Alaska Wind Integration ConferenceJune 29, 2010

Oahu Wind Integration Study

Dean ArakawaSr. Engineer, Renewable Energy PlanningHawaiian Electric Company

2

The Challenge

3

Hawaii’s Economy in 2008

SPENDING ON ENERGY $ 8.4 BILLION

GROSS STATE PRODUCT $63.8 BILLION

4

Hawaii’s Energy Use Today

Primary energy: 90% fossil fuel, Imported crude oil refined:

ELECTRICITY 32%

JET FUEL 34%

GASOLINE/ 27%MARINE FUEL

OTHER 7%

5

Hawaii’s Electricity Issues are Fundamentally Different than

the Mainland USU.S. Electric Power Industry

Net Generation, 2008

Coal48%

Petroleum2%

Natural Gas21%

Nuclear20%

Hydroelectric Conventional

6%

Non-Hydro Renewables

3%

HECO, HELCO & MECONet Generation, 2008

Petroleum77%

Hydroelectric ConventionalLess than 1%

Coal15%

Non-Hydro Renewables

8%

6

The Solutions

7

A Paradigm Shift is Required

Economic drain > Economic engine Energy insecurity > Energy security Environmental harm > Environmental

compatibility Price volatility > Price stability

8

Where Are We Today?

As of 2009 – Hawaiian Electric companies19 % Renewable Energy & Energy Efficiency

(~50% / 50%)

State Goal by 2030 – for Hawaii’s economy40% Renewable Energy30% Energy Efficiency

9

How We Can Move Ahead:

Grid transformation Renewable energy including liquid

fuels substitute Inter-island connection

1010

Kauai

Oahu

Molokai

Lanai

Maui

Hawaii

Oahu’s Challenge

Solar

Wind Geothermal

MSW

Biomass/Biofuel

OTEC/Wave

DSM/Energy Efficiency

Population 905,601 *

Population173,057 *

Tri-islandpopulation141,783 *

* U.S. Censusestimates asof July 2007

1111

Hawaii’s Wind Energy Resources

1212

Wind on Molokai and Lanai

04/19/23

13

Renewable Game Plan for Hawaii

The load is on Oahu, but the renewable resource is limited.

The neighbor islands have abundant renewable resources, but limited load.

Ultimately, the islands can benefit by being cabled together.

14

How Can We Do It?

‘Interisland Wind’ Lanai & Molokai wind farms– 200 MW each– Undersea cable

to Oahu

Learn more at:www.interislandwind.com

15

HECO’s System

16

Hawaiian Electric

ISLAND PEAK DEMAND (2008)

OAHU* 1200 MW

MAUI 195 MW

HAWAII 200 MW

KAUAI served by separate utility co-op

* 80% of state population

Isolated, stand-alone grids

17

Big Wind Components

Successful Big Wind

Wind Plant Development &

Performance=

Required wind plant forecasting and performance characteristics

Resource intermittency mitigation and management (e.g. energy storage requirements)

Adequate capacity factor yielding commercially reasonable pricing

Community acceptance of large wind plants

Wind Plant Issues

Undersea Cable Intertie

+

Sizing and selection (AC, DC) Cable system reliability and configuration

(e.g. mono-pole, bi-pole, spare cable, etc.)

Landing sites and footprint for converter station and supporting equipment

Ocean permitting and environmental issues

O&M responsibilities and operating agreement

Cable Issues

Oahu Integration & Infrastructure

+

Oahu Issues Maintain 60Hz frequency and system stability Maintain adequate operating reserves in

response to wind Improve generator response Enhance system controls and automated

features Maintain reliable operations via PPA

commitments Community acceptance of new T&D

infrastructure

18

Generation Resources on Oahu

H-POWER (46 MW)

H-POWER (27 MW)

Waiau (473 MW)

Honolulu (108 MW)

Kahe (604 MW)

AES (180 MW)

Kalaeloa (208 MW)

Legend

Firm Capacity, Net-MW

CIP CT-1 (113 MW)

Future As-Available Resource, MW-nameplate

Kahuku Wind Power (30 MW)

