / 66

54. Smart Grid in 2012
Midwest ISO Today
Wednesday morning, April 11, 2013
Real-time prices early this morning as I depart for work:
11 April 2013 07:25 11 April 2013 07:30 11 April 2013 07:35
10 April 2013 09:15 10 April 2013 09:20 10 April 2013 09:25
32 / 66

55. Smart Grid in 2012
Midwest ISO Today
Last week
33 / 66

56. Smart Grid in 2012
Midwest ISO Today
Last week
Prices depend on time, location and context
33 / 66

57. Smart Grid in 2012
Cold Causes Price Spikes
Texas today: Winter of 2011
5am 10am 3pm 8pm
−500
0
1000
2000
3000
$/MWh
February 2, 2011$/MWh
−10
0
10
20
40
60
80
5am 10am 3pm 8pm
Power Prices inTexas
January 31, 2011
34 / 66

58. Smart Grid in 2012
Cold Causes Price Spikes
Texas today: Winter of 2011
5am 10am 3pm 8pm
−500
0
1000
2000
3000
$/MWh
February 2, 2011$/MWh
−10
0
10
20
40
60
80
5am 10am 3pm 8pm
Power Prices inTexas
January 31, 2011
There will be multiple autopsies of the causes for the latest power breakdowns ... Who
profited off 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
34 / 66

59. Smart Grid in 2012
Cold Causes Price Spikes
Texas today: Winter of 2011
5am 10am 3pm 8pm
−500
0
1000
2000
3000
$/MWh
February 2, 2011$/MWh
−10
0
10
20
40
60
80
5am 10am 3pm 8pm
Power Prices inTexas
January 31, 2011
Proposed Remedy Public Utility Commission of Texas (PUCT)
... considering raising offer caps to as high as $9,000/MWh,
among other measures. [Brattle Group, June 1 2012]
34 / 66

60. Smart Grid in 2012
Cold Causes Price Spikes
Texas today: Winter of 2011
5am 10am 3pm 8pm
−500
0
1000
2000
3000
$/MWh
February 2, 2011$/MWh
−10
0
10
20
40
60
80
5am 10am 3pm 8pm
Power Prices inTexas
January 31, 2011
Proposed Remedy Public Utility Commission of Texas (PUCT)
... considering raising offer caps to as high as $9,000/MWh,
among other measures. [Brattle Group, June 1 2012]
Efficient Outcome! October 25, 2012: The Public Utility Commission of Texas has
approved a series of increases in the ERCOT high system-wide offer cap (HCAP)
starting June 1, 2013, with the cap eventually reaching $9,000/MWh.
34 / 66

61. Smart Grid in 2012
Day-Ahead Market Outcomes
Texas today: Summer of 2011
Source: U.S. Energy Information Administration, based on the Electric Reliability Council of Texas (ERCOT).
Note: ERCOT North Zone includes Dallas/Fort Worth metro region and surrounding areas of Northeast Texas. On-Peak
refers to the 16-hour time block from hours ending 7:00 a.m. to 10:00 p.m. CDT on weekdays, excluding NERC holidays
ERCOT North Zone - August 1-30, 2011
Hourly day-ahead, daily on-peak, and monthly weighted average prices
3,000
2,000
2,500
1,500
1,000
0
500
wholesaleprice($/MWh)
1 32 4 5 76 8 9 1110 12 13 1514 16 1817 19 20 2221 23 2524 26 27 2928 30 31
hourly, day-ahead price
daily, on-peak price
weighted average monthly
price ($188/MWh)
Source: U.S. Energy Information Administration, based on the Electric Reliability Council ofTexas (ERCOT).
Note: ERCOT North Zone includes Dallas/FortWorth metro region and surrounding areas of NortheastTexas. On-Peak refers
to the 16-hour time block from hours ending 7:00 a.m. to 10:00 p.m. CDT on weekdays, excluding NERC holidays.
35 / 66

