Managing the Winds of Change – California Experiences

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Managing the Winds of Change California Experiences

Dora Nakafuji

University of Hawaii

September 17, 2009

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World Perspective – We’re not alone!

• Reduce and mitigate climate change impacts (pollution, GHG)

• Strengthen energy security by reducing dependence on oil

• Eliminate fuel poverty by diversifying with environmentally-friendly resources

• Support economic growth & competitiveness

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Solano 65 MW

Altamont Pass 562 MW

Tehachapi Ranges 710 MW

San Gorgonio 359 MW

Orange 36 MW San Diego

4 MW

Pacheco Pass 16 MW

Solano 65 MW

Altamont Pass 562 MW

Tehachapi Ranges 710 MW

San Gorgonio 359 MW

Orange 36 MW San Diego

4 MW

Pacheco Pass 16 MW

Overview

• Answers to TEST at end of seminar

• Policies Drivers & Integration Challenges

• Where we are Today – Wind Resources– Research & Support

Efforts– Statewide Integration &

Planning

• 2020 and Beyond?

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*2005

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Renewable Integration TEST Questions

• What will the future electricity system look like and where will renewable resources likely to come from –remote locations, out-of-state?– How do we currently get electricity today, tomorrow, future?

• What is needed for the grid to accommodate renewables (technologies/infrastructure, market, regulation)?– What are the drivers and challenges for integration?

• What are the impacts of increasing renewable energy penetration on system reliability and dispatchability?– Why all the fuss about integration?

• Will the “planned” system last another 30-40 years?– Why is the life span for wind generators, PV systems etc?

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Renewable Portfolio Standards

• 28 states have different mandatory RPS (portfolios mix of resources)

• Combination of new Energy Efficiency or Renewable Energy resources

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Renewable Energy & Climate Change Policies

• A flexible, market-driven policy to ensure that a certain amount of renewable energy is included in the portfolio of electricity resources serving a state or country

• Ensures that renewable energy technologies (i.e. solar, wind) and the public benefits of these clean technologies be recognized as cost-effective and competitive in the electricity markets.

Key Renewable Energy Policy Impacting California

Accelerated RPS(from IEPR / EAP /

SB1250/107Governor’s Response)

California Solar Initiative

2010 20202016

Governor’s GHG Reduction Targets &

AB32

Specific GHG reduction targets allocated to RE will most likely be contained in the Climate Action Team Recommendations to the Governor, expected in 2006.

State Bioenergy Goal(Executive Order S-06-06)

Renewables 33% of generation

(~98,000 GWh)

40% biofuels produced in California

3,000 MW of new solar (~5,000 GWh 1)


20% of RPS from biopower(~20,000 GWh1)


(~54,000 GWh)


Key Renewable Energy Policy Impacting California

Accelerated RPS(from IEPR / EAP /

SB1250/107Governor’s Response)

California Solar Initiative

2010 20202016

Governor’s GHG Reduction Targets &

AB32

Specific GHG reduction targets allocated to RE will most likely be contained in the Climate Action Team Recommendations to the Governor, expected in 2006.

State Bioenergy Goal(Executive Order S-06-06)


(~98,000 GWh)


3,000 MW of new solar (~5,000 GWh 1)




(~54,000 GWh)


• Helps put the electricity industry on a path toward increasing sustainability.

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CA RPS Eligible Technologies

• Biomass

• Biodiesel

• Conduit hydro

• Fuel cells using renewable fuel

• Digester gas

• Geothermal

• Landfill gas

• Municipal solid waste conversion

• Ocean wave, ocean thermal, tidal current

• Photovoltaic

• Small hydro

• Solar thermal electric

• Wind

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Great so what’s the problem?

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A Critical Question

Facts of Life:

How do we accommodate a large amount of renewable energy resources onto our power system without sacrificing reliability?

• Mandated Renewable Portfolio Standard (wind, geothermal, biomass, etc)

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Ex. California RPS Projections

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Projected Renewables to Meet California Policy Goals

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Data Sources: 2004, CEC Electricity Report which includes all renewables in the State, not just IOUs; 2010 and 2020, PIER Renewables Projections.