Honua Power (6 MW)

Future Firm Capacity, Net-MW

Airport DSG (8 MW)

Total Existing Firm Capacity = 1,732 MW-net

Total Future Firm Capacity = 35 MW-net

Oahu RE RFP Pending

400 MW Wind Planned

19

Inter-island Wind Project

Scenario Analysis

(GE MAPS/PSLF)

HECO Baseline Information

HECO Model Development

GE

Wind Forecasting

Oahu Transmission StudiesStead State Load Flow/

Transient Stability/Short Circuit

Steam GeneratorImprovements

Load Control

Standby/Quick StartGeneration

EMS/AGC CapabilityAnalysis

Oahu T&D RoutingStudy and Engineering

Design

Submarine CableArchitecture andFunctional Specs

Wind ResourceModeling

PPA Negotiations/Interconnection

Requirements Study

Wind Capacity Calculation

Steam GeneratorProjects

EMS UpgradeProjects

Load ControlProjects

Future GeneratingResource Plan

Oahu TransmissionProjects

Submarine CableProcurement

and Permitting

Follow-on Implementation

20

Oahu600MW of new

Renewables~1200MW Peak

Lanai+200MW new

Wind

sub- sea cables

Molokai+200MW new Wind

+100MW new Wind+100MW new PV

100MW-400MW100MW“Big Wind”Oahu + Lanai only

Scenario #3

Scenario #5

Scenario #1

Baseline

Scenario

100MW

100MW

-

Oahu

Solar

---2014 Baseline

200MW200MW100MW“Big Wind”Oahu + Lanai +

Molokai

-

Molokai

WindTitle

100MW

Oahu

-

Lanai

“Big Wind”Oahu only

100MW-400MW100MW“Big Wind”Oahu + Lanai only

Scenario #3

Scenario #5

Scenario #1

Baseline

Scenario

100MW

100MW

-

Oahu

Solar

---2014 Baseline

200MW200MW100MW“Big Wind”Oahu + Lanai +

Molokai

-

Molokai

WindTitle

100MW

Oahu

-

Lanai

“Big Wind”Oahu only

Scenario Analysis

These 3 scenarios were analyzed to determine the

commitment/dispatch, identify new operating

characteristics, and establish a new baseline to assess strategies to enhance operation with

high penetrations of renewables

These four scenarios were the focus of the

study (Scenarios 2 and 4 were only moderately

different than these three scenarios).

Interest from the team to focus effort on

mitigating strategies as opposed to these

only moderately

21

-50 -40 -30 -20 -10 0 10 20 30 40 500

5

10

15

20

25

30

35

40

45

50

Farm power (MW per interval)

Fre

quency

(%

)

100MW Oahu + 200MW Lanai + 200MW Molokai

0.1% percentile (1min) = -12.27

0.1% percentile (5min) = -31.336

0.1% percentile (10min) = -49.305

Negative most (1min) = -22.479

Negative most (5min) = -54.9215

Negative most (10min) = -90.258

99.9% percentile (1min) = 11.7685

99.9% percentile (5min) = 33.0615

99.9% percentile (10min) = 54.0865

Positive most (1min) = 22.5425

Positive most (5min) = 65.0885

Positive most (10min) = 95.845

Interval = 1min

Interval = 5min

Interval = 10min

1 day1 min 1 hr 1 wk10 min1 sec

GovernorResponse

Governor Response Automatic

Generation Control

AGC Regulation Economic

DispatchEconomicDispatch

ArbitragePlanning

GovernorResponseInertiaInertia

Positive Sequence Load Flow (GE PSLFTM)

Interhour Renewables Variability AnalysisTM

Long-term Dynamic Simulations (AGC)TM

Multi-Area Production Simulation (GE MAPSTM)

GovernorResponseSupportVoltage

Statistical Wind Power Variability Assessments

-0.25 -0.2 -0.15 -0.1 -0.05 0 0.05 0.1 0.15 0.2 0.250

10

20

30

40

50

Power ramp (pu per interval)

Fre

quency

(%

)

