Demand-Side Flexibility for Reliable Ancillary Services

Demand-Side Flexibility for Reliable
Ancillary Services in a Smart Grid:
Eliminating Risk to Consumers and the Grid
ANALYTIC RESEARCH FOUNDATIONS
FOR THE NEXT-GENERATION ELECTRIC GRID
Irvine, California, Feb. 11–12, 2015
Sean P. Meyn
Florida Institute for Sustainable Energy
Department of Electrical and Computer Engineering — University of Florida
Thanks to my colleagues, Prabir Barooah and Ana Buˇsi´c
and to our sponsors NSF, AFOSR, DOE / TCIPG

Eliminating Risk to Consumers and the Grid
Outline
1 Challenges of Renewable Energy Integration
2 FERC Pilots the Grid
3 Demand Dispatch
4 Buildings as Batteries
5 Intelligent Pools in Florida
6 Conclusions

Jan 01 Jan 02 Jan 03 Jan 04 Jan 05 Jan 06
GW
0
1
2
3
4
GW (t) = Wind generation in BPA, Jan 2015
Scary ramps
Challenges

Challenges of Renewable Energy Integration
Some of the Challenges
1 Large sunk cost (decreasing!)
1 / 25

2 Engineering uncertainty
1 / 25

3 Policy uncertainty
1 / 25

4 Volatility
Start at the bottom...
1 / 25

What’s so scary about volatility?
4 Volatility
GW
0
1
2
3
4
Scary ramps
2 / 25

4 Volatility =⇒ greater regulation needs
0
2
4
6
8
2
4
6
8
0
October 20-25 October 27 - November 1
Hydro
GenerationandLaodGW
GW
Thermal
Wind
Load
Generation
Disturbance from Nature
3 / 25

4 Volatility =⇒ greater regulation needs
0
2
4
6
8
2
4
6
8
0
0.8
-0.8
1
-1
0
0.8
-0.8
1
-1
0
Sun Mon Tue
October 20-25 October 27 - November 1
Hydro
Wed Thur FriSun Mon Tue Wed Thur Fri
GenerationandLaodGW
GWGW
RegulationGW
Thermal
Wind
Load
Generation
Regulation
Error Signal in Feedback Loop
3 / 25

Comparison: Flight control
How do we ﬂy a plane through a storm?
Brains
Brawn
4 / 25

How do we ﬂy a plane through a storm?
Brains
Brawn
What Good Are These?
4 / 25

How do we operate the grid in a storm?
Balancing Authority Ancillary Services Grid
Measurements:
Voltage
Frequency
Phase
Σ
−
Brains
Brawn
What Good Are These?
5 / 25

Disturbance decomposition
GW
0
1
2
3
4
Scary ramps
6 / 25

GW
0
1
2
3
4
G
Goal:
W (t) = Wind generation in BPA, Jan 2015
Scary ramps
GW (t) + Gr(t) ≡ 4GW
6 / 25

Sca
GW
0
1
2
3
4
G
Goal:
W (t) = Wind generation in BPA, Jan 2015
Scary
Scary
Scary
Scary
Scary
GW (t) + Gr(t) ≡ 4GW
6 / 25

GW
0
1
2
3
4
Goal: GW (t) + Gr(t) ≡ 4GW
obtained from
generation?
Gr(t)
Gr(t)
Scary
6 / 25

GW
0
1
2
3
4
Gr(t)
Gr = G1 + G2 + G3
G1
6 / 25

GW
0
1
2
3
4
Gr(t)
Gr = G1 + G2 + G3
G1
G2
6 / 25

GW
0
1
2
3
4
Gr(t)
Gr = G1 + G2 + G3
G1
G2
G3
6 / 25

GW
0
1
2
3
4
Gr(t)
Gr = G1 + G2 + G3
G1
G2
G3 Where do we find
these ailerons?
6 / 25

GW
0
1
2
3
4
Gr(t)
G1
G2
G
Traditional generation
FERC Order 745
FERC Order 7553
Gr = G1 + G2 + G3
FERC Pilots the Grid

FERC 745: Demand & Generation smooth the Grid
7 / 25

Origin of FERC 745 – Incentives for Demand Response
FERC 745 is Born!
134 FERC ¶61,187
UNITED STATES OF AMERICA
FEDERAL ENERGY REGULATORY COMMISSION
18 CFR Part 35
[Docket No. RM10-17-000; Order No. 745]
Demand Response Compensation in Organized Wholesale Energy Markets
(Issued March 15, 2011)
8 / 25

FERC 745 is Born!
134 FERC ¶61,187
18 CFR Part 35
The Commission concludes that paying LMP can address the identiﬁed
barriers to potential demand response providers.
8 / 25

