2014 pv distribution system modeling workshop: determining recommended settings for smart inverters:...
DESCRIPTION
2014 PV Distribution System Modeling Workshop: Determining Recommended Settings for Smart Inverters: Jeff Smith, EPRITRANSCRIPT
Jeff Smith, Matt Rylander, Huijuan LiEPRI
EPRI Smart Inverter Workshop, Santa Clara, CA5/7/2014
Determining Recommended Settings for Smart Inverters
2© 2014 Electric Power Research Institute, Inc. All rights reserved.
Overview
Objective Determine recommended settings for field site demonstration
Evaluate the effectiveness of various smart inverter functions and settings for improving feeder voltage performance as load and PV vary over time
Approach Time-series simulations in OpenDSS comparing feeder performance with and without smart inverter functions
Sites Three different feeders, each with unique characteristics and overall objectives for use of smart inverters
3© 2014 Electric Power Research Institute, Inc. All rights reserved.
Which Smart Inverter Setting is Most Appropriate for My Situation?
0 5 10 15 20 25
1.024
1.026
1.028
1.03
1.032
1.034
1.036
1.038
1.04
1.042
1.044
Hour
Vol
tage
(pu)
Voltages with different voltvar settings
---- Voltvar
---- No PV---- PV base
115 unique volt/var control settings
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Site Characteristics
Site kWdc(Panel size)
kWac(inverter rating
Short-circuit MVA @ POI
X/R @ POI
J1 1900 1700 30-36* 1.8-2.6
E1 605 566 38 1.8
H1 1000 1000 71 1.7
*multiple POI
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Overall Approach
• Solar variability conditions– Clear day– Overcast day– Highly variable day
• Load variability conditions– Peak load day– Minimum load day
• Smart inverter settings– Volt-var– Volt-watt– Off-unity power factor 0
2
4
6
8
10
12
1 3 5 7 9 11 13 15 17 19 21 23 25
Power (M
W)
Local Time (Hour)
Offpeak
Peak
Sandia’s variability index (VI) and clearness index (CI) to classify days
Consideration for Different Feeder Load Profiles
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Smart Inverter Settings
Power Factor Settings (inductive)0.99 0.98 0.97 0.96 0.95 0.94 0.93 0.92 0.91 0.9
Sample volt/var curves shown: see Video for complete set of curves
Similar range of curves used for volt/watt control
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Feeder Model Validation
0.98
0.985
0.99
0.995
1
1.005
1.01
1.015
1.02
0
100
200
300
400
500
600
1 14 27 40 53 66 79 92 105
118
131
144
157
170
183
196
209
222
235
248
261
274
287
300
313
326
339
352
365
378
391
404
417
430
443
456
469
482
495
per‐un
it volta
ge
P (kW)
P (kW)
V_model (pu)
V_measure (pu)
E1
J1 H1
0.98
0.985
0.99
0.995
1
1.005
1.01
1.015
1.02
0
200
400
600
800
1000
1200
1 16 31 46 61 76 91 106
121
136
151
166
181
196
211
226
241
256
271
286
301
316
331
346
361
376
391
406
421
436
451
466
481
496
per‐un
it volta
ge
P (kW)
P (kW)
V_measure (pu)
V_model(pu)
0
50
100
150
200
250
1.02
1.03
1.04
1.05
1.06
1.07
0 50 100 150 200 250 300
PV (k
W)
Volta
ge (V
pu)
Time (sec)
Measured
Simulated
PV (kW)
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Smart Inverter Model ValidationOpenDSS Simulations
260
265
270
275
280
285
290
295
Volta
ge (V
ln)
Time (s)
Measured
Simulated
‐400
‐300
‐200
‐100
0
100
200
300
400
Reactiv
e Po
wer (k
var)
Time (s)
Measured
Simulated
9© 2014 Electric Power Research Institute, Inc. All rights reserved.