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Ex. Technology – Lay of the Land

• Comprised of multiple utility service areas

• Mix of generation resources (base, peak, intermediate & intermittent)

• More than 124,000 miles of (T&D) power lines with over 2000 substations

• Supplies over 294 billion kilowatt-hours per year to 35 million Californians

• Electricity generation of over 61,000 MW supply electricity into California’s grid

• 30% imported from out of state across high voltage DC lines

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Components of the Grid

The electricity system is a blend of hardware, market competitive and regulated components��

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Physical constraints

RECs

Power purchase agreements Transmission access

agreements

Emission penalties

Power purchase agreements

Storage or other regulation services

Energy efficiency (PV, DG, DER)

Process constraints

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Integration Challenges

• Constrained and insufficient transmission and distribution (T&D) infrastructure

• Limited peak generating capacity and flexible units

• Lack of operating experience at high renewable penetration levels

• Abundant in-state renewable resources and aggressive policy for growth, but lacking a “game plan” (RPS) to help prioritize development

• Lack of integrated system

• Aging workforce & infrastructure!!!

*Source: EIA

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A Critical Question

Facts of Life:



• Wind, geothermal, biomass…resources have different generation characteristics

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Geographic & Seasonal Variability of Wind

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Managing the Electrical Grid

• Decisions are based on a set of conditions– Dispatch of energy is based on existing system

and market signals conditions (demand) determines dispatch, expertise determines resources committed and response

– Desired resource response is deterministic – ON or OFF

– If resources do not respond or are insufficient…alternatives are dispatched

• Wind and solar add additional variability to the set of conditions used in informing decisions

• System operators don’t have a “read” on the prevailing conditions to adequately forecast wind and solar

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* Typical Summer Month

Typical Summer Demand with Wind & Solar Gen. Profiles

Average System LoadAverage WindAverage Solar

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Averaged WindGeneration Curve

Averaged SolarGeneration Curve Source: IAP CEC/PIER

Both wind and solar face intermittency challenges

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Typical Output P

rofile for Different G

enerators

1.5

1.7

1.9

2.1

2.3

2.5

2.7

2.9

3.1

3.3

3.5

15:56:01

15:57:25

15:58:50

16:00:19

16:03:17

16:04:49

16:07:40

16:09:13

16:10:35

16:12:00

16:13:33

16:14:58

16:16:30

16:17:51

16:19:16

16:20:48

16:22:17

16:23:46

16:25:07

16:26:31

16:27:54

Power (MW)

Time

Peaker

Base G

enerationInterm

ittent (Wind)

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A Critical Question

Facts of Life:




• Current power systems were not designed to operate with large amounts of differing and variable renewable resources

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Demand Is Met with Different Generating Unit Types

Midnight Midnight

MW

Baseload

Cycling

12 noon

MW

Use cycling units

Typical Daily Demand ProfileUse peaking units

Use the most efficient, lowest cost baseload units

Source: HECO IRP

* Intermittent (wind & solar) resources?

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* Typical Summer Month

0

10000

20000

30000

40000

50000

60000

1 25 49 73 97 121 145

Hour

Gen

erat

ion

(MW

)

IMPORTS

HYDRO

PSH

WIND

SOLAR PV

SOLAR CON.

GAS TURBINE

COMB. CYCLE

STEAM

BIOMASS

GEOTHERMAL

NUCLEAR

PLANNED OPS

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5000

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(MW

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PSH

WIND

SOLAR PV

SOLAR CON.

GAS TURBINE

COMB. CYCLE

STEAM

BIOMASS

GEOTHERMAL

NUCLEAR

ACTUAL OPS

Managing the Mix

• Always striking a balance between changing demand and supply (temporal and locational variant)

• CA loading order requires energy efficiency, renewables, clean NG

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Ideal Situation

Midnight Midnight

MW

12 noonMidnight Midnight

MW

12 noon

Min & Max output of base (firm) generating units

Output of intermittent(as available)

units

Supply Meets Demand

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Problems Encountered

Midnight Midnight

MW

12 noonMidnight Midnight

MW

12 noon

Min & Max output of base (firm) generating units

Output of intermittent(as available)

units

Excess Energy –curtailed or dumped WE PAY FOR

Supply exceeds Demand at minimum load

Supply does not meet demand at maximum load

Costly Energy –procured, WE PAY FOR THIS

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Wind Ramps and Impacts on Other Generation

