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1
Centralized and Decentralized Control for Demand Response
Energy and Environment SeminarUniversity of Washing
October 28th, 2010
Project team:Shuai Lu (PI) Harold Kirkham Nader Samaan Ruisheng Diao Marcelo Elizondo Chunlian Jin Ebony Mayhorn Yu Zhang
Presented by:Shuai Lu
Outline
Concept of demand responseTypes of demand response programs Centralized and decentralized control in existing power systemsModels to simulate the effects of demand responseComparing the two control philosophiesConcluding remarks
Defining Demand Response
An earlier definition by FERC (2008)[1]: A reduction in the consumption of electric energy by customers from their expected consumption in response to an increase in the price of electric energy or to incentive payments designed to induce lower consumption of electric energy.
Newer definition by FERC (2010)[2]:“demand response” includes consumer actions that can change any part of the load profile of a utility or region.
smart appliances or devices that can respond automatically to the signals from utility or changes of power system condition.smart integration of changeable consumption with variable generation (wind and solar)manage demand as needed to provide grid services such as regulation and reserves
[1] Wholesale Competition in Regions with Organized Electric Markets, FERC Order No. 719, October 2008[2] National Action Plan on Demand Response. FERC, June 2010
Type of Demand Response Programs
FERC DR Categorization [3]:Type 1: dynamic pricing without enabling technologies (manual response to price signal)Type 2: dynamic pricing with enabling technologies (automatic response to price signal) Type 3: direct load control Type 4: interruptible tariffs Type 5: demand response programs operated by Independent System Operators (ISO) or utilities (providing various reserves for the system)
Another category that need to be added:Type 6: autonomous load response to frequency and voltage
4
[3] A National Assessment of Demand Response Potential, FERC, June 2009
Group DR Programs Based on Control Approaches
5
Grouping Criteria Location where theinformation is from
Local CenterLocation
where the response decision is
made
Local Type 6 *Types 1 & 2
Central Types 3, 4 & 5
*If the price is generated through an auction process, in which both generation and demand submit bids in real time to get a market clearing price, then DR Type 1 and 2 could be considered decentralized control. Otherwise, if the price signal is “designed” by the system operator according to certain physical variables of the system, Type 1 and 2 could be considered a combination of centralized and decentralized control,
Centralized and Decentralized Control in Existing Power Systems
Purpose of controlsTo maintain system voltages and frequency and other system variables within their acceptable limits, in response to normal load and generation variations as well as large disturbances.
Centralized controlsGeneration scheduling and dispatchAutomatic generation control for frequency regulationReal and reactive power flow adjustments to resolve congestions or reduce loss
Decentralized controlsGenerator governor responseAutomatic voltage regulationProtection relays
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A Test Platform for Demand Response Control Approaches
7
800
806 808 812 814
810
802 850
818
824 826
816
820
822
828 830 854 856
852
832888 890
838
862
840836860834
842
844
846
848
864
858
Modified IEEE 34 bus test feeder:Lumped loads were replaced by 147 detailed household load models;A load factor of 40% was assumed to determine the number of households.
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Water Heater Model
8
24.00019.20014.4009.60004.8000-0.0000 [h]
45.00006
45.00004
45.00002
45.00000
44.99998
44.99996
44.99994
test_blick: y1
24.00019.20014.4009.60004.8000-0.0000 [h]
130.00
120.00
110.00
100.00
90.00
80.00
70.00
test_blick: Tw
24.00019.20014.4009.60004.8000-0.0000 [h]
0.005
0.004
0.003
0.002
0.001
0.000
-0.001
water heater_single: Total Active Power in MW
myinputs(2)
Date: 7/9/2010
Annex: /2
DIg
SILE
NT
Water temperature
Active power
Water flow
Electric power
Water temperature
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Air Conditioning Model
9
10000.08000.06000.04000.02000.00.0000 [s]
PQ Measurement: Active Power in p.u.