Selecting the “Best” Smart Inverter Settings
• Objectives– Each feeder analysis has unique set of objectives– Voltage– Efficiency– Control
• Metrics– Approximately 20 conditions are monitored for each feeder– Only daylight impact is analyzed– Mean voltage at the point of common coupling (PCC)– Voltage variability index at the PCC– Tap operations– Losses
• Rank objective impact based on the metrics for each scenario– Solar– Load
6 combinations all weighted equally (for now…)
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Demo Site J1: Objectives & Metrics
Objective Metric Weight
1. Avoid overvoltage conditions
100
2. Improve customer efficiency
100
3. Reduce line regulator tap changes
100
4. Combined 1, 2, and 3 33/33/33
11© 2014 Electric Power Research Institute, Inc. All rights reserved.
Sample PlotsClear Day Overcast day
Highly variable day
PC
C v
olta
ge
hour
PC
C v
olta
ge
hour
PC
C v
olta
ge
hour
0 5 10 15 20 25 30
1.02
1.025
1.03
1.035
1.04
1.045
1.05
0 5 10 15 20 25 30
1.02
1.025
1.03
1.035
1.04
1.045
1.05
0 5 10 15 20 25 301.01
1.02
1.03
1.04
1.05
1.06
1.07
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Circuit Performance Characterization
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Volt/Var ResultsDemo Site J1
Lesson Learned“best” settings can be difficult to identify
1.01
1.015
1.02
1.025
1.03
1.035
1.04
1.045
1.05
1 9 17 25 33 41 49 57 65 73 81 89 97 105
113
Feeder Head Voltage
Max Feeder HeadVoltage (pu)
Min Feeder HeadVoltage (pu)
0
100
200
300
400
500
600
700
800
900
1 7 13 19 25 31 37 43 49 55 61 67 73 79 85 91 97 103
109
115
Reg/LTC Tap Operations
Tap Operations
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
1 8 15 22 29 36 43 50 57 64 71 78 85 92 99 106
113
Cap Operations
Cap Operations
1400
1450
1500
1550
1600
1650
1700
1 9 17 25 33 41 49 57 65 73 81 89 97 105
113
Feeder Losses (kWh)
Feeder Losses (kWh)
0.99
1
1.01
1.02
1.03
1.04
1.05
1.06
1.07
1 9 17 25 33 41 49 57 65 73 81 89 97 105
113
PCC Voltage
Max PCC Voltage (pu)
Min PCC Voltage (pu)
0
2
4
6
8
10
12
14
16
18
1 7 13 19 25 31 37 43 49 55 61 67 73 79 85 91 97 103
109
115
VI at PCC
VI at PCC
0.97
0.98
0.99
1
1.01
1.02
1.03
1.04
1.05
1.06
1.07
1 8 15 22 29 36 43 50 57 64 71 78 85 92 99 106
113
Feeder End Voltage
Max Feeder EndVoltage (pu)
Min Feeder EndVoltage (pu)
0
1000
2000
3000
4000
5000
6000
7000
1 9 17 25 33 41 49 57 65 73 81 89 97 105
113
Time Above ANSI (sec)
Time Above ANSI (sec)
0.9
0.92
0.94
0.96
0.98
1
1.02
1.04
1.06
1.08
1 7 13 19 25 31 37 43 49 55 61 67 73 79 85 91 97 103
109
Overall Feeder Min/Max Voltage
Max Feeder Voltage(pu)
Min Feeder Voltage(pu)
Peak load day
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Demo Site J1Combined Objective 4 Best Settings• Objective
– Avoids overvoltage– Improves efficiency– Reduces tap operations
• Metrics– Lower mean voltage– Flatter voltage profile – Less tap operations
General trends in rank are due to rolling through different setting
characteristics
Lesson LearnedOverall best settings have similar curves
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Sample Results – Volt/var controlDemo Site J1
‐1.2
‐1
‐0.8
‐0.6
‐0.4
‐0.2
00.95 0.97 0.99 1.01 1.03 1.05
% Avail vars
per‐unit voltage1.01