0% percentile (10min) = -0.140% percentile (60min) = -0.450.1% percentile (10min) = -0.090.1% percentile (60min) = -0.27

99.9% percentile (10min) = 0.1099.9% percentile (60min) = 0.31100% percentile (10min) = 0.18100% percentile (60min) = 0.48

Interval = 10min

Interval = 60min

-150 -100 -50 0 50 100 1500

10

20

30

40

50

Power ramp (MW per interval)

Fre

quency

(%

)

0% percentile (10min) = -82.850% percentile (60min) = -269.050.1% percentile (10min) = -54.900.1% percentile (60min) = -163.16

99.9% percentile (10min) = 60.1199.9% percentile (60min) = 183.45100% percentile (10min) = 105.95100% percentile (60min) = 289.31

Interval = 10min

Interval = 60min

2008

-0.25 -0.2 -0.15 -0.1 -0.05 0 0.05 0.1 0.15 0.2 0.250

10

20

30

40

50

Power ramp (pu per interval)

Fre

quency

(%

)

0% percentile (10min) = -0.140% percentile (60min) = -0.450.1% percentile (10min) = -0.090.1% percentile (60min) = -0.27

99.9% percentile (10min) = 0.1099.9% percentile (60min) = 0.31100% percentile (10min) = 0.18100% percentile (60min) = 0.48

Interval = 10min

Interval = 60min

-150 -100 -50 0 50 100 1500

10

20

30

40

50

Power ramp (MW per interval)

Fre

quency

(%

)

0% percentile (10min) = -82.850% percentile (60min) = -269.050.1% percentile (10min) = -54.900.1% percentile (60min) = -163.16

99.9% percentile (10min) = 60.1199.9% percentile (60min) = 183.45100% percentile (10min) = 105.95100% percentile (60min) = 289.31

Interval = 10min

Interval = 60min

2008

New tools and data needed to properly model and assess system impacts

within operational time constraints.

Tools Needed For Each Timescale

22

Modeling Tools

Quantify frequency performance during wind/solar variability events and wind ramp events…

• Reserve requirements• Types of regulating units,• Benefit of increasing ramp

rates

1sec results for one 1hr

Frequency analysis, including governors and AGC response.

Initialized from MAPS and driven by major wind/solar

events.

Long-termDynamic Simulations(Auto Gen Control)

Quantify reserve violations, fast starts & load shed events caused by sub-hourly wind/solar/load changes…

• Assess reserve requirements• Assess fast-start events• Select windows for further

analysis

10min results for 1yr

Sub-hourly wind/solar/load changes with respect to

reserve, based on commitment and dispatch.

Inter-hourVariability Analysis

Quantify energy production, variable cost, wind power curtailment, emissions, etc for each scenario to assess…

• Wind/solar delivered• Unit commitment• Variable cost • Emissions, etc

Hourly results for 1yr

Unit commitment/ dispatch, representing operating rules, benchmarked against system

operation.

Multi-AreaProduction Simulation

(GE MAPS)

Quantify system stability performance during contingencies…

• Wind/solar plant requirements (freq control, LVRT, voltage control)

• System contingencies•Generator trip•Load rejection•Other

Full Transmission model for voltage & stability

performance, governor response, contingency

analysis.

1ms results for 1min

Positive SequenceLoad Flow(GE PSLF)

Quantify frequency performance during wind/solar variability events and wind ramp events…

• Reserve requirements• Types of regulating units,• Benefit of increasing ramp

rates

1sec results for one 1hr

Frequency analysis, including governors and AGC response.

Initialized from MAPS and driven by major wind/solar

events.

Long-termDynamic Simulations(Auto Gen Control)

Quantify reserve violations, fast starts & load shed events caused by sub-hourly wind/solar/load changes…

• Assess reserve requirements• Assess fast-start events• Select windows for further

analysis

10min results for 1yr

Sub-hourly wind/solar/load changes with respect to

reserve, based on commitment and dispatch.

Inter-hourVariability Analysis

Quantify energy production, variable cost, wind power curtailment, emissions, etc for each scenario to assess…

• Wind/solar delivered• Unit commitment• Variable cost • Emissions, etc

Hourly results for 1yr

Unit commitment/ dispatch, representing operating rules, benchmarked against system

operation.