10000.08000.06000.04000.02000.0-0.0000 [s]
84.00
83.00
82.00
81.00
80.00
House Common Model: To
10000.08000.06000.04000.02000.0-0.0000 [s]
3.00
2.00
1.00
0.00
-1.00
House Common Model: p
10000 08000 06000 04000 02000 00 0000 [s]
79.00
78.00
77.00
76.00
75.00
74.00
73.00
Outdoor temperature
Active power
Indoor temperature
Equivalent Thermal Parameters Circuit
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Ten Types of House Load Representing Other Appliances
10
site ResidenceSize
Occupants_number
28 2965 460 3156 3
100 2510 3110 1518 2250 1248 2344 4119 6361 2416 4364 868 1483 1988 2500 2676 3
Information of the 10 types house
Other appliances data is taken from ELCAP load data set
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Single House Model
11
A/C Water Heater Other appliances
Response Mechanisms in the Household Load Model
All demand responses come from A/C units and water heaters, i.e., thermostat-controlled loads.Centralized control
Proportional controllers for temperature settings adjustmentDirect on/off controlCommunication delays are added
Decentralized controlBang-bang controllers for frequency, voltage and price responses
12
Simulations of the Two Control Approaches
Two types of DR functions were simulated:Response to power system frequency dipBalancing generation and load (regulation and load following services)
The modified IEEE 34 bus feeder is connected to the IEEE 39 bus transmission system model to simulate frequency response.Regulation signal from a balancing authority and wind power derived from actual wind data were used to test balancing services.
13
1414 Project:
Graphic: 39-bus_grid
RMS-Simulation,balanced 10:000 sNodesLine to Line Positive-Sequence Voltage, Magnitude [kV]Li G d P i i S V l M i d [ ]
Main67.5880.9803.545
Station7/B794.8950.949-5.534
Station6/B696.8460.968-2.404
Station5/B596.3990.964-3.159
Station4/B496.5780.966-3.130
Station3/B399.3190.993-1.878
Station2/B2101.18..1.012-0.543
Station29/B29103.80..1.0389.201
Station28/B28103.53..1.0356.314
on1/B193.3940.934
-12.73..
Station27/B27100.91..1.0090.974
Station26/B26102.90..1.0292.367
Station25/B25103.61..1.0361.652
Station24/B24100.10..1.0014.855
Station23/B23101.97..1.020
13.489
Station22/B22102.84..1.028
13.703
Station21/B21100.09..1.0018.024
Station20/B20102.99..1.030
11.454
Station19/B19100.52..1.00511.745
Station18/B1899.4290.9940.014
Station17/B1799.7850.9981.877
Station16/B1699.4660.9954.385
Station15/B1597.8080.9781.860
Station14/B1497.6070.976-0.282
Station13/B1398.2250.9820.924
Station12/B1296.7530.9680.498
Station11/B1197.8940.9790.177
Station10/B1098.6610.9871.469
tation9/B991.9450.919-14.99..
Station8/B894.3670.944-6.522
2-W
inding
..
2.010.64
78.96
-2.01-0.4778.96Load21
262.21110.05
Load8
471.21158.88
Load39
841.00190.44
G~G10
250.38348.9828.63
G~G9
845.6368.2198.08G~
G8
608.6773.71
101.01
G~G7
634.98127.4598.13
G~G6
785.23361.17110.10
G~G5
570.26-74.59104.57
G~G4
713.06362.37111.87
740.65345.69102 17
G~G2
523.80337.9392.35
G~G1
Traf
o9
845.6368.2192.27
-840.1..39.3792.27
L28-29-356.3..9.96
199.37
357.98-18.76199.37
L26-28-154.2..-35.5788.96
155.20-36.9088.96L25-26
38.55-53.3336.92
-38.49-0.7136.92
L26-
27-182.8..-129.3..128.15
183.53111.22128.15
L17-
27-86.3056.9771.0686.47-87.1871.06
Traf
o8
608.6773.7192.32
-606.5..9.82
92.32
L2-2
5
-416.9..54.22
241.01
429.08-54.61241.01
Traf
o10
-250.3..-318.5..27.36
250.38348.9827.36
L16-
24
143.7598.58102.78-143.6..-103.5..102.78
Traf
o6
-785.2..-263.7..103.20
785.23361.17103.20
L23-
24
-437.3..-10.86252.32
441.5640.83
252.32
Traf
o7
634.98127.4588.75
-633.0..-22.4888.75
L22-
23
46.4781.2562.27
-46.41-99.6662.27
L21-22-734.3..-131.5..430.38
738.76182.46430.38
Traf
o19-
2..