1.02
1.03
1.04
1.05
1.06
1.07
0 5 10 15 20 25 30
per‐un
it vo
ltage
Hour
no_PV
PV base
voltvar
‐100
0
100
200
300
400
500
600
700
800
900
0 5 10 15 20 25 30
tap op
erations
hour
Tap_noPV
Tap_Pvbase
Tap_voltvar
‐1.5
‐1
‐0.5
0
0.5
1
1.5
0.95 0.97 0.99 1.01 1.03 1.05 1.07 1.09
Negative impact on voltage and line regulator operations
Positive impact on voltage and line regulator operations
1.01
1.02
1.03
1.04
1.05
1.06
1.07
0 5 10 15 20 25 30
per‐un
it volta
ge
hour
no_PV
PV_base
Voltvar
Volt/var curveDaily voltage profile
Regulator tap operations
Volt/var curveDaily voltage profile
Regulator tap operations
0
100
200
300
400
500
600
700
800
0 5 10 15 20 25 30tap op
erations
Tap_noPV
Tap_Pvbase
Tap_voltvar
Lesson LearnedSlight variation in settings can yield significantly different responses
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Demo Site J1Trends in Volt/var Characteristics
Best curves begin absorbing reactive power at 1.02 Vpu
Best curves have a steep volt-varslope
Lesson LearnedInitial results indicate trends can be seen
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Demo Site J1Best Setting Impact for Objective 4 • Each smart inverter function has one “Best” setting• Totalized metric for each “Best” setting in Objective 4 is
shown• The Volt-var function and setting has the best impact for
each metric
PV volt/var volt/watt power factor
PCC Mean Voltage (pu) 1.031 1.027 1.031 1.031
PCC VVI 18.88 8.39 15.56 8.41Tap Operations 675 418 603 523
18© 2014 Electric Power Research Institute, Inc. All rights reserved.
Metric Improvement Based on Objective
PV volt/var volt/watt power factor
PCC Mean Voltage 1.031 1.027 1.031 1.031PCC VVI 18.88 8.39 15.56 8.41Tap Operations 675 418 603 523
PCC Mean Voltage 1.031 1.025 1.031 1.031PCC VVI 18.88 30.21 15.56 14.18Tap Operations 675 1727 603 485
PCC Mean Voltage 1.031 1.033 1.032 1.031PCC VVI 18.88 6.02 9.92 8.41Tap Operations 675 437 533 523
PCC Mean Voltage 1.031 1.034 1.032 1.032PCC VVI 18.88 6.60 9.92 9.599Tap Operations 675 401 533 485
Obj 4Overall
Obj 1Reduce
Overvoltage
Obj 2Improve
Efficiency
Obj 3Reduce
Taps
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Demo Site J1 Best Curves
• Best volt/var and volt/watt curves shown for each objective
• Each objective optimized with different curve characteristics
Objective 1Objective 2Objective 3Objective 4
Best Power Factor SettingObjective 1 2 3 4
power factor
0.90 0.97 0.94 0.97
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Impact of Load Level on Best Settings
Peak LoadOffpeak Load
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Sample Day – Comparing “Best” Setting Responses
Offpeak day, highly variable solar
1.02
1.025
1.03
1.035
1.04
1.045
1.05
0 5 10 15 20
per‐un
it vo
ltage
hour
PCC Voltage
0
10
20
30
40
50
60
70
80
0 5 10 15 20
#
hour
Tap Operations
Lesson LearnedPower factor and proper volt/varsettings can be effective
22© 2014 Electric Power Research Institute, Inc. All rights reserved.
Demo Site E1: Objectives & Metrics
Objective Metric Weight
1. Reduce voltageflicker/voltage variations
100
2. Reduce losses 1003. Combined 1 and 2 50/50
23© 2014 Electric Power Research Institute, Inc. All rights reserved.
