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RGGI Renewable Energy Modeling Assumptions

Bob Grace, Sustainable Energy Advantage, LLCRegina Jain, LaCapra Associates

RGGI Stakeholder MeetingFebruary 16, 2005 NY, NY

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Overview

• Overview of Renewable Energy Analysis

• Key Challenges: Demand Assumptions– Differing RPS policies in states across region

• Key Challenges: Supply Assumptions– Developing resource potential– Developing representative costs

• Summary of Key Renewable Energy Inputs

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Development of Renewable Energy Modeling Inputs

• Purpose: – Develop reasonable input assumptions for IPM renewable energy

(RE) supply availability, cost and demand to:(i) determine baseline (ii) enable policy analysis of greenhouse gas initiative measures

• Perspective:– “Middle of the Road,” neither conservative nor aggressive

• Constraints:– Recent studies and sources – Consistency across the modeling region– Accommodate state/regional studies using different methodologies

and assumptions, and filling numerous data gaps• Analysis years – 2005, 2010, 2015, 2020

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Modeling ChallengesExample: wind power (land-based)• Windy land area by wind speed class• Performance (c.f.) by wind speed class• Production profile• Land Exclusions• MW quantities• Distance from transmission (cost adders)• Representative costs (capital, operating,

financing)• Project scale• Improved performance and cost over time• Additional system (integration) costs• Production tax credit availability• Resolution (# blocks modeled)• Phase-in availability (IPM would take all

at once!)

Analysis and judgment required:• Selection of appropriate data

sources (credible, recent, applicable to region)

• Resolve conflicts, fill gaps, extrapolate

• Avoid bias

• Taking analysis to appropriate level of detail & materiality

• Wide range of input parameters…

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Demand Drivers for Incremental Renewable Energy

RPS: Resources Compete to Meet Demand• Connecticut Class 1 (excl. fuel cells)• Massachusetts• New Jersey Class 1 (excl. solar tier)• Rhode Island (less 2% existing)• Maryland Tier 1• New York main tier • Pennsylvania Tier 1 (excl. solar tier)

RPS: Forced Quantities• NY Customer Sited Tier• NJ & PA Solar Tiers• CT fuel cells (est.)

RPS Ignored (existing RE):• Maine• CT Class 2• MD Tier 2• PA Tier 2

Green Power + Other• NY Executive Order 111•State-by-state penetration of voluntary demand (H, M, L; NY 1% goal)

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Adjustments to RPS % Targets for…

• Extrapolations MA, NJ beyond set targets

• Load exemptions

• Existing eligible supply in baseline

• Bonus credits (MD)

• Alternative Compliance Payments (MD)

• Supply from outside modeling footprint

• Coal-mine methane (PA)

• Biomass retrofits (MA)

• “Forced” supply (e.g. PV)

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Representing RPS Demand: “Standard” RPS Definitions

• Challenge: Eligibility, geographical/delivery & vintage requirements differ• Approach Simplify:

– Approximate differing eligible resources and geographic requirements across RGGI states while relaxing the fewest possible constraints

– Consolidate into 2 “standard” RPS policies

RGGI Northern Tier RPS RGGI Southern Tier RPS

Represents State RPS MA & RI NY, NJ, MD, CT, PA

Eligible to Supply RECs without Energy Delivery

New EnglandNEPOOL,

NYISO, PJM

Eligible to Supply RECs only with energy delivery

NY, Quebec Ontario & Quebec

Eligible Resource Types

Wind, LFG (post 97 only) Incremental hydro <30 MW

(only after 2006)

All post-1997 biomass

Biomass co-firing @ coal plants 2010 and later

Wind (all); LFG (all) Incremental hydro <30 MW

All post-2002 biomass

Biomass co-firing @ coal plants

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Supply Side Resources Modeled• Restricted analysis to

subset of technologies:– Proven– Commercially

available– RPS-eligible – Material contribution

over analysis horizon

Supply Curve• Onshore wind• Offshore wind • Landfill Gas• Biomass Co-firing• Biomass Direct Fire (NOx

control)• Biomass Gasification• Hydroelectric

Forced, Fixed Quantities• Solar/Photovoltaics• Fuel Cells

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Resource Potential Philosophy