62. Smart Grid in 2012
Madness in New Zealand
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/
0
50
100
Nodal Power Prices in NZ: $/MWh
4am 9am 2pm 7pm
36 / 66

63. Smart Grid in 2012
Madness in New Zealand
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
0
10,000
20,000
Nodal Power Prices in NZ: $/MWh
37 / 66

64. Smart Grid in 2012
Madness in New Zealand
New Zealand today: March 26, 2011
>$20 million dollars demanded back from Genesis
Stratford
Otahuhu
http://www.electricityinfo.co.nz/4am 9am 2pm 7pm
0
10,000
20,000
Nodal Power Prices in NZ: $/MWh
Preliminary view of NZ Electrical Authority: Genesis was not guilty of
“manipulative” ... or “deceptive” conduct. However, high prices threatened to
37 / 66

65. Smart Grid in 2012
Madness in New Zealand
New Zealand today: March 26, 2011
>$20 million dollars demanded back from Genesis
Stratford
Otahuhu
http://www.electricityinfo.co.nz/4am 9am 2pm 7pm
0
10,000
20,000
Nodal Power Prices in NZ: $/MWh
Preliminary view of NZ Electrical Authority: Genesis was not guilty of
“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
37 / 66

66. Smart Grid in 2012
PNNL Prices to Devices Projects
Automation in the market Transactive Controls: Market-Based GridWiseTM
Controls for Building Systems
P–kσP+kσ
Tset = 72o
FTmin = 67o
F Tmax = 77o
F
PMeanPrice
Current Zone
Temperature
Bid Price
Clearing Price
Adjusted Zone
Set Point Temperature
Desired or
Idea Set Point
Maximum
Set Point
Minimum
Set Point
Bid Curve
Tcurrent = 75o
FTset,a = 70o
F
P–kσP–kσP+kσP+kσ
Tset = 72o
FTmin = 67o
F Tmax = 77o
F
PMeanPrice
Current Zone
Temperature
Bid Price
Clearing Price
Adjusted Zone
Set Point Temperature
Desired or
Idea Set Point
Maximum
Set Point
Minimum
Set Point
Bid Curve
Tcurrent = 75o
FTset,a = 70o
F
Tset = 72o
FTmin = 67o
F Tmax = 77o
F
PMeanPrice
Current Zone
Temperature
Clearing Price
Adjusted Zone
Set Point Temperature
Desired or
Idea Set Point
Maximum
Set Point
Minimum
Set Point
Bid Curve
Tcurrent = 75o
FTset,a = 70o
F
Tset = 72o
FTmin = 67o
F Tmax = 77o
F
PMeanPricePMeanPrice
Current Zone
Temperature
Clearing Price
Adjusted Zone
Set Point Temperature
Desired or
Idea Set Point
Maximum
Set Point
Minimum
Set Point
Bid Curve
Tcurrent = 75o
FTset,a = 70o
F Comfort
$$$
38 / 66

67. Smart Grid in 2012
PNNL Prices to Devices Projects
Automation in the market Transactive Controls: Market-Based GridWiseTM
Controls for Building Systems
P–kσP+kσ
Tset = 72o
FTmin = 67o
F Tmax = 77o
F
PMeanPrice
Current Zone
Temperature
Bid Price
Clearing Price
Adjusted Zone
Set Point Temperature
Desired or
Idea Set Point
Maximum
Set Point
Minimum
Set Point
Bid Curve
Tcurrent = 75o
FTset,a = 70o
F
P–kσP–kσP+kσP+kσ
Tset = 72o
FTmin = 67o
F Tmax = 77o
F
PMeanPrice
Current Zone
Temperature
Bid Price
Clearing Price
Adjusted Zone
Set Point Temperature
Desired or
Idea Set Point
Maximum
Set Point
Minimum
Set Point
Bid Curve
Tcurrent = 75o
FTset,a = 70o
F
Tset = 72o
FTmin = 67o
F Tmax = 77o
F
PMeanPrice
Current Zone
Temperature
Clearing Price
Adjusted Zone
Set Point Temperature
Desired or
Idea Set Point
Maximum
Set Point
Minimum
Set Point
Bid Curve
Tcurrent = 75o
FTset,a = 70o
F
Tset = 72o
FTmin = 67o
F Tmax = 77o
F
PMeanPricePMeanPrice
Current Zone
Temperature
Clearing Price
Adjusted Zone
Set Point Temperature
Desired or
Idea Set Point
Maximum
Set Point
Minimum
Set Point
Bid Curve
Tcurrent = 75o
FTset,a = 70o
F Comfort
$$$
Proportional control: Comfort = k × Price
38 / 66