Sample Plots
0 5 10 15 20 25 300.975
0.98
0.985
0.99
0.995
1
1.005
1.01
1.015
0 5 10 15 20 25 300.985
0.99
0.995
1
1.005
1.01
1.015
0 5 10 15 20 25 300.975
0.98
0.985
0.99
0.995
1
1.005
1.01
1.015
Clear Day Overcast day
Highly variable day
PC
C v
olta
ge
hour
PC
C v
olta
ge
hour
PC
C v
olta
ge
hour
24© 2014 Electric Power Research Institute, Inc. All rights reserved.
Demo Site E1 Best Curves
• 3 best volt/var and volt/watt curves shown for each objective
• Each objective optimized with different curve characteristics
Objective 1Objective 2Objective 3
Best Power Factor SettingObjective 1 2 3
power factor 0.92 0.99 0.93
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Metric Improvement Based on Objective
PV volt/var volt/watt power factor
PCC VVI 9.1787 7.4029 8.9498 6.8539Losses (kWh) 3079 3038 3078 3124
PCC VVI 9.1787 7.0951 8.9498 6.8480Losses (kWh) 3079 3082 3078 3129
PCC VVI 9.1787 7.4029 8.9498 8.1283Losses (kWh) 3079 3038 3078 3091
Obj 3
Obj 1
Obj 2
power factor does not reduce losses
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Demo Site H1: Objectives & Metrics
Objective Metric Weight
1. Flatter voltage and improved customer efficiency
5050
2. Reduced LTC tap changes
100
3. Combined 1 and 2 25/25/50
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Demo Site H1: Best Curves
• 1 best volt/var and volt/watt curves shown for each objective
• Each objective optimized with different curve characteristics
Best Power Factor SettingObjective 1 2 3
power factor 0.92 0.96 0.96
Objective 1Objective 2Objective 3
28© 2014 Electric Power Research Institute, Inc. All rights reserved.
Metric Improvement Based on Objective
PV volt/var volt/watt power factor
PCC Mean Voltage 1.008 1.008 1.008 1.007PCC VVI 11.5798 10.7196 11.0827 8.0583Tap Operations 54 53 54 55
PCC Mean Voltage 1.008 1.006 1.008 1.007PCC VVI 11.5798 11.0533 11.0827 8.0391Tap Operations 54 57 54 55
PCC Mean Voltage 1.008 1.009 1.008 1.007PCC VVI 11.5798 9.4340 10.1347 8.0583Tap Operations 54 50 53 55
Obj 3
Obj 1
Obj 2
29© 2014 Electric Power Research Institute, Inc. All rights reserved.
Summary
• Overall “best” setting depends upon objective– Improve voltage– Increase efficiency– Regulator operations– Increase hosting
• Preliminary analysis indicates trends in recommended settings can be found
• Caution: Minor changes in settings (volt/var) can have significantly different impacts
• Less “aggressive” settings work– Less risk, less potential benefit
(e.g., increasing hosting capacity)
• Results shown today are based upon site-specific conditions
• Future work for determining recommended settings– Other locations– Other feeders– Combined inverters
Jeff Smith, Huijuan LiEPRI
EPRI Smart Inverter Workshop, Santa Clara, CA5/7/2014
Potential Interaction Between Smart Inverters
31© 2014 Electric Power Research Institute, Inc. All rights reserved.
Overview
Objective ApproachEvaluating potential inverter interaction
Investigate possible inverter interaction resulting from smart inverter control on multiple PV systems
Time-domain analysis in Matlab/Simulink to investigate possible inverter interaction
32© 2014 Electric Power Research Institute, Inc. All rights reserved.
Studied System
PV1: 400 kW, 475 kVAPV2: 1000 kW, 1235 kVA20 s simulation widow 1.2 Mvar Cap is switched on at 10 s, which causes voltage rise
33© 2014 Electric Power Research Institute, Inc. All rights reserved.