0

500

1000

1500

2000

2500

3000

3500

1 25 49 73 97 121 145

Hours

Ram

p R

ate

Do

wn

Cap

acity

(M

W/m

in) PSH

GAS TURBINE

STEAM

COMB. CYCLE

HYDRO

• Wind (or solar) ramping down

• If available - stand-by or reactive units must ramp up to continue to meet demand

Wind drop off over 15 minutes

Flexible unit started to fill gap

CA ramping using available hydro-power

(200MW/min limit*)* Source: HI & CEC

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A Critical Question

Facts of Life:




• Current power systems were not designed to operate with large amounts of differing and variable renewable resources

• When ANY resource is not carefully integrated (planned) onto the power system, the system will be more prone to failures

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Managing the Mix

• Striking a balance between changing demand and supply

• Do it at the least cost

• Do it without sacrificing reliability

• Do it so it can be sustained

SupplyDemand =

�∞

+=0

pplyVariableSuSupplyDemandEmerging Paradigm

Current Paradigm

2010 Load Duration Curve

310000

15000

20000

25000

30000

35000

40000

45000

50000

55000

0 2630 5260 7890 10520 13150 15780 18410 21040 23670 26300

HoursM

W

CAISO load, actual, MW2010X Total Actual L-W-S2010T Total Actual L-W-S

A1

A2

A3A1

A4

A5

A

A A8A1

A9

A11

A12

A13

A14

B1B4

B2

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B5G3

B6

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C1G10G11

C2I2

C3G8I3J2

C4

D1

D2

F1

F2G1

G2G5

G G7G9

HH2

I1

B#1 B#2 B#3 B#4 B#5 B#6 B#7 B#8 B#9 B#10

July 21, 20036-9AM

July 1, 20026-9AM

May 3. 20044-7AM

May 3. 20048-11 PM

February 16, 2004

00-2AM

July 19, 20046-9AM QSS

May 15. 20031-4 AM QSS

June 24, 20044-7PM QSS

* Known system stress conditions

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Unit Com m itm entand

D ay-Ahead Scheduling

Load Follow ing(5 M inute D ispatch)

Frequency and T ie-Line Regulation

(AG C)

D ay-ahead and M ulti-Day

Forecasting

Fast

er (s

econ

ds)

Ti

me

Fram

e

Slo

wer

(Yea

rs)

O peration Process Issues

Hour-Ahead Forecasting

and Plant Active Pow er M aneuvering and

M anagem ent

Resource andC apacity Planning

(Reliab ility)

Unit Dispatch

0

100

200

300

400

500

600

700

0 2000 4000 6000 8000

Hour

MW

Real-Tim e and Autonom ous Protection and Control Functions

(AG C, LVRT, PSS, G overnor, V -R eg, etc.)

C apacity Valuation(UC AP, IC AP)

andLong-Term Load

G row th Forecasting

2001 Average Load vs Average W ind

0

5,000

10,000

15,000

20,000

25,000

30,000

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Managing the Risks – New Markets & Infrastructure

Mixed Renewables &

Clean Coal

Wind

Wind

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Wind

WindWind

WindSolar

WindGeo

Geo

Wind

Hydro

WindHydro

HydroGeo

WindGeo

Solar

Solar

Wind

Wind

in state Bio/PV

• Traditional processes no longer adequate – new modeling tools and technology specific information now needed

• Increasing reliance on out-of-state and out-of-region renewable resources makes CA dependent on conditions of that state or region (e.g., extended drought or storm conditions)

• Planning and forecasting capability must now include consideration of climate impactson the combined output of all weather dependent resources -wind, solar, hydro versus only a single resource

WindSolarLOTS OF UNKNOWNS &

UNCERTAINTIES

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Timing & Economic Analysis

0

0.01

0.02

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2005 2007 2009 2011 2013 2015 2017Year