Technical Potential

Economic Potential

Maximum Physical

Based on Demand

“Developable Potential”

That portion of technical potential that could

realistically be developed subject to real-world

constraints in the presence of sufficiently high demand

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Key Challenges: Developing Resource Costs

For each technology, we sought to characterize:• Capital Costs, $/kW• Fixed O&M, $/kW-year• Variable O&M, $/MWh• Heat Rate (Btu/kWh)• Performance (Capacity Factor)• Financing Assumptions (structure, cost of money, term)• Production Profile (electricity revenue determines need

for REC revenue)

Some examples follow….

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Wind Resource Potential Of vast potential, how much is developable?

On-Shore:• NREL performed analysis for RGGI (Oct. ’04) of windy land area by:

– Wind speed, distance from transmission, 9 land use types– Excluded land with >20% slope, protected federal lands, etc.

• We then:– Allocated between wind “farms” and “clusters” based on state-specific dynamics

(landform, ownership, programs to encourage clusters) drives cost due to scale economies

– Applied substantial further land use exclusions

Off-Shore:• No comprehensive study available, so Commissioned study for RGGI based

on detailed GIS analysis (AWS Truewind) • Limited developable potential:

– <100 ft. max depth beyond 3 miles of shore– Exclusions 87.5% of remainder to approximate shipping lanes, fisheries shoals,

proximity to transmission, permitting difficulties, etc.

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Resource Costs: WindCosts vary depending on:

– Substantial economies of scale: wind farms (more than 10 wind turbines) vs. clusters (2 to 10 turbine configurations)

– Distance from transmission: Near (<5 miles), far (5-20 mi.) or distant (>20 mi.)

106 “blocks” modeled– Source: NY RPS Cost Analysis, adjusted to reflect impact of steel markets

& exchange rates – Canadian wind exported to Northern Tier subject to delivery cost adder

Wind Integration• Large quantities of wind (a variable resource) may impose some

upstream operating costs on system• Our analysis of available studies of such costs concluded

additional operational costs ~ $1/MWh at low wind %, ~ $10/MWh when wind penetration reaches 20%.

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Resource Potential: Biomass• Biomass fuel availability is the constraint on amount of new biomass• Challenges:

– 1) Est. amount of biomass fuel available for incremental power generation– 2) Based on total cost of energy, determine which technologies will likely be

built– 3) Allocate fuel to technologies (no shared fuel curve in IPM)– 4) Power plant access to fuel supplies (delivery cost, logistics)

• Fuel Availability and Cost– Data source for fuel quantities: Oak Ridge National Laboratory study (most

credible study that covered all RGGI states)– Quantities described by four cost blocks (from $.70 to $3.15 per mmbtu)– Fuels considered: agriculture residues, forest residues, mill wastes, urban

wastes, and dedicated crops (potential)– Remove fuel used in existing biomass facilities– Assumed not economic to transport fuel over state borders, except NYC/CT

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Resource Potential: BiomassNew Construction of Biomass Facilities• Co-firing: Cheap, but limited by current coal capacity;

– potential assumed to be 25% of existing coal facilities, 15% of output.

• Gasification, direct-fire and fluidized bed total energy costs compared in each year– New build in each year is all most economic technology– Remaining fuel (after use by co-firing) allocated to these technologies

Sustainable Biomass Requirements• No adjustments made for NJ and CT RPS fuel restrictions. • Assume NY and MD, which have minimal restrictions, can absorb

RECs generated by such fuel by displacement.

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Other Resource Potential Challenges

• Phase-in Availability– Can’t build everything overnight (but the model doesn’t

know that) due to development & construction lead-time, infrastructure, public acceptance, etc.

