2014 pv distribution system modeling workshop: determining recommended settings for smart inverters:...

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


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


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


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


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


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)


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


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…)


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


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


Circuit Performance Characterization


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


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


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


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


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


Metric Improvement Based on Objective


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




Obj 4Overall

Obj 1Reduce

Overvoltage

Obj 2Improve

Efficiency

Obj 3Reduce

Taps


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


Impact of Load Level on Best Settings

Peak LoadOffpeak Load


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


Demo Site E1: Objectives & Metrics


1. Reduce voltageflicker/voltage variations

100

2. Reduce losses 1003. Combined 1 and 2 50/50


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


Demo Site E1 Best Curves

• 3 best volt/var and volt/watt curves shown for each objective


Objective 1Objective 2Objective 3

Best Power Factor SettingObjective 1 2 3

power factor 0.92 0.99 0.93




PCC VVI 9.1787 7.4029 8.9498 6.8539Losses (kWh) 3079 3038 3078 3124



Obj 3

Obj 1

Obj 2

power factor does not reduce losses


Demo Site H1: Objectives & Metrics


1. Flatter voltage and improved customer efficiency

5050

2. Reduced LTC tap changes

100

3. Combined 1 and 2 25/25/50


Demo Site H1: Best Curves

• 1 best volt/var and volt/watt curves shown for each objective


Best Power Factor SettingObjective 1 2 3

power factor 0.92 0.96 0.96

Objective 1Objective 2Objective 3







Obj 3

Obj 1

Obj 2


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


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


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


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 !


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


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


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


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


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


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:


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


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


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


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


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


Volt/var 2: slower response


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


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


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


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


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


4 6 8 10 12 14 16 18 20-100

-80

-60

-40

-20

0

20

40

60

80

100



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

2014 pv distribution system modeling workshop: determining recommended settings for smart inverters:...

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