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Three Pulls – Technology, Market, Policy/Regulatory

Technology

MarketPolicy

• Characterize renewable resources

• Limitations of transmission infrastructure

• Mix of generation resources• Age and lifespan of existing

technology• Understanding of new technology• Fit of new technology to existing

infrastructure

• Renewables incentives• Cost and demand for new

technology• Cost-benefit of new technology• Utility structure (deregulated or

vertical)• Green energy service credit for

renewables

• Local state & national energy policy & regulatory environment

• Power purchase agreements limits, terms and conditions

• FERC & national policy• Other standards – Environmental,

air quality, energy efficiency

Significant Need and Potential to help build a resilient Future System

Not an overnight process

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Why should WE care? Can we make a difference?

Signs

Current Impacts

Future Impacts

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Today’s Challenges!

Vestas V90, 3 MW80m tower, 90m rotor

V90 Largest land based wind turbine to date

B747, 60m wing span

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Tomorrow’s Designs

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Increased Data Quality & Confidence

• Refines wind resource locations and new development potential

• Identifies additional land area for wind development

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Strategic Assessment Approach

• Identifies key focus locations for development

• Considers development timeframeand economics for maximum public benefits– Transmission– Environmental– Other non-energy benefits

• Prioritizes renewable and transmission build-out

• Integrate solutions for planning needs

Resource Assessment

Technical Potential

Economic Potential

Transmission Impact

Other Benefits

Prioritized Results

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Wind Resource Assessment

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Los Angeles – Kern Pardee – Vincent2376 MWGenCost: $2376MTrans Cost: $843 M

San Diego – Miguel600 MWGenCost: $600 MTrans Cost: $162 M

Solano Vaca-Dixon100 MWGenCost: $100 MTrans Cost: $140 M San Bernardino

Etiwanda280 MWGenCost: $280 MTrans Cost: $34 M

Imperial82 MW

Solano Vaca-Dixon-Contra Costa275 MWGenCost: $275 M

AlamedaContra Costa – Tesla132 MWGenCost: $132 M

Los Angeles – Kern Tehachapi500 MWGenCost: $500 M

Riverside1416 MWGenCost: $1416 M

San Diego Glencliff - Los Coches150 MWGenCost: $150 M

Los Angeles – Kern Pardee – Vincent2376 MWGenCost: $2376MTrans Cost: $843 M

San Diego – Miguel600 MWGenCost: $600 MTrans Cost: $162 M

Solano Vaca-Dixon100 MWGenCost: $100 MTrans Cost: $140 M San Bernardino

Etiwanda280 MWGenCost: $280 MTrans Cost: $34 M

Imperial82 MW

Solano Vaca-Dixon-Contra Costa275 MWGenCost: $275 M

AlamedaContra Costa – Tesla132 MWGenCost: $132 M

Los Angeles – Kern Tehachapi500 MWGenCost: $500 M

Riverside1416 MWGenCost: $1416 M

San Diego Glencliff - Los Coches150 MWGenCost: $150 M

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Sodar & Tall Tower Monitoring

• Responds to industry’s need to acquire accurate, upper atmospheric wind data within the operating regime of current wind turbine technologies

• Enables wind data to be remotely measured at elevations of 50m to 200m –typical heights of new turbine technologies

• Reduces development risk at new sites with wind data substantiated by tall tower and SODAR measurements

• Improves wind plant power prediction for energy generation and wind energy forecasting

• Industry participation: Calpine, Oakcreek, Enxco

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Improving Wind Forecasting Capabilities

• Conduct research to help identify and reduce sources of wind forecasting error

• Efforts have identified need for coupling field monitoring with modeled wind forecasts to increase accuracy especially during summer seasons where local terrain and thermal heating drive the winds

• Effort under DOE engages with the industry to develop and deploy the Wind SENSEforecasting capability into the control room and enable better integration of intermittent renewables

Photo of Altamont Pass by Steve Deutsch, 2003

- Previous research funded by PIER, CEC- New Wind SENSE effort funded by DOE

Continue to narrow gap between observed and predicted power.

Continue to narrow gap between observed and predicted power.

