LCOEs and Renewables€¦ · 25/07/2013 · Victor Niemeyer . Program Manager, Energy and...

Victor Niemeyer Program Manager, Energy and Environmental Policy Analysis and

Company Strategy Program

EIA LCOE/LACE Workshop July 25, 2013

LCOEs and Renewables

2 © 2013 Electric Power Research Institute, Inc. All rights reserved.

EPRI Generation Options Report Provides Excellent Example of LCOE Use

By Robin Bedillion of EPRI’s Strategic Energy Analysis Group

Reference: EPRI Report 1026656

(free from EPRI.com, search for “1026656”)


Levelized Cost of Electricity Analysis – Objectives

• Utilize EPRI capital cost data and methodologies to calculate levelized costs of electricity (LCOEs) in constant 2011 $ – Incorporate key assumptions needed for calculations – capital cost,

fuel cost, fixed and variable O&M, fuel type and energy content, capacity factor, cost of money

• Provide a generic basis for comparison of technologies for baseload and renewable generation

• Evaluate sensitivities of LCOE to potential CO2 costs and other parameters


Magnitude of Cost Estimates* can be Very Different Site Specific vs. Generic Constant $, Current $

* Data shown for illustrative purposes only


Levelized Cost of Electricity Analysis – Assumptions • All baseload technologies are assumed to have an 80%

capacity factor, except for nuclear which has a 90% capacity factor.

• Non-dispatchable renewables assume a range of capacity factors based on a range of resource availability assumptions.

• No production or investment tax credits assumed for any technologies.

• No integration costs (e.g. costs associated with additional reserves, balancing, conventional generation cycling, etc.) included for non-dispatchable technologies.


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Cost of CO2, $/metric ton

Pulverized Coal (PC) – 2015

0.84 metric tons CO2/MWh x $100/tonne = +$84/MWh

All-in Capital Costs: $2,400-2,875/kW

Fuel Costs: $2-3/MMBtu

All costs are in constant Dec 2011$

LCOE is shown for high level comparison purposes. Actual plant investment decisions are affected by a number of other project specific considerations and caution should be used when comparing technologies based on LCOE. See Appendix A of report 1026656 for more details.


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PC, IGCC, NGCC Comparison – 2015

IGCC

PC

NGCC




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Biomass – 2015

*Biomass emissions can vary significantly based on fuel source and life-cycle emission assumptions. Conventionally, the release of carbon from biogenic sources is assumed to be balanced by the uptake of carbon when the feedstock is grown, resulting in zero net CO2 emissions over some period of time.

No investment or production tax credits are assumed. CO2 emissions are assumed to be neutral*.


Fuel Costs: $2-6/MMBtu




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Wind – 2015

No investment or production tax credits are assumed.


Onshore Wind


Capacity Factor: 28-40%

Offshore Wind

All-in Capital Costs : $3,250-5,225/kW




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Solar Photovoltaic (PV) – 2015

No investment or production tax credits are assumed.






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PC

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Nuclear

Biomass

Geothermal

Comparative Levelized Costs of Electricity of Dispatchable Technologies – 2015


Average LCOE values based on estimated capital cost ranges.

No investment or production tax credits are assumed for any technology.

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Cost of CO2, $/metric ton LCOE is shown for high level comparison purposes. Actual plant investment decisions are affected by a number of other project specific considerations and caution should be used when comparing technologies based on LCOE. See Appendix A of report 1026656 for more details.


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Onshore Wind

Offshore Wind

CSP

Solar PV

Comparative Levelized Costs of Electricity of Non-Dispatchable Technologies* – 2015


Average LCOE values based on estimated capital cost ranges.

No investment or production tax credits are assumed for any technology.


*For wind, solar PV, and CSP without storage, production is set by resource availability, not load demand. LCOE values presented here do not include integration costs (e.g. costs associated with additional reserves, balancing, conventional generation cycling, etc.). Care should be used when comparing LCOEs of these technologies to dispatchable technologies.