Interactions Between the Two InvertersSingle PV providing vars Both PVs providing vars
4 6 8 10 12 14 16 18 200.95
0.96
0.97
0.98
0.991
1.01
1.02
1.03
1.04
1.05
Time(s)
Vol
tage
(pu)
4 6 8 10 12 14 16 18 200.95
0.96
0.97
0.98
0.991
1.01
1.02
1.03
1.04
1.05
Time(s)
Vol
tage
(pu)
V1
V2
4 6 8 10 12 14 16 18 200.950.96
0.97
0.980.99
1
1.011.02
1.03
1.041.05
Time(s)
Vol
tage
(pu)
4 6 8 10 12 14 16 18 200.950.96
0.97
0.980.99
1
1.011.02
1.03
1.041.05
Time(s)
Vol
tage
(pu)
V1
V2
OscillationsObserved !
34© 2014 Electric Power Research Institute, Inc. All rights reserved.
What May Impact Var Control Var control flow
VoltVar CurveInverter
Averagingwindow
VReference Q
Average V
QPI
controller
(Kp Ki)
Switching Command
Factors may impact var control:• Volt-var curve parameters• PI controller parameters: Kp and Ki
• Voltage average window length
35© 2014 Electric Power Research Institute, Inc. All rights reserved.
Impact of Volt-var Parameters
Volt/var 1 Volt/var 2
% AvailableVars
voltage (pu)
‐100
Capacitive100
Inductive
0.95 1.05
% AvailableVars
voltage (pu)
‐100
Capacitive100
Inductive
0.99 1.01
Controller parameters for both cases:
Kp Ki0.3 3
36© 2014 Electric Power Research Institute, Inc. All rights reserved.
4 6 8 10 12 14 16 18 200.950.96
0.97
0.980.99
1
1.011.02
1.03
1.041.05
Time(s)
Vol
tage
(pu)
4 6 8 10 12 14 16 18 200.950.96
0.97
0.980.99
1
1.011.02
1.03
1.041.05
Time(s)
Vol
tage
(pu)
Volt/var 1
Voltages
4 6 8 10 12 14 16 18 200.95
0.96
0.97
0.98
0.99
1
1.01
1.02
1.03
1.04
1.05
Time(s)
Vol
tage
(pu)
V1 V1
4 6 8 10 12 14 16 18 200.95
0.96
0.97
0.98
0.99
1
1.01
1.02
1.03
1.04
1.05
Time(s)
Vol
tage
(pu)
V2 V2
Volt/var 2
High ratio may cause oscillations
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Volt/var 1
4 6 8 10 12 14 16 18 20-100
-80
-60
-40-20
0
2040
60
80100
Time (s)
% o
f Ava
ilabl
e V
ar
Actual varVar reference
Vars
Var 1 Var 1
Var 2 Var 2
4 6 8 10 12 14 16 18 20-100
-80
-60
-40-20
0
2040
60
80100
Time(s)
% A
vaila
ble
Var
s
Actual VarVar reference
4 6 8 10 12 14 16 18 20-100
-80
-60
-40-20
0
2040
60
80100
Time(s)
% A
vaila
ble
Var
s
Actual varVar reference
4 6 8 10 12 14 16 18 20-100
-80
-60
-40-20
0
2040
60
80100
Time (s)
% A
vaila
ble
Var
s
Actula varVar reference
Volt/var 2
38© 2014 Electric Power Research Institute, Inc. All rights reserved.
Impact of Controller Parameters
Volt/var 2 Volt/var 2: slower response
% AvailableVars
voltage (pu)
‐100
Capacitive100
Inductive
0.99 1.01
Controller parameters for case 1:
Kp Ki0.3 3
% AvailableVars
voltage (pu)
‐100
Capacitive100
Inductive
0.99 1.01
Kp Ki0.1 1
Controller parameters for case 2:
39© 2014 Electric Power Research Institute, Inc. All rights reserved.