68. Smart Grid in 2012
PNNL Prices to Devices Projects
Automation in the market Transactive Controls: Market-Based GridWiseTM
Controls for Building Systems
300
200
100
0 5 10 15 20 25
0
$/MWh
Hour
Mean Price
Zone Bid Price
Market Clearing Price
Proportional control: Comfort = k × Price
39 / 66

69. Smart Grid in 2012
PNNL Prices to Devices Projects
Automation in the market Transactive Controls: Market-Based GridWiseTM
Controls for Building Systems
Mean Price
Zone Bid Price
Market Clearing Price
300
200
100
0 5 10 15 20 25
0
ConsumerAnger
Hour
Proportional control: Comfort = k × Price
40 / 66

70. Some Science
Torque
Speed
LowCost
Economics with Engineering
41 / 66

71. Some Science
Torque
Speed
LowCost
Economics with Engineering
Concerning real-time pricing not TOU or contracts
41 / 66

72. Some Science
Equilibrium with Dynamics & Network Constraints
Entropic prices
Theorem 1: When dynamics (temporal constraints) are taken into
account, price is never equal to marginal cost [5, 4, 3, 1]
42 / 66

73. Some Science
Equilibrium with Dynamics & Network Constraints
Entropic prices
Theorem 1: When dynamics (temporal constraints) are taken into
account, price is never equal to marginal cost [5, 4, 3, 1]
Equilibrium price
The equilibrium price process is a function of equilibrium reserves:
P∗
(t) = p∗
(Re
(t))
The marginal value of power to the consumer.
42 / 66

74. Some Science
Equilibrium with Dynamics & Network Constraints
Entropic prices
Theorem 1: When dynamics (temporal constraints) are taken into
account, price is never equal to marginal cost [5, 4, 3, 1]
Equilibrium price
The equilibrium price process is a function of equilibrium reserves:
P∗
(t) = p∗
(Re
(t))
The marginal value of power to the consumer.
Proof: Lagrangian decomposition,
as in the static Second Welfare Theorem
42 / 66

75. Some Science
Equilibrium with Dynamics & Network Constraints
Entropic prices
What is marginal value?
It is not always obvious. With the introduction of network constraints,
43 / 66

76. Some Science
Equilibrium with Dynamics & 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 (as defined in static model)
Prices can go well below zero
[Dynamic competitive equilibria in electricity markets. Wang et. al. 2011]
43 / 66

77. Some Science
Equilibrium with Dynamics & 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 (as defined in static model)
Prices can go well below zero
[Dynamic competitive equilibria in electricity markets. 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
0
1,000
0
- 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
0
TasmaniaVictoria
43 / 66

78. Some Science
Sustainable business?
Marginal value of electricity,
$250,000/MWh (?)
Purchase Price $/MWh
Previous week
Spinning reserve prices PX prices $/MWh
100
150
0
50
200
250
10
20
30
40
50
60
70
Texas: February2,2011
California: July2000Illinois:July1998
Ontario: November,2005
0
1000
2000
3000
4000
5000
Mon Tues Weds Thurs Fri Mon Tues WedsWeds Thurs Fri Sat Sun
Tues Weds Thurs
Time3 6 9 12 15 18 213 6 9 12 15 18 213 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
0
ForecastPricesForecastDemand
5am 10am 3pm 8pm
−500
0
1000
2000
3000
$/MWh
Average price
is usually $30
$/MWh
44 / 66