Observations on Value of Wind and Solar

Victor Niemeyer


AWS Truepower Data Set: Capturing the Location and Variability of Wind

• AWS Truepower wind data – Based on actual 1997-2012

meteorology

– Provides simulated hourly output for typical turbines (80/100m height, 1.5-2.0 MW)

• Identified 5300+ “utility-scale” sites – Exclusion areas

– 100 MW site minimum

– Distance to grid

– Terrain/wake effects


Location of wind resource by state and CF

New England Mid-Atlantic

S-Atlantic NE-Central

SE-Central NW-Central

SW-Central Texas

Mountain Pacific

California

Potential Capacity (MW)

MAMENHVTN

YPAMDNCSCVAILINM

IOHW

IWVALG

AMSTNIAKSM

NMONDNESDARLAO

KTXAZCOIDMTNMNVUTW

YORW

ACA

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10,000

20,000

30,000

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50,000

60,000

70,000

Capacity Factor (CF)


Site Capacity Factors Drive Average Costs of Generation; Distance to Grid is Secondary

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Site

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MW

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Site Capacity Factor (%)

Wind Generation Costs by Capacity Factor


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Wind TWh (million MWh)

2007 Combined On- and Off-shore Wind Generation Supply

EPRI Wind Resource Assessment from Truepower Shows Vast Generation Potential

Total U.S. Gen in 2007

2007 Gen by Coal

Cost to generate a MWh from wind (no tax credits)


Considerable Year-to-year Variation in National Wind Energy Supply

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Wind TWh (million MWh)

Combined On- and Off-shore Wind Generation Supply for Selected Years

2007 Generation Cost

1998 (worst)

12 Yr Avg

2008 (best)


Example Analysis for NW-Central Region

• State hourly load data for 2007 from Energy Velocity

• Hourly loads and wind output synchronized so driven by same 2007 meteorology

• Add 50 GW new installed wind capacity within region

• Rank sites by capacity factor, build best sites first

NW-Central


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NWC Time Series from 8/9/07 to 8/16/07 w 50 GW Added

Wind

NWC Load

Anti-correlation of Wind with Load Creates Ramping Issues (50 GW example)

The morning up-ramp

The evening down-ramp


Anti-correlation of Wind with Load Also Forces Diminishing Returns to Wind Additions: 100 GW

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NWC Time Series from 8/9/07 to 8/16/07 w 100 GW Added

Wind

NWC Load

More wind than load produces local surplus that must be spilled or exported


Modeling Provides Preliminary Realistic Assessment of Wind’s Strategic Potential

Mix of wind and transmission investment and operating decisions to minimize cost of delivering wind to serve load

• Simultaneous regional 8760 hourly loads and potential wind for 2007

• Existing mix of generation and transmission capability

• New wind turbine costs

• New transmission costs

Pacific

California

Mountain

Texas

NW-Central

SW-Central

NE-Central

M-Atlantic

S-Atlantic

SE-Central

Florida

NE

1.6

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Summer Capacity in GW (source: EPA)

REGEN Optimization


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National Wind Energy Potential Supply Curves* (including delivery costs)

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Delivered Cost with Existing Transmission

Generation Cost

Cost Delivered to Load with New Transmission

Transmission Line Miles

*EPRI – AWS TruePower National Wind Energy Supply Curves


Following Example Shows Similar Diminishing Returns for Large Penetrations of Solar

• Same NW-Central region (MN, ND, SD, KS, IA, NE, MO)

• Hourly loads from Energy Velocity

• Solar and wind shapes from AWS Truepower

• Plots show net load with additions of 0 to 20 GW of solar PV

• Sensitivity case shows 20 GW of PV with 20 GW of wind


2007 Peak Day Net Load with No Solar PV (Reference Case)

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NW-Central Week of 8/5/2007 with 0 GW PV

Net Load-NW-Central


Peak Day Net Load with 5 GW of Solar PV (peak and energy reduction)

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Peak Day Net Load with 10 GW of Solar PV (peaks getting “spiky”)

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Peak Day Net Load with 15 GW of Solar PV (no further peak reduction)

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Peak Day Net Load with 20 GW of Solar PV

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High Penetration of Wind and Solar Lead to Extreme Variability and Limited Peak Synergy

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Observations

• LCOEs useful for ball park estimates of costs, but numerous embedded assumptions mean “caveat user”

• Wind and solar provide “shaped energy” whose value can be usefully summarized by LACE, but diminishing returns to wind/solar at policy-relevant levels of penetration means LACE estimates are not constants

• Good reasons for using power system simulation models in policy analysis (e.g., NEMS, IPM, US-REGEN, Haiku)

• LCOE, LACE, and the simulation models aren’t perfect

• But they all can be useful


Together…Shaping the Future of Electricity

LCOEs and Renewables€¦ · 25/07/2013 · Victor Niemeyer . Program Manager, Energy and...

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Transcript of LCOEs and Renewables€¦ · 25/07/2013 · Victor Niemeyer . Program Manager, Energy and...