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WindSENSE Project Link Forecasts with Operations

• Objectives– Build and enhance California wind

forecasting efforts to improve adoption and use of optimal wind forecasting capability

– Improve short-term wind energy modeling capabilities with optimally located remote sensor networks (i.e. met towers, SODAR, doppler) providing a 3-D area “sense”

– Develop key indicators based on control room organizational knowledge to inform the design for an integrated forecasting interface

Goal: Develop Wind SENSE to provide control room operators an awareness or “sense” of the wind conditions and energy forecasts in their native operating environments

* DOE funded

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Transform Statistics to Actions

• Development of a web-portal to access information tracking, trending and monitoring wind development in California

• Address CA driven issues from avian, community lighting impacts, off shore deep water and land use concerns

• Transform Analysis to actionable information for sitingneeds

Example of industry avian observation data linking their behavior to terrain and ground cover. Results translate in locations where wind turbines may be re-sited to have less impact on birds in the area.

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Funded by CEC/PIERhttps://eed.llnl.gov/renewable/

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Help Bridge the Gaps between Climate Prediction and Electricity Industry

• Translate the potential impact on wind, solar and hydro generationgresources due to climate change

• Key Objectives:– Bring climate change considerations to the

forefront of utility planning and longer-term electricity infrastructure planning

– Work with industry to determine what information is needed (i.e. resolution, type) and how to best utilize climate change results to assess impacts on future planning and validation needs

*Research funded by CEC/PIER

Bringing Different Perspectives Together

0

500

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2000

2500

3000

3500

1 25 49 73 97 121 145

Hours

Ram

p R

ate

Do

wn

Cap

acity

(M

W/m

in) PSH

GAS TURBINE

STEAM

COMB. CYCLE

HYDRO

0

500

1000

1500

2000

2500

3000

3500

1 25 49 73 97 121 145

Hours

Ram

p R

ate

Do

wn

Cap

acity

(M

W/m

in) PSH

GAS TURBINE

STEAM

COMB. CYCLE

HYDRO

Source: CEC - IAP

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Looking at System Solutions

Leveraging CA-based expertise to developing industry decision tools/aids

Engineering and advance computational capability to convert Data (science) to Knowledge (to deployment)

Some Wind Industry Challenges in CA:• Climate change uncertainties, • Intermittency and integration issues,• Long-term RPS siting and planning• Improved turbine performance and site-tailored designs

Data to Knowledge Conversion Process

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Developing New Technologies

Control Surface

Translational Tab

Conventional Control Proposed Control

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Patent # 7,028,954 B2

• Homogeneous charge compression ignition (HCCI) technology

• Joint industry testing of new low emission, high efficient engine for flex-fuels

• Flexible fuels from bio-diesel, ethanol or other synthetic fuels

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Points to Consider

• Aging infrastructure – sensors and monitoring programs, new materials, technology

• Workforce and transition management –training, simulations, knowledge extraction

• Secure & reliable environment for a commoditize critical infrastructure – modeling of all levels

• Un-intended consequences (land use, water, infrastructure)

Lots of Opportunities Need to develop new workforce & new technologies=

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Making a Difference

• What will the future electricity system look like and where will renewable resources likely to come from – remote locations, out-of-state?

• What are the impacts of increasing renewable energy penetration on system reliability and dispatchability?

• UNINTENDED CONSEQUENCES:How will our landscape (land use, water use, waste management) change as we accommodate renewables?

• Will the “planned” system last another 30-40 years?

• Will we change or environment as we change?

Wind resource opportunities

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References

• State incentives and news – http://www.dsireusa.org/

• Global & Climate news and renewables– http://www.pewclimate.org/what_s_being_done/in_the_states/rps.cfm

• California renewable resource information– http://energy.ca.gov

• Other states– Texas: http://www.seco.cpa.state.tx.us/re_rps-portfolio.htm– New York: http://www.dps.state.ny.us/03e0188.htm– Hawaii: http://www.pewclimate.org/node/6695

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Questions/Comments??

Contact Info:

Dora Nakafuji

Director of Renewable Energy [email protected]

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Managing the Winds of Change – California Experiences

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