Spectral Decomposition of Demand-Side Flexibility for Reliable Ancillary Services

Spectral Decomposition of Demand-Side Flexibility
for Reliable Ancillary Services
International Conference on System Sciences
Kauai — January 5-8, 2015
Sean P. Meyn
Prabir Barooah and Ana Buˇsi´c
Yue Chen, Jordan Ehren, He Hao
Electrical and Computer Engineering & Florida Institute for Sustainable Energy
University of Florida
Thanks to NSF, AFOSR, and DOE / TCIPG

Demand-Side Flexibility for Reliable Ancillary Services
Outline
1 What Do We Want?
2 Spectral Decomposition
3 Buildings as Batteries
4 Intelligent Pools in Florida
5 Conclusions

Contour Map: Real Time Market - Locational Marginal Pricing Help?
$10/MWh
Nirvana @ ERCOT
What Do We Want From DR?

What Do We Want?
We want: Responsive Regulation
Plot of wind generation output in BPA — First week of 2015
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
1 / 15

What Do We Want?
Demand Dispatch the Answer?
A partial list of the needs of the grid operator, and the consumer:
2 / 15

What Do We Want?
High quality AS? (Ancillary Service)
Does the deviation in power consumption accurately track the desired
deviation target?
2 / 15

What Do We Want?
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
Reg service from generators is not perfect
2 / 15

What Do We Want?
High quality AS?
Reliable?
Will AS be available each day?
It may vary with time, but capacity must be predictable.
2 / 15

What Do We Want?
High quality AS?
Reliable?
Cost eﬀective?
This includes installation cost, communication cost, maintenance,
and environmental.
2 / 15

What Do We Want?
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?
2 / 15

What Do We Want?
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.
2 / 15

What Do We Want?
High quality AS?
Reliable?
Cost eﬀective?
Customer QoS constraints satisﬁed?
Demand Dispatch can do all of this! (by design)
2 / 15

GW
0
1
2
3
4
Gr(t)
Gr = G1 + G2 + G3
G1
Spectral Decomposition

Taming Scary Ramps – An Example from BPA
GW
0
1
2
3
4
3 / 15

GW
0
1
2
3
4
Scary ramps
3 / 15

GW
0
1
2
3
4
G
Goal:
W (t) = Wind generation in BPA, Jan 2015
Scary ramps
GW (t) + Gr(t) ≡ 4GW
3 / 15

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
Can the product be obtained
from generation?
Gr(t)
3 / 15

GW
0
1
2
3
4
Goal: GW (t) + Gr(t) ≡ 4GW
Can the product be obtained
from generation?
Gr(t)
Gr(t)
Scary
3 / 15

GW
0
1
2
3
4
Proposal:
Gr(t)
Scary
Gr = G1 + G2 + G3
3 / 15

GW
0
1
2
3
4
Proposal:
Gr(t)
Scary
Gr = G1 + G2 + G3
H1 : Low pass
H2 : Band pass
H3 : High pass
Gi = HiGr
3 / 15

GW
0
1
2
3
4
Proposal:
Similar to PJM’s RegA/D
Gr(t)
Scary
Gr = G1 + G2 + G3
H1 : Low pass
H2 : Band pass
H3 : High pass
Gi = HiGr
3 / 15

GW
0
1
2
3
4
Gr(t)
Gr = G1 + G2 + G3
G1
3 / 15

GW
0
1
2
3
4
Gr(t)
Gr = G1 + G2 + G3
G1
Not at all scary!
3 / 15

GW
0
1
2
3
4
Gr(t)
Gr = G1 + G2 + G3
G1
G2
3 / 15

GW
0
1
2
3
4
Gr(t)
Gr = G1 + G2 + G3
G1
G2
G3
3 / 15

GW
0
1
2
3
4
Gr(t)
Nothing
Scary
Here!
G1
G2
G3
3 / 15

GW
0
1
2
3
4
Gr(t)
G1
G2
G
Gas-turbine/hydro
3
3 / 15

GW
0
1
2
3
4
Gr(t)
G1
G2
G
Gas-turbine/hydro
Chillers/pool pumps
3
3 / 15

GW
0
1
2
3
4
Gr(t)
G1
G2
G
Gas-turbine/hydro
Chillers/pool pumps
Interior commercial HVAC3
3 / 15

Control Architecture
Frequency Decomposition
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
4 / 15

Frequency Decomposition
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.
4 / 15

Example from BPA
Balancing Reserves from Bonneville Power Authority:
−800
−600
-1000
−400
−200
0
200
400
600
800
BPA Reg signal
(one week)
MW
5 / 15

Example from BPA
−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
= +
5 / 15

Example from BPA
−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 ?
5 / 15

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.
6 / 15

◦ Buildings have large thermal capacity
6 / 15

◦ Buildings have large thermal capacity
◦ Modern buildings have fast-responding equipment:
VFDs (variable frequency drive)
6 / 15

Tracking RegD at Pugh Hall — ignore the measurement noise
In one sentence:
7 / 15

In one sentence: Ramp up and down power consumption, just 10%, to
track regulation signal.
7 / 15

Result:
7 / 15

Result:
PJM RegD Measured
Power
(kW)
0
1
-1
0 10 20 30 40
Time (minute)
7 / 15

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
8 / 15

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
8 / 15

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!
8 / 15

What do you think?
Questions:
Capacity?
9 / 15

What do you think?
Questions:
Capacity? Tens of Gigawatts from commercial buildings in the US
9 / 15

What do you think?
Questions:
Can we obtain a resource as eﬀective as today’s spinning reserves?
9 / 15

What do you think?
Questions:
Yes!! Buildings are well-suited to balancing reserves,
and other high-frequency regulation resources
9 / 15

What do you think?
Questions:
much better than any generator
9 / 15

What do you think?
Questions:
How to compute baselines?
9 / 15

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!
9 / 15

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?
9 / 15

−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
10 / 15

1,5KW 400V
Pool owners are oblivious, until they see frogs and algae
10 / 15

1,5KW 400V
Pool owners do not trust anyone: Privacy is a big concern
10 / 15

1,5KW 400V
Pool owners do not trust anyone: Privacy is a big concern
Randomized control strategy is needed.
10 / 15

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
11 / 15

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
Each pool pump turns on/oﬀ with probability depending on
1) its internal state, and 2) the BPA reg signal
11 / 15

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

Conclusions
Conclusions
What we want: Responsive Regulation and Happy Consumers
12 / 15

Conclusions
Conclusions
We got it!
12 / 15

Conclusions
Conclusions
High quality Ancillary Service
Reliable on many time scales
Cost eﬀective? marginal cost zero?
Customer QoS constraints satisﬁed? damn straight!
12 / 15

Conclusions
Conclusions
High quality Ancillary Service
Reliable on many time scales
Cost eﬀective? marginal cost zero?
Customer QoS constraints satisﬁed? damn straight!
Demand Dispatch can do all of this!
12 / 15

Conclusions
Conclusions
A caveat: There is the “tragedy of the commons”
– perhaps not so in Hawaii?
12 / 15

Conclusions
Conclusions
A caveat: There is the “tragedy of the commons”
– perhaps not so in Hawaii?
Need for Research in Engineering and Economics
12 / 15

Conclusions
Conclusions
Thank You!
13 / 15

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
14 / 15

Conclusions
References: Demand Response
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. Buˇsić, 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.
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. 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.
15 / 15

Spectral Decomposition of Demand-Side Flexibility for Reliable Ancillary Services

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