Multi-AreaProduction Simulation

(GE MAPS)

Quantify system stability performance during contingencies…

• Wind/solar plant requirements (freq control, LVRT, voltage control)

• System contingencies•Generator trip•Load rejection•Other

Full Transmission model for voltage & stability

performance, governor response, contingency

analysis.

1ms results for 1min

Positive SequenceLoad Flow(GE PSLF)

-50 -40 -30 -20 -10 0 10 20 30 40 500

5

10

15

20

25

30

35

40

45

50

Farm power (MW per interval)

Frequency

(%

)

100MW Oahu + 200MW Lanai + 200MW Molokai

0.1% percentile (1min) = -12.270.1% percentile (5min) = -31.3360.1% percentile (10min) = -49.305Negative most (1min) = -22.479Negative most (5min) = -54.9215Negative most (10min) = -90.258

99.9% percentile (1min) = 11.768599.9% percentile (5min) = 33.061599.9% percentile (10min) = 54.0865Positive most (1min) = 22.5425Positive most (5min) = 65.0885Positive most (10min) = 95.845

Interval = 1min

Interval = 5min

Interval = 10min

-50 -40 -30 -20 -10 0 10 20 30 40 500

5

10

15

20

25

30

35

40

45

50

-50 -40 -30 -20 -10 0 10 20 30 40 500

5

10

15

20

25

30

35

40

45

50

Farm power (MW per interval)

Frequency

(%

)

100MW Oahu + 200MW Lanai + 200MW Molokai

0.1% percentile (1min) = -12.270.1% percentile (5min) = -31.3360.1% percentile (10min) = -49.305Negative most (1min) = -22.479Negative most (5min) = -54.9215Negative most (10min) = -90.258

99.9% percentile (1min) = 11.768599.9% percentile (5min) = 33.061599.9% percentile (10min) = 54.0865Positive most (1min) = 22.5425Positive most (5min) = 65.0885Positive most (10min) = 95.845

Interval = 1min

Interval = 5min

Interval = 10min

23

Wind and Solar Data Development

Wind and solar data monitoring units Develop high resolution wind and solar

time series data for modeling work

24

Model Data RequirementsSummary of Thermal Unit

25

• Wind energy curtailment at high penetrations•Zero marginal cost energy not being accepted

• More frequent operation of thermal units at minimum power•What if there is a loss of load on the system?

• Large system contingencies•What if the undersea cable trips?

• Variability of wind energy•Large sustained drops in wind/solar power during

load rises• Reduced thermal unit efficiency & potentially

higher O&M costs•Higher sub-hourly maneuvering to balance

wind/solar power

Integration Challenges …

26

• Wind power forecasting to improve unit commitment

• Refine up reserve requirements based on wind power variability

• Reduce minimum power of baseload units• Seasonally cycle-off select baseload units• Reduce reserve requirement (use of fast-start

units and load control)• Increase thermal unit ramp rate capability• Consider advanced wind turbine technologies to

provide “grid support” (e.g., inertia, over-frequency control)

Evaluating Candidate Strategies

2727

Dynamic Response Study

Improving the dynamic responses of generating units on the HECO grid will facilitate the interconnection of greater amounts of variable generation with reduced amounts of other technologies to mitigate adverse operational impacts.

PREMISE

2828

Objectives1. Confirm I&C logic for “AGC” of governors

2. Characterize existing inertial, droop, and AGC (i.e., “ramp rate”) responses

3. Develop control strategies and tune systems for improved response (model input)

4. Identify factors and equipment that limit unit response

5. Identify capital projects to address limitations

2929

Pre-Tuning Uninhibited Boiler Following Response Trend

Combustion Control at Combustion Control at Top LoadTop Load

3030

Post-Tuning Uninhibited Boiler Following Response Trend

3131

Post-Tuning 3 MW/min Coordinated Control Response Trend

3232

5 MW/min Response Trend

3333

System Load/Frequency Response to 125 MW Kahe 5 Trip

(3-14-2009, 20 min response)Theo W. Hetherington – C.S.Squared

3434

DYNAMIC RESPONSE – GENERATING UNITSFor Analytical Purposes Only

Projected Projected DroopUnit ODOM "Everyday" "Once-in-While" (governor)