-47.72-234.1..28.94
48.15242.4928.94
Traf
o4
713.06362.37107.60
-708.5..-269.8..107.60
Traf
o5
570.26-74.5995.16
-567.3..133.2695.16
L16-
19
660.3627.41379.63
-653.4..26.69379.63
L16-
21
470.1220.86
272.07
-468.3..-16.30272.07
L17-18
-393.6..-9.75
228.69
394.789.52
228.69
L3-1
8
-243.8..5.51
142.42
244.53-18.57142.42
L16-
17
482.93-69.64283.24
-481.2..77.66283.24
L15-
16-467.2..-125.8..285.67
469.45132.04285.67
L14-
15
-163.7..-9.8297.64
164.30-19.0097.64
L13-
14
-203.3..-47.72123.55
203.7435.74123.55
Traf
o12-
1..
-17.79-44.595.87
17.8345.675.87Tr
afo1
1-1.
.
-10.6939.094.87
10.72-38.354.87
Traf
o3
-740.6..-206.6..104.24
740.65345.69104.24
L10-
13221.7976.81
138.76
-221.5..-81.42138.76
L10-
11518.85129.79313.97-517.6..-124.1..313.97
L3-4
105.85111.5098.74
-105.5..-127.0..98.74
L4-5
4.537.02
11.99-4.53
-19.4911.99
L2-3
164.7099.27
117.98
-164.2..-119.2..117.98
L1-2
-492.6..-113.6..312.52
502.61165.01312.52
L1-3
9
-489.5..-100.9..321.03
492.60113.65321.03
L9-3
9
352.9828.98
232.90
-351.4..-89.47232.90
L8-9356.37
49.53222.40
-352.9..-28.98222.40
L5-6
-482.9..-127.7..299.19483.47130.62299.19
L5-8
-485.2..-129.1..307.19
487.46147.19307.19
L7-8342.92
78.65215.01
-342.3..-79.28215.01
L6-7557.42
178.59350.74
-555.2..-155.1..350.74
L6-1
1-526.2..-73.63316.79528.3785.06316.79
Traf
o2
514.63333.3589.34
-514.6..-235.5..89.34
L26-29
-201.9..-38.73116.53
204.18-46.98116.53
L4-14-365.9..-51.77220.95
367.1257.54
220.95
Load4
466.93171.83
Load3
302.212.25
Load18
149.1528.32
Load25
215.9245.50
Load26
134.1116.40
Load27
269.1972.33
Load28
201.1126.95
Load29
277.9626.37
Load24
293.61-87.72
Load15
302.97144.86
Load16
313.0430.73
Load23
237.9181.32
Load20
615.05100.88
Load12
7.0782.94
Load31
9.174.59
Load7
212.2976.53
DIg
SILE
NT
Connection to test feeder
Connection to test feeder
Under- frequency event
Under- frequency event
Under- voltage event
Under- voltage event
Simulation with Transmission networkIEEE 39 bus system with 10 generators, total generation around 6.18 GW
IEEE 34 bus system
Frequency Event Created
15
0 10 20 30 40 50 6059.2
59.4
59.6
59.8
60
60.2
Time (min)
Freq
uenc
y (H
z)
Frequency dip created by tripping generator 1, a large generator in the IEEE 39 bus system. Loads at buses 20, 8 and 39 were disconnected to simulate the recovery of the system frequency.