4 6 8 10 12 14 16 18 200.950.96
0.97
0.980.99
1
1.011.02
1.03
1.041.05
Time(s)
Vol
tage
(pu)
Volt/var 2
4 6 8 10 12 14 16 18 200.950.96
0.97
0.980.99
1
1.011.02
1.03
1.041.05
Time(s)
Vol
tage
(pu)
Voltages
V1 V1
V2 V24 6 8 10 12 14 16 18 20
0.950.96
0.97
0.980.99
1
1.011.02
1.03
1.041.05
Time(s)
Vol
tage
(pu)
Volt/var 2: slower response
4 6 8 10 12 14 16 18 200.950.96
0.97
0.980.99
1
1.011.02
1.03
1.041.05
Time(s)
Vol
tage
(pu)
Smaller control parameters, which means smaller adjustments at each step, reduce
the oscillations
40© 2014 Electric Power Research Institute, Inc. All rights reserved.
4 6 8 10 12 14 16 18 20-100
-80
-60
-40-20
0
2040
60
80100
Time(s)
% A
vaila
ble
Var
s
Actual varVar reference
Volt/var 2
4 6 8 10 12 14 16 18 20-100
-80
-60
-40-20
0
2040
60
80100
Time(s)
% A
vaila
ble
Var
s
Actual VarVar reference
4 6 8 10 12 14 16 18 20-100
-80
-60
-40-20
0
2040
60
80100
Time(s)
% A
vaila
ble
Var
s
Actual varVar reference
Vars
Var 1Var 1
Var 2 Var 24 6 8 10 12 14 16 18 20
-100
-80
-60
-40-20
0
2040
60
80100
Time(s)
% A
vaila
ble
Var
s
Actual varVar reference
Volt/var 2: slower response
41© 2014 Electric Power Research Institute, Inc. All rights reserved.
Impact of Window Length of Averaging Voltage
Volt/var 2 Volt/var 2: larger avg window
% AvailableVars
voltage (pu)
‐100
Capacitive100
Inductive
0.99 1.01
% AvailableVars
voltage (pu)
‐100
Capacitive100
Inductive
0.99 1.01
Controller parameters for both cases:
Kp Ki0.3 3
Length of average window= 0.05s Length of average window= 1 s
42© 2014 Electric Power Research Institute, Inc. All rights reserved.
Volt/var 2
4 6 8 10 12 14 16 18 200.950.96
0.97
0.980.99
1
1.011.02
1.03
1.041.05
Time(s)
Vol
tage
(pu)
Voltages
V1 V1
V2 V24 6 8 10 12 14 16 18 20
0.950.96
0.97
0.980.99
1
1.011.02
1.03
1.041.05
Time(s)
Vol
tage
(pu)
Volt/var 2: larger avg window
4 6 8 10 12 14 16 18 200.95
0.96
0.97
0.98
0.99
1
1.01
1.02
1.03
1.04
1.05
Time(s)
Vol
tage
(pu)
4 6 8 10 12 14 16 18 200.95
0.96
0.97
0.98
0.99
1
1.01
1.02
1.03
1.04
1.05
Time(s)
Vol
tage
(pu)
Longer voltage averaging window increases oscillation magnitude, but
improved dampening occurs
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Volt/var 2
4 6 8 10 12 14 16 18 20-100
-80
-60
-40-20
0
2040
60
80100
Time(s)
% A
vaila
ble
Var
s
Actual VarVar reference
4 6 8 10 12 14 16 18 20-100
-80
-60
-40-20
0
2040
60
80100
Time(s)
% A
vaila
ble
Var
s
Actual varVar reference
Vars
Var 1 Var 1
Var 2 Var 2
Volt/var 2: slower avg window
4 6 8 10 12 14 16 18 20-100
-80
-60
-40
-20
0
20
40
60
80
100
Time(s)
% A
vaila
ble
Var
s
Actual varVar reference
4 6 8 10 12 14 16 18 20-100
-80
-60
-40
-20
0
20
40
60
80
100
Actual varVar reference
44© 2014 Electric Power Research Institute, Inc. All rights reserved.
Conclusions
• Interactions exist between the two close by inverters• High ratio may cause oscillations• Smaller adjustments at each step as a result of smaller
control parameters reduces oscillations• Longer voltage averaging window increases magnitude of
oscillations, although dampening does occur