  (MW/min) (MW/min) (MW/min) (%)H8 1.4 3.0 5.0 5.0H9 1.4 3.0 5.0 5.0W3 0.9 2.5 4.0 5.0W4 0.5 2.5 4.0 5.0W5 1.4 3.0 5.0 5.0W6 1.4 3.0 5.0 5.0W7 2.3 5.0 7.0 5.0W8 2.3 5.0 7.0 5.0W9 3.0 5.0 10.0 5.0W10 3.0 5.0 10.0 5.0K1 2.3 5.0 7.0 5.0K2 2.3 5.0 7.0 5.0K3 2.3 5.0 7.0 5.0K4 2.3 5.0 7.0 5.0K5 2.5 7.0 10.0 5.0K6 2.5 6.0 8.0 5.0

CIP CT-1 na 10.0 13.0 5.0H-Power 2.0 1.8 2.0 5.0

KPLP 2.5 5.0

AES 2.5 5.0

35

Impact of Renewables Variabilityon System Frequency

Higher thermal unit ramp rates helped manage frequency

Large and fast-wind power variability over the 5-

10min timeframe in both directions

Largest wind forecast error. Largest hourly wind drop

(311MW; 27% of gen.)All fast-start units dispatched

Fast Wind Power VariabilityAug 30th 10am (995MW Load)

Sustained Wind Power DropOct 12th 2pm (1160MW Load)

Manageable system frequency over fast wind

variability events

Manageable system frequency over largest

wind dropGE Internal – HECO Proprietary

36

0 600 1200 1800 2400 3000 360059.4

59.6

59.8

60

60.2

s

Hz

Frequency

0 600 1200 1800 2400 3000 360059.4

59.6

59.8

60

60.2

s

Hz

Frequency

0 600 1200 1800 2400 3000 36000

20

40

60

80

100

120

s

MW

Lanai 200 MWMolokai 200 MWOahu1 50 MWOahu2 50 MWCentralized PV 60 MWCentralized PV 20 MWCentralized PV 5 MWResidential PV 15 MW

MW

200MW Lanai(curve on top of one

another)

Thermal Unit Ramp Rates & Droop

Today’s Ramp Rate / Droop

Propose Future Ramp Rate / Droop

UFLS at 59.5 Hz

Large Wind/Solar/Load ChangeAug 30th 10am (1108MW Load)

37

Results

38

Operational Strategies andUnit Modifications

More Wind Energy Delivered & Lower Variable Cost

Benefits from…• Operational Strategies Wind forecasting & refine up

reserve requirement• Thermal Unit Modifications Reduce unit min power &

seasonally cycle off baseload units• Modifying Reserve Req’ts Credit load control & fast-start

units for up reserve

39

What Worked Well for HECO

Dedicated cross-functional team Technical Review Committee Weekly meetings during scenario

analysis Selected the most difficult scenario

first Prudent use of modeling results

40

Hawaii’s Energy Futurewww.hawaiisenergyfuture.com

Hawaiian Electric Companywww.heco.com

Hawaii Clean Energy Initiative http:/hawaii.gov/gov/initiatives/2009/energy

Hawaii energy datahttp://hawaii.gov/dbedt/info/energy

Thank You

Learn more ….