FERC 745 is Born!
134 FERC ¶61,187
18 CFR Part 35
The Commission concludes that paying LMP can address the identiﬁed
barriers to potential demand response providers.
The outcome?
8 / 25

FERC 745 Is Dead!
9 / 25

FERC 745 Is Dead!
Conjecture: It had to die.
9 / 25

FERC 745 Is Dead!
FERC 745 Nirvana:
Peaks shaved!
9 / 25

FERC 745 Is Dead!
FERC 745 Nirvana:
Peaks shaved!
Contingencies resolved in seconds!!
Prices smoothed to Marginal Cost!
9 / 25

FERC 745 Is Dead!
FERC 745 Nirvana:
Peaks shaved!
Contour Map: Real Time Market - Locational Marginal Pricing Help?
$10/MWh
Nirvana @ ERCOT
9 / 25

FERC 745 Is Dead!
FERC 745 Nirvana:
Peaks shaved!
$10/MWh
Nirvana @ ERCOT
The problem: In this market, there is no opportunity without crisis
9 / 25

FERC 745 Is Dead!
FERC 745 Nirvana:
Peaks shaved!
$10/MWh
Nirvana @ ERCOT
The problem: In this market, there is no opportunity without crisis
The paradox: In this nirvana,
there is no business case for demand response
9 / 25

FERC Order 755
Pay-for-Performance
Time
Regulation Required @ MISO
0
200
400
600
-400
-200
10 / 25

FERC Order 755
Pay-for-Performance
Time
0
200
400
600
-400
-200
Requires ISO/RTOs to pay regulation resources
based on actual amount of regulation service provided
(speed and accuracy).
10 / 25

FERC Order 755
Pay-for-Performance
Time
0
200
400
600
-400
-200
Two part settlement:
1 Uniform price for frequency regulation capacity
2 Performance payment for the provision of frequency regulation
service, reﬂecting a resource’s accuracy of performance
11 / 25

FERC Order 755
Pay-for-Performance
Time
0
200
400
600
-400
-200
Performance?
11 / 25

FERC Order 755
Pay-for-Performance
Time
0
200
400
600
-400
-200
Performance? Now interpreted as mileage:
Payment ∝
T
0
d
dt
G(t)| dt (or discrete-time equivalent)
11 / 25

FERC Order 755
Pay-for-Performance
Time
0
200
400
600
-400
-200
Performance? Now interpreted as mileage:
Payment ∝
T
0
d
dt
G(t)| dt (or discrete-time equivalent)
Not perfect, but it is creating incentives
Question: What is the cost/value of regulation?
11 / 25

GW
0
1
2
3
4
Gr(t)
Gr = G1 + G2 + G3
G1
G2
G3 Where do we find
these ailerons?
Demand Dispatch

Demand Dispatch
We want: Responsive Regulation
Demand Dispatch the Answer?
A partial list of the needs of the grid operator, and the consumer:
12 / 25

Demand Dispatch
High quality AS? (Ancillary Service)
Does the deviation in power consumption accurately track the desired
deviation target?
12 / 25

Demand Dispatch
High quality AS? (Ancillary Service)
-15
-10
-5
0
5
10
15
20
25
30
35
6:00 7:00 8:00 9:00 6:00 7:00 8:00 9:00
Regulation(MW)
Gen 'A' Actual Regulation
Gen 'A' Requested Regulation
-20
-15
-10
-5
0
5
10
15
20
:
Regulation(MW)
Gen 'B' Actual Regulation
Gen 'B' Requested Regulation
Fig. 10. Coal-fired generators do not follow regulation signals precisely....
Some do better than others
Regulation service from generators is not perfect
Frequency Regulation Basics and Trends — Brendan J. Kirby, December 2004
12 / 25

Demand Dispatch
High quality AS?
Reliable?
Will AS be available each day?
It may vary with time, but capacity must be predictable.
12 / 25

Demand Dispatch
High quality AS?
Reliable?
Cost eﬀective?
This includes installation cost, communication cost, maintenance,
and environmental.
12 / 25

Demand Dispatch
High quality AS?
Reliable?
Cost eﬀective?
Is the incentive to the consumer reliable?
If a consumer receives a $50 payment for one month, and only $1 the
next, will there be an explanation that is clear to the consumer?
12 / 25

Demand Dispatch
High quality AS?
Reliable?
Cost effective?
Customer QoS constraints satisfied?
The pool must be clean, fresh fish stays cold, building climate is
subject to strict bounds, farm irrigation is subject to strict constraints,
data centers require sufficient power to perform their tasks.
12 / 25