79. Some Science
Sustainable business?
Marginal value of electricity,
$250,000/MWh (?)
Purchase Price $/MWh
Previous week
Spinning reserve prices PX prices $/MWh
100
150
0
50
200
250
10
20
30
40
50
60
70
Texas: February2,2011
California: July2000Illinois:July1998
Ontario: November,2005
0
1000
2000
3000
4000
5000
Mon Tues Weds Thurs Fri Mon Tues WedsWeds Thurs Fri Sat Sun
Tues Weds Thurs
Time3 6 9 12 15 18 213 6 9 12 15 18 213 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
0
ForecastPricesForecastDemand
5am 10am 3pm 8pm
−500
0
1000
2000
3000
$/MWh
Average price
is usually $30
$/MWh
However,
44 / 66

80. Some Science
Sustainable business?
Marginal value of electricity,
$250,000/MWh (?)
Purchase Price $/MWh
Previous week
Spinning reserve prices PX prices $/MWh
100
150
0
50
200
250
10
20
30
40
50
60
70
Texas: February2,2011
California: July2000Illinois:July1998
Ontario: November,2005
0
1000
2000
3000
4000
5000
Mon Tues Weds Thurs Fri Mon Tues WedsWeds Thurs Fri Sat Sun
Tues Weds Thurs
Time3 6 9 12 15 18 213 6 9 12 15 18 213 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
0
ForecastPricesForecastDemand
5am 10am 3pm 8pm
−500
0
1000
2000
3000
$/MWh
Average price
is usually $30
$/MWh
However,
Theorem 2: In this equilibrium, the average price is
precisely the average marginal cost
Proof: Lagrangian relaxation of initial condition.
44 / 66

81. Some Science
Sustainable business?
Marginal value of electricity,
$250,000/MWh (?)
Purchase Price $/MWh
Previous week
Spinning reserve prices PX prices $/MWh
100
150
0
50
200
250
10
20
30
40
50
60
70
Texas: February2,2011
California: July2000Illinois:July1998
Ontario: November,2005
0
1000
2000
3000
4000
5000
Mon Tues Weds Thurs Fri Mon Tues WedsWeds Thurs Fri Sat Sun
Tues Weds Thurs
Time3 6 9 12 15 18 213 6 9 12 15 18 213 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
0
ForecastPricesForecastDemand
5am 10am 3pm 8pm
−500
0
1000
2000
3000
$/MWh
Average price
is usually $30
$/MWh
However,
Theorem 2: In this equilibrium, the average price is
precisely the average marginal cost
Proof: Lagrangian relaxation of initial condition.
Is this a sustainable business?
44 / 66

82. Some Science
More Engineering: Where is the Missing Money?
FERC Order 755
New rules for fair treatment of resources participating in regulation markets
Time
Regulation Required @ MISO
0
200
400
600
-400
-200
Current method of regulation compensation does not fairly account
for the regulation service provided.
45 / 66

83. Some Science
More Engineering: Where is the Missing Money?
FERC Order 755
New rules for fair treatment of resources participating in regulation markets
Time
Regulation Required @ MISO
0
200
400
600
-400
-200
Current method of regulation compensation does not fairly account
for the regulation service provided.
Requires ISOs to pay resources based on actual service provided
45 / 66

84. Some Science
More Engineering: Where is the Missing Money?
FERC Order 755
New rules for fair treatment of resources participating in regulation markets
Time
Regulation Required @ MISO
0
200
400
600
-400
-200
Current method of regulation compensation does not fairly account
for the regulation service provided.
Requires ISOs to pay resources based on actual service provided
And, how much is that?
45 / 66

85. Some Science
The Future as seen by FERC Today
FERC Order 755
Time
Regulation Required @ MISO
0
200
400
600
-400
-200
Possible payment plan, consider 1 of storage regulation,
Payment ∝
T
0
d
dt
G(t)| dt
46 / 66