41

BACK UP

4242

Oahu Generating FleetOahu Generating Fleet

Unit Capability TypeOperating

ModeService

Date Age

Honolulu 8 56 Steam, Non-Reheat Cycling 1954 55Honolulu 9 57 Steam, Non-Reheat Cycling 1957 52Waiau 3 49 Steam, Non-Reheat Cycling 1947 62Waiau 4 49 Steam, Non-Reheat Cycling 1950 59Waiau 5 57 Steam, Non-Reheat Cycling 1959 50Waiau 6 56 Steam, Non-Reheat Cycling 1961 48Waiau 7 92 Steam, Reheat Base 1966 43Waiau 8 94 Steam, Reheat Base 1968 41Waiau 9 53 Combustion Turbine Peaking 1973 36Waiau 10 54 Combustion Turbine Peaking 1973 36Kahe 1 92 Steam, Reheat Base 1963 46Kahe 2 89 Steam, Reheat Base 1964 45Kahe 3 92 Steam, Reheat Base 1970 39Kahe 4 93 Steam, Reheat Base 1972 37Kahe 5 142 Steam, Reheat Base 1974 35Kahe 6 142 Steam, Reheat Base 1981 28

HPOWER 46 Steam, Non-Reheat Base 1990 19Kalaeloa 208 Combined Cycle Base 1991 18AES 180 Steam, Reheat Base 1992 17

Major Independent Power Producers

HECO Generating Units

43

How is frequency performance affected by installed wind power and scenario

assumptions? New RR and Droops

0

0.005

0.01

0.015

0.02

0.025

0.03

fIRMS fIRMS20 fIRMS5 fIRMS1

Fre

qu

ency

RM

S (

Hz)

Sc1

Sc3b

Sc3f3

Sc5b_FS

Sc5f3_FS

No solar variability, No AES governor response PSLF

Wind Power Variability

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

RMS20 RMS5 RMS1

Scenario

MW

Sc1

Sc3

Sc5

Input Data

• Good correlation between increased wind power variability and associated frequency performance

• 3B and 5B scenarios have better frequency performance than 3F3 and 5F3 scenarios. This is because fewer units are against their limits (more up regulation in 3B and 5B as compared to 3F3 and 5F3).

Proposed Ramp Rates & DroopsWind Power Variability

44

Maneuvering of HECO units w.r.t. total system variability

0.50

0.60

0.70

0.80

0.90

1.00

RMS20 RMS5 RMS1

Po

wer

Ou

tpu

t R

MS

w.r

.t.

tota

l va

riab

ilit

y

Sc 1

Sc 3b

Sc 3f3

Sc 5b

Sc 5f3

How much does maneuvering of HECO units increase in scenarios with more wind power?

Maneuvering of HECO units doubled in scenarios with offshore wind for slow and fast variations

Proposed AGC ramp-rates, no solar variability, no AES governor response

Maneuvering of HECO units w.r.t scenario 1

0.0

0.5

1.0

1.5

2.0

2.5

RMS20 RMS5 RMS1

Po

we

r O

utp

ut

RM

S w

.r.t

. Sc

1

Sc 1

Sc 3b

Sc 3f3

Sc 5b

Sc 5f3

• A high percentage of total system variability (>80%) is counteracted by HECO units in all scenarios and for fast and slow variations.

• System variability is higher if solar variability is considered. HECO units perform most of the maneuvering.

45

What units increase maneuvering in scenarios with more wind power?

Variability of HECO units increased to counteract additional wind power variability in scenarios 3 and 5

AES

0

0.5

1

1.5

2

2.5

RMS20 RMS5 RMS1

Po

wer

Ou

tpu

t R

MS

(M

W)

Sc1

Sc3b

Sc3f3

Sc5b_FS

Sc5f3_FS

KALAELOA CT1

0

0.5

1

1.5

2

2.5

RMS20 RMS5 RMS1

Po

wer

Ou

tpu

t R

MS

(M

W)

Sc1

Sc3b

Sc3f3

Sc5b_FS

Sc5f3_FS

KAHE 6

0

0.5

1

1.5

2

2.5

RMS20 RMS5 RMS1

Po

wer

Ou

tpu

t R

MS

(M

W)

Sc1

Sc3b

Sc3f3

Sc5b_FS

Sc5f3_FS

KAHE 4

0

0.5

1

1.5

2

2.5

RMS20 RMS5 RMS1

Po

wer

Ou

tpu

t R

MS

(M

W)

Sc1

Sc3b

Sc3f3

Sc5b_FS

Sc5f3_FS

Proposed AGC ramp-rates, no solar variability, no AES governor response PSLF