Demand Dispatch
High quality AS?
Reliable?
Cost eﬀective?
Customer QoS constraints satisﬁed?
Perhaps demand dispatch can do all of this?
12 / 25

Demand Dispatch
Control Architecture
Frequency Decomposition for Demand Dispatch
Power GridControl Flywheels
Batteries
Coal
GasTurbine
BP
BP
BP C
BP
BP
Voltage
Frequency
Phase
HC
Σ
−
Actuator feedback loop
A
LOAD
Today: PJM decomposes regulation signal based on bandwidth,
R = RegA + · · · + RegD
13 / 25

Demand Dispatch
Power GridControl Flywheels
Batteries
Coal
GasTurbine
BP
BP
BP C
BP
BP
Voltage
Frequency
Phase
HC
Σ
−
A
LOAD
Today: PJM decomposes regulation signal based on bandwidth,
R = RegA + · · · + RegD
Proposal: Each class of DR (and other) resources will have its own
bandwidth of service, based on QoS constraints and costs.
13 / 25

Demand Dispatch
GW
0
1
2
3
4
Gr(t)
G1
G2
G
Traditional generation
DD: Chillers & Pool Pumps
DD: HVAC Fans3
Gr = G1 + G2 + G3
14 / 25

Demand Dispatch
Balancing Reserves from Bonneville Power Authority:
−800
−600
-1000
−400
−200
0
200
400
600
800
BPA Reg signal
(one week)
MW
15 / 25

Demand Dispatch
−800
−600
-1000
−400
−200
0
200
400
600
800
BPA Reg signal
(one week)
MW
0
−800
−600
-1000
−400
−200
200
400
600
800
MW
−800
−600
-1000
−400
−200
0
200
400
600
800
= +
15 / 25

Demand Dispatch
−800
−600
-1000
−400
−200
0
200
400
600
800
BPA Reg signal
(one week)
MW
0
−800
−600
-1000
−400
−200
200
400
600
800
MW
−800
−600
-1000
−400
−200
0
200
400
600
800
= +
= HVAC + Pool Pumps
15 / 25

0
−800
−600
-1000
−400
−200
200
400
600
800
MW
=
Buildings as Batteries

HVAC ﬂexibility to provide additional ancillary service
◦ Buildings consume 70% of electricity in the US
HVAC contributes to 40% of the consumption.
16 / 25

◦ Buildings have large thermal capacity
16 / 25

◦ Buildings have large thermal capacity
◦ Modern buildings have fast-responding equipment:
VFDs (variable frequency drive)
16 / 25

Tracking RegD at Pugh Hall — ignore the measurement noise
In one sentence:
17 / 25

In one sentence: Ramp up and down power consumption, just 10%, to
track regulation signal.
17 / 25

Result:
17 / 25

Result:
PJM RegD Measured
Power
(kW)
0
1
-1
0 10 20 30 40
Time (minute)
17 / 25

Pugh Hall @ UF
How much?
−4
−2
0
2
4
−10
0
10
0 500 1000 1500 2000 2500 3000 3500
−0.2
0
0.2
Time (s)
Fan Power Deviation (kW )
Regulation Signal (kW )
Input (%)
Temperature Deviation (◦
C)
One AHU fan with 25 kW motor:
> 3 kW of regulation reserve
Pugh Hall (40k sq ft, 3 AHUs):
> 10 kW
Indoor air quality is not aﬀected
18 / 25

Pugh Hall @ UF
How much?
−4
−2
0
2
4
−10
0
10
0 500 1000 1500 2000 2500 3000 3500
−0.2
0
0.2
Time (s)
Input (%)
C)
> 10 kW
100 buildings:
> 1 MW
18 / 25

Pugh Hall @ UF
How much?
−4
−2
0
2
4
−10
0
10
0 500 1000 1500 2000 2500 3000 3500
−0.2
0
0.2
Time (s)
Input (%)
C)
> 10 kW
100 buildings:
> 1 MW
That’s just using the fans!
18 / 25

What do you think?
Questions:
Capacity?
19 / 25

What do you think?
Questions:
Capacity? Tens of Gigawatts from commercial buildings in the US
19 / 25

What do you think?
Questions:
Can we obtain a resource as eﬀective as today’s spinning reserves?
19 / 25

What do you think?
Questions:
Yes!! Buildings are well-suited to balancing reserves,
and other high-frequency regulation resources
19 / 25

What do you think?
Questions:
much better than any generator
19 / 25

What do you think?
Questions:
How to compute baselines?
19 / 25

What do you think?
Questions:
Who cares? The utility or aggregator is responsible for the equipment –
the consumer cannot ‘play games’ in a real time market!
19 / 25