86. Some Science
The Future as seen by FERC Today
FERC Order 755
Time
Regulation Required @ MISO
0
200
400
600
-400
-200
Possible payment plan, consider 1 of storage regulation,
Payment ∝
T
0
d
dt
G(t)| dt
Hmmm....
46 / 66

87. Some Science
The Future as seen by FERC Today
FERC Order 755
Time
Regulation Required @ MISO
0
200
400
600
-400
-200
Possible payment plan, consider 1 of storage regulation,
Payment ∝
T
0
d
dt
G(t)| dt
Hmmm....
Let’s have a closer look ...
46 / 66

88. Some Science
The Future as seen by FERC Today
FERC Order 755
Time
Regulation Required @ MISO
0
200
400
600
-400
-200
Last month, the Midwest ISO found that their payments were providing an
incentive for responsive generation,
5,000
4,000
3,000
2,000
1,000
0
Fast Middle Slow
Jan & Feb 2012
Day-Ahead
Average Total Daily Regulation Volume in MW
5,000
4,000
3,000
2,000
1,000
0
Fast Middle Slow
Real-Time Jan & Feb 2013
Since addition of mileage product, regulation has shifted from
slower to faster ramping resources
Payment based on wear & tear
*
*
“ “
https://www.misoenergy.org/Library/Repository/Meeting%20Material/Stakeholder/BOD/Markets%20Committee/2013/20130327/20130327%20Markets%20Committee%20of%20the%20BOD%20Item%2005%20Frequency%20Regulation%20Compensation.pdf
March 27, 2013 document from Midwest ISO
d
dt
(tG ) dt
47 / 66

89. Some Science
More Engineering: Where is the Missing Money?
Addressing FERC Order 755
World-view, from eyes of a coal generator operator:
Control must respect dynamics & costs
48 / 66

90. Some Science
More Engineering: Where is the Missing Money?
Addressing FERC Order 755
World-view, from eyes of a coal generator operator:
Control must respect dynamics & costs
Cost of generation:
Includes G and d
dt G,
shut-down, O&M, investment, ...
48 / 66

91. Some Science
More Engineering: Where is the Missing Money?
Addressing FERC Order 755
World-view, from eyes of a coal generator operator:
Control must respect dynamics & costs
Cost of generation:
Includes G and d
dt G,
shut-down, O&M, investment, ...
What is “marginal cost”?
Torque
Speed
LowCost
48 / 66

92. Some Science
More Engineering: Where is the Missing Money?
Addressing FERC Order 755
World-view, from eyes of a coal generator operator:
Control must respect dynamics & costs
Cost of generation:
Includes G and d
dt G,
shut-down, O&M, investment, ...
What is “marginal cost”?
Torque
Speed
LowCost
Theorem 3: If c(G, d
dt G) = ce(G) + cw( d
dtG) then
48 / 66

93. Some Science
More Engineering: Where is the Missing Money?
Addressing FERC Order 755
World-view, from eyes of a coal generator operator:
Control must respect dynamics & costs
Cost of generation:
Includes G and d
dt G,
shut-down, O&M, investment, ...
What is “marginal cost”?
Torque
Speed
LowCost
Theorem 3: If c(G, d
dt G) = ce(G) + cw( d
dtG) then
E[P∗
] = E[ ce (G)]
48 / 66

94. Some Science
More Engineering: Where is the Missing Money?
Addressing FERC Order 755
World-view, from eyes of a coal generator operator:
Control must respect dynamics & costs
Cost of generation:
Includes G and d
dt G,
shut-down, O&M, investment, ...
What is “marginal cost”?
Torque
Speed
LowCost
Theorem 3: If c(G, d
dt G) = ce(G) + cw( d
dtG) then
E[P∗
] = E[ ce (G)]
Competitive equilibrium never compensates for “wear and tear”
48 / 66