Frequency Response Provided by DR
16
0 10 20 30 40 50 601500
2000
2500
3000
3500Total Feeder Load
Time (min)
Act
ive
Pow
er (k
W)
DR to frequency event @ 6minBase case (no frequency event)
0 10 20 30 40 50 602000
2500
3000
3500Total Feeder Load
Time (min)A
ctiv
e P
ower
(kW
)
DR to 5 degF temp setting changeBase CaseCentralized control:
Assuming 20 seconds delay by devices and 2 min delay by operators [4].
Decentralized control:Frequency thresholds 59.4 and 59.94 Hz.
[4] Demand Response Spinning Reserve Demonstration, LBNL-62761, Lawrence Berkeley National Laboratory, May 2007
Initialization period of A/C and water heaters
DR Following Regulation Signals
17
0 10 20 30 40 50 602200
2400
2600
2800
3000
3200
3400Total Feeder Load
Time (min)
Act
ive
Pow
er (k
W)
DR to regulation signalBase case
0 10 20 30 40 50 60-200
0
200
400Regulation Signal
Time (min)
Act
ive
Pow
er
0 10 20 30 40 50 60-300
-200
-100
0
100Feeder Load Reduction
Time (min)
Act
ive
Pow
er
Feeder load
Regulation signal and demand response providing regulation:Assuming 5 sec communication delay
DR Following Wind Power Variations
Water heaters and A/C units following wind power variation:Assuming 5 sec communication delay
Control law:ΔTset = k•RegWith constraints on Tset and ΔTset
0 10 20 30 40 50 600.0105
0.011
0.0115
0.012Regulation Signal
Time (min)
Act
ive
Pow
er (p
u)
0 10 20 30 40 50 60-1000
-500
0
500Feeder Load Reduction
Time (min)
Act
ive
Pow
er (k
W)
Regulation Signal Derived from Wind Power Output
Predictability of DR under Centralized Control
19
0 10 20 30 40 50 602000
2200
2400
2600
2800
3000
3200
3400Total Feeder Load
Time (min)
Act
ive
Pow
er (k
W)
1 degF temperature setting change2 degF temperature setting change3 degF temperature setting change5 degF temperature setting changeBase case
Feeder load change as a function of changes in temperature settings (ΔTset )
Predictability of DR under Centralized Control
20
1 2 3 50
100
200
300
400
Temperature Setting Change (degF)
Act
ive
Pow
er (k
W)
Max Feeder Load Reduction
144.44194.69 216.72
291.20
1 2 3 50
50
100
150
Temperature Setting Change (degF)
Ene
rgy
(kW
h)
Energy of temperature setting change from base case
34.0356.66
74.06
113.33
Load reduction (max kW) as a function of changes in temperature settings
Load reduction (kWh in 60-minute simulation) as a function of changes in temperature settings
Predictability of DR under Decentralized Control
21
0 10 20 30 40 50 601500
2000
2500
3000
3500Total Feeder Load
Time (min)
Act
ive
Pow
er (k
W)
DR to frequency event @ 6minBase case (no frequency event)
Reduction caused by frequency response
Reduction caused by voltage response
Comparison of the Characteristics of Two Control Philosophies
Response timeDecentralized control is much faster and suitable for improving system frequency response or resolving frequency and voltage stress of the system.Centralized control is slower and can not follow the fast changes of regulation signal but is suitable for load following service and spinning reserve.
PredictabilityResponse from decentralized control is more complicated and harder to predict.Response from centralized control is close-to-linear, in terms of load change vs. temperature setting adjustment
Reliability, complexity…
22
Conclusion
Similar to how centralized and decentralized control philosophies are applied in the control of generation and transmission systems, it is expected that the advantages of both centralized control and decentralized control be exploited to achieve the best performance of the smart grid.
23
Acknowledgement
Research is funded by PNNL lab directed research and development (LDRD) program.The project team received support and help from the following PNNL colleagues:
Carl ImhoffDave ChassinJason FullerChellury Sastry