What do you think?
Questions:
Who cares? The utility or aggregator is responsible for the equipment –
the consumer cannot ‘play games’ in a real time market!
What open issues do you see?
19 / 25

−600
−400
−200
0
200
400
600
Day 1 Day 2 Day 3 Day 4 Day 5 Day 6 Day 7
MW
Intelligent Pools in Florida

Example: One Million Pools in Florida
How Pools Can Help Regulate The Grid
1,5KW 400V
Needs of a single pool
Filtration system circulates and cleans: Average pool pump uses
1.3kW and runs 6-12 hours per day, 7 days per week
20 / 25

1,5KW 400V
Pool owners are oblivious, until they see frogs and algae
20 / 25

1,5KW 400V
Pool owners do not trust anyone: Privacy is a big concern
20 / 25

1,5KW 400V
Pool owners do not trust anyone: Privacy is a big concern
Randomized control strategy is needed.
20 / 25

Pools in Florida Supply G2 – BPA regulation signal∗
Stochastic simulation using N = 105
pools
Reference Output deviation (MW)
−300
−200
−100
0
100
200
300
0 20 40 60 80 100 120 140 160
t/hour
0 20 40 60 80 100 120 140 160
∗transmission.bpa.gov/Business/Operations/Wind/reserves.aspx
21 / 25

pools
−300
−200
−100
0
100
200
300
0 20 40 60 80 100 120 140 160
t/hour
0 20 40 60 80 100 120 140 160
Each pool pump turns on/oﬀ with probability depending on
1) its internal state, and 2) the BPA reg signal
21 / 25

pools
−300
−200
−100
0
100
200
300
0 20 40 60 80 100 120 140 160
t/hour
0 20 40 60 80 100 120 140 160
Mean-ﬁeld model: Input-output system stable? Passive?
21 / 25

Power GridControl WaterPump
Batteries
Coal
GasTurbine
BP
BP
BP C
BP
BP
Voltage
Frequency
Phase
HC
Σ
−
A
LOAD
Conclusions

Conclusions
Conclusions
Answers ... and Questions
1 Volatility
22 / 25

Conclusions
Conclusions
1 Volatility
This appears to be manageable! Demand Dispatch can be designed
to work cooperatively with generation and other resources.
Open questions on many spatial and temporal scales. Most loads
could provide synthetic inertia and governor response1. Is this wise?
1
Scweppe et. al. 1980
22 / 25

Conclusions
Conclusions
1 Volatility
This is real We don’t know why the grid is so reliable today.
1
22 / 25

Conclusions
Conclusions
1 Volatility
Need for better understanding of grid2/distribution/social dynamics.
1
2
Thorpe et. al. 2004
22 / 25

Conclusions
Conclusions
1 Volatility
Scary!
1
2
Thorpe et. al. 2004
22 / 25

Conclusions
Conclusions
1 Volatility
Scary!
Need for Research in Engineering and Economics
1
2
Thorpe et. al. 2004
22 / 25

Conclusions
Conclusions
Thank You!
23 / 25

Conclusions
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
24 / 25

Conclusions
Selected References
More at www.meyn.ece.uﬂ.edu
A. Brooks, E. Lu, D. Reicher, C. Spirakis, and B. Weihl. Demand dispatch. IEEE Power
and Energy Magazine, 8(3):20–29, May 2010.
H. Hao, T. Middelkoop, P. Barooah, and S. Meyn. How demand response from commercial
buildings will provide the regulation needs of the grid. In 50th Allerton Conference on
Communication, Control, and Computing, pages 1908–1913, 2012.
H. Hao, Y. Lin, A. Kowli, P. Barooah, and S. Meyn. Ancillary service to the grid through
control of fans in commercial building HVAC systems. IEEE Trans. on Smart Grid,
5(4):2066–2074, July 2014.
S. Meyn, P. Barooah, A. Buˇsi´c, Y. Chen, and J. Ehren. Ancillary service to the grid using
intelligent deferrable loads. ArXiv e-prints: arXiv:1402.4600 and to appear, IEEE Trans. on
Auto. Control, 2014.
D. Callaway and I. Hiskens, Achieving controllability of electric loads. Proceedings of the
IEEE, vol. 99, no. 1, pp. 184–199, 2011.
M. Parashar, J. Thorp, and C. Seyler. Continuum modeling of electromechanical dynamics
in large-scale power systems. IEEE Trans. on Circuits and Systems I, 51(9):1848–1858,
2004.
25 / 25

Demand-Side Flexibility for Reliable Ancillary Services

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