95. Conclusions & Suggestions
Conclusions & Suggestions
49 / 66

96. Conclusions & Suggestions
What is the Value of Power?
Answers to Quiz #1
Wind generation
for one day in the
Pacific Northwest
Price is $20/MWh
0
2000
4000
6000
8000
April 6
MW
1600 MW average output
Value = 1600 MW x 24 hours x $20/MWh = $768,000 ?
50 / 66

97. Conclusions & Suggestions
What is the Value of Power?
Answers to Quiz #1 Wind generation
for one day in the
Pacific Northwest
Price is $20/MWh
0
2000
4000
6000
8000
April 6
MW
1600 MW average output
Value = 1600 MW x 24 hours x $20/MWh = $768,000 ?
Answer: Correct!
Electrons are electrons, so add them up, and put them on the market!
51 / 66

98. Conclusions & Suggestions
What is the Value of Power?
Answers to Quiz #1 Wind generation
for one day in the
Pacific Northwest
Price is $20/MWh
0
2000
4000
6000
8000
April 6
MW
1600 MW average output
Value = 1600 MW x 24 hours x $20/MWh = $768,000 ?
Answer: False!!
Spring 2012 report from this region:
Annual “expected value” of oversupply costs estimated at $12 million per
year, with 300,000 MWh of wind curtailment
www.nwcouncil.org/media/11074/2012 1212SupplementalReport.pdf
51 / 66

99. Conclusions & Suggestions
What is the Value of Power?
Answers to Quiz #1 Wind generation
for one day in the
Pacific Northwest
Price is $20/MWh
0
2000
4000
6000
8000
April 6
MW
1600 MW average output
Value = 1600 MW x 24 hours x $20/MWh = $768,000 ?
Answer: False!!
Spring 2012 report from this region:
Annual “expected value” of oversupply costs estimated at $12 million per
year, with 300,000 MWh of wind curtailment
The first answer would be correct if we had
infrastructure in place to mitigate volatility
www.nwcouncil.org/media/11074/2012 1212SupplementalReport.pdf
51 / 66

100. Conclusions & Suggestions
What is the Value of Power?
Answers to Quiz #2
Zero net power
Price is $20/MWh
−800
−600
-1000
−400
−200
0
200
400
600
800
April 3 April 4 April 5 April 6 April 7 April 8 April 9
MW
Value = 0 MW x 7 days x $20/MWh = $0 ?
52 / 66

101. Conclusions & Suggestions
What is the Value of Power?
Answers to Quiz #2 Zero net power
Price is $20/MWh
−800
−600
-1000
−400
−200
0
200
400
600
800
April 3 April 4 April 5 April 6 April 7 April 8 April 9
MW
Value = 0 MW x 7 days x $20/MWh = $0 ?
Answer: Correct!
The total power is zero, and the ± 800 MW perturbation is
inconsequential given the 8000 MW load
53 / 66

102. Conclusions & Suggestions
What is the Value of Power?
Answers to Quiz #2 Zero net power
Price is $20/MWh
−800
−600
-1000
−400
−200
0
200
400
600
800
April 3 April 4 April 5 April 6 April 7 April 8 April 9
MW
Value = 0 MW x 7 days x $20/MWh = $0 ?
Answer: False!
Disturbance to the grid is costly, the actual value is −$500,000 (guess)
53 / 66

103. Conclusions & Suggestions
What is the Value of Power?
Answers to Quiz #2 Zero net power
Price is $20/MWh
−800
−600
-1000
−400
−200
0
200
400
600
800
April 3 April 4 April 5 April 6 April 7 April 8 April 9
MW
Value = 0 MW x 7 days x $20/MWh = $0 ?
Answer: False!
Disturbance to the grid is costly, the actual value is −$500,000 (guess)
Answer: False!!
This is the BPA regulation signal! The actual value is ...
53 / 66

104. Conclusions & Suggestions
What is the Value of Power?
Answers to Quiz #2
April 3 April 4 April 5 April 6 April 7 April 8 April 9
54 / 66

105. Conclusions & Suggestions
What is the Value of Power?
Answers to Quiz #2
Answer: False!!
This is the BPA regulation signal! The actual value is ...
55 / 66

106. Conclusions & Suggestions
What is the Value of Power?
Answers to Quiz #2
Answer: False!!
This is the BPA regulation signal! The actual value is ...
0
2000
4000
6000
8000
April 3 April 4 April 5 April 6 April 7 April 8 April 9
MWMW
Load
Generation
from Wind
Balancing reserves deployed
Value no less than the
Seattle economy?−800
−600
-1000
−400
−200
0
200
400
600
800
April 3 April 4 April 5 April 6 April 7 April 8 April 9
Curtailment tresholds
55 / 66

107. Conclusions & Suggestions
What is the Value of Power?
Extra credit: What if one resource cannot provide all of the balancing needs?
Balancing
Reserves
Desired
What’s the
value of this:
−800
−600
-1000
−400
−200
0
200
400
600
800
−800
−600
-1000
−400
−200
200
400
600
800
April 3 April 4 April 5 April 6 April 7 April 8 April 9
MWMW
56 / 66

108. Conclusions & Suggestions
What is the Value of Power?
Extra credit: What if one resource cannot provide all of the balancing needs?
Balancing
Reserves
Desired
What’s the
value of this:
−800
−600
-1000
−400
−200
0
200
400
600
800
−800
−600
-1000
−400
−200
0
200
400
600
800
April 3 April 4 April 5 April 6 April 7 April 8 April 9
MWMW
57 / 66

109. Conclusions & Suggestions
What is the Value of Power?
Extra credit: What if the shape isn’t quite right?
Balancing
Reserves
Desired
What’s the
value of this:
−800
−600
-1000
−400
−200
0
200
400
600
800
−800
−600
-1000
−400
−200
200
400
600
800
April 3 April 4 April 5 April 6 April 7 April 8 April 9
MWMW
58 / 66

110. Conclusions & Suggestions
What is the Value of Power?
Extra credit: What if the shape isn’t quite right?
Balancing
Reserves
Desired
What’s the
value of this:
Delay is deadly
in a control system
Answer,
−800
−600
-1000
−400
−200
0
200
400
600
800
−800
−600
-1000
−400
−200
200
400
600
800
April 3 April 4 April 5 April 6 April 7 April 8 April 9
MWMW
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111. Conclusions & Suggestions
Smart Grid 2020
A playground for control theory
Baseline generation
Volatility from nature
Consumer demand (est.)
Power Consumption
Quality of Life
Power Grid
Increasing timescale of ancillary service, measured in Hz
Governors
Flywheels
Coal Generation
Flexible Manufacturing
Distributed Data Centers
Capacitor
Banks
Hydro Generation
GasTurbine Generation
Heating,Ventillation & Cooling
Batteries
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112. Conclusions & Suggestions
The current RTM paradigm must be reconsidered
Why have real time markets?
No value has been demonstrated for real-time markets.
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113. Conclusions & Suggestions
The current RTM paradigm must be reconsidered
Why have real time markets?
No value has been demonstrated for real-time markets.
Empirical evidence: We cannot distinguish robbery from efficiency.
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114. Conclusions & Suggestions
The current RTM paradigm must be reconsidered
Why have real time markets?
No value has been demonstrated for real-time markets.
Empirical evidence: We cannot distinguish robbery from efficiency.
IsThis A Free Market For Fire Fighters?
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115. Conclusions & Suggestions
The current RTM paradigm must be reconsidered
Why have real time markets?
No value has been demonstrated for real-time markets.
Empirical evidence: We cannot distinguish robbery from efficiency.
IsThis A Free Market For Fire Fighters?
Why then would you use real-time prices to control devices?
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116. Conclusions & Suggestions
The current RTM paradigm must be reconsidered
Why have real time markets?
No value has been demonstrated for real-time markets.
Empirical evidence: We cannot distinguish robbery from efficiency.
IsThis A Free Market For Fire Fighters?
Why then would you use real-time prices to control devices?
The EIA study shows that there are alternatives
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117. Conclusions & Suggestions
The current RTM paradigm must be reconsidered
Why have real time markets?
IsThis A Free Market For Fire Fighters?
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118. Conclusions & Suggestions
The current RTM paradigm must be reconsidered
Why have real time markets?
IsThis A Free Market For Fire Fighters?
“ ... One result of this divorce of the theory from its subject
matter has been that the entities whose decisions economists are
engaged in analyzing have not been made the subject of study
and in consequence lack any substance. ...consumers without
humanity, firms without organization, and even exchange without
markets”
R. Coase, 1988
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119. Conclusions & Suggestions
The current RTM paradigm must be reconsidered
Alternatives
TOU prices for peak shaving, and
Contracts for real-time demand-response services
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120. Conclusions & Suggestions
The current RTM paradigm must be reconsidered
Alternatives
TOU prices for peak shaving, and
Contracts for real-time demand-response services
Successful contracts today: Constellation Energy, Alcoa, residential pool
pumps, commercial buildings (see new work at Univ. of Florida), ...
Efficiency loss, but utility and consumers each have reliable services
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121. Conclusions & Suggestions
The current RTM paradigm must be reconsidered
Alternatives
New smart appliances that can facilitate these contracts
Control theory to make this all work:
We don’t know why the grid is so robust today. Introducing
all of these dynamics will lead to new control challenges.
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122. Conclusions & Suggestions
The current RTM paradigm must be reconsidered
Alternatives
New smart appliances that can facilitate these contracts
Control theory to make this all work:
We don’t know why the grid is so robust today. Introducing
all of these dynamics will lead to new control challenges.
Energy policy that is guided by an understanding of both physics and
economics
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123. Conclusions & Suggestions
The current RTM paradigm must be reconsidered
Alternatives
New smart appliances that can facilitate these contracts
Control theory to make this all work:
We don’t know why the grid is so robust today. Introducing
all of these dynamics will lead to new control challenges.
Energy policy that is guided by an understanding of both physics and
economics
Thank You!
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124. Conclusions & Suggestions
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)
Pn
(x, · ) − π f → 0
sup
C
Ex[SτC(f)]<∞
References
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125. References
References: Economics
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. Where is the Missing Money? The impact of generation
ramping costs in electricity markets. In preparation, 2012.
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.
U.S. Energy Information Administration. Smart grid legislative and regulatory policies and
case studies. December 12 2011.
http://www.eia.gov/analysis/studies/electricity/pdf/smartggrid.pdf
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126. References
References: Demand Response
H. Hao, A. Kowli, Y. Lin, P. Barooah, and S. Meyn Ancillary Service for the Grid Via
Control of Commercial Building HVAC Systems. ACC 2013.
S. Meyn, P. Barooah, A. Busic, and J. Ehren. Ancillary service to the grid from deferrable
loads: the case for intelligent pool pumps in Florida. Submitted to IEEE Conference on
Decision & Control (invited), 2013.
P. Xu, P. Haves, M. Piette, and J. Braun, Peak demand reduction from pre-cooling with
zone temperature reset in an office building, 2004.
D. Callaway and I. Hiskens, Achieving controllability of electric loads. Proceedings of the
IEEE, vol. 99, no. 1, pp. 184–199, 2011.
D. Watson, S. Kiliccote, N. Motegi, and M. Piette, Strategies for demand response in
commercial buildings. In Proceedings of the 2006 ACEEE Summer Study on Energy
Efficiency in Buildings, August 2006.
S. Kundu, N. Sinitsyn, S. Backhaus, and I. Hiskens, Modeling and control of
thermostatically controlled loads, Arxiv preprint arXiv:1101.2157, 2011. [Online]. Available:
http://arxiv.org/abs/1101.2157
S. Koch, J. Mathieu, and D. Callaway, Modeling and control of aggregated heterogeneous
thermostatically controlled loads for ancillary services, in Proc. PSCC, 2011, pp. 1–7.
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