• Imports into RGGI Modeling footprint– From US: modeled WV Wind only

– From Canada: large wind potential, constrained by transmission capacity

– Costs associated with energy deliver requirements

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Other Resource Cost Challenges

• Generalization into resource “blocks” vs. project-, site-specific factors

• Minimize detail for modeling simplicity without removing meaningful distinctions

• Variety of different sources• LFG: costs vary by with and without collection

systems, scale• Hydro: costs vary between upgrades and powering

existing dams without generation

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Major Cost Wildcard:Production Tax Credits (PTC)

• Federal PTC– Set to expire 12/31/2005– Major wildcard for future

re: duration, value, applicability

• Modeling Approach– Seek “middle ground”

between further PTC extension after 2005 and no PTC extension

Resource/

Installation

2004-05 2006-10 2011 +

Wind, Closed Loop Biomass1, Solar

1.8 cents/kWh + CPI for first 10 years of operation

0.9 cents/kWh + CPI for first 10 years of operation

0

Open-loop biomass, Landfill gas

0.9 cents/kWh + CPI for first 5 yrs. of operation

0.45 cents/kWh + CPI for first 5 yrs. of operation

0

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Modeled Adjusted Incremental RPS Demand

-

10,000

20,000

30,000

40,000

50,000

60,000

2005 2010 2015 2020

GW

h/y

r

GP + EO111

Forced (PV, small wind, fuel cell)

RI

MA

PA - Tier 1 Main Tier

MD Tier 1

NY- Main Tier

NJ- Class 1 Main Tier

CT Class 1

Southern Tier

Northern Tier

Northern Tier includes MA and RI.

Southern Tier includes. CT Class 1, NJ Class 1 Main Tier, NY Main Tier, MD Tier 1, and PA Tier 1.

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Summary of Inputs: Supply Curve

Cost and Potential of Renewable Resources, 2010

-20

406080

100120

140160

- 500 1,000 1,500 2,000 2,500 3,000

MW Potential

$/MWh

4,000 5,000

LFG w/cLFG w/o c

WF 6

WF 5 WF 4

NH 2

NH 1

OW 6WC 3 OW 5

WF 3

HU 2

WC 4

WC5, WC6, HU1

COF

BIO

Caveats:

•2010 is last year of PTC

•These are all-in COE, but premium varies based on regional electricity prices, production profile

•More biomass potential is off the charts

•Co-firing is an estimate for comparison purposes

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Capital Cost Trajectory over TimeInstalled Costs Trajectory over Time, $2003/kW

$0

$500

$1,000

$1,500

$2,000

$2,500

$3,000

$3,500

2005 2010 2015 2020

Hydro

Fuel Cells SOFC

Gasification

Direct-Fired

Landfill Gas

Offshore Wind

Fuel Cells MCFC

Onshore Wind

Co-Firing

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Conclusions/Final Thoughts: Assessing RE Developable Potential

• Targeted “middle of the road” estimates… try to avoiding bias of both skeptics and technologic optimists

• Baseline demand driven by locked-in policies• Best data sources available balancing regionally consistent vs. current & unbiased• Many choices necessary to reflect feasible “developable potential” in the face of

wide range of factors• Simplify for modeling without losing meaningful detail• PTC wildcard merits sensitivity analysis

Caution: RE and GHG (& other air) policies not synchronized• Accounting systems for RECs not designed to track emission rights• RE mandates vary on eligibility of resources selling off emission rights:

– RECs are RPS-eligible even if GHG benefits sold elsewhere (NJ; MA?)– All Environmental Attributes bundled for compliance (NY)– TBD (RI)

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The End

(Extra reference slides follow…)

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On-Shore Wind Potential excluded this % of windy land…

• Urban 99.5%

• Agriculture 50.0%

• Grassland 50.0%

• Ridge Forest 75.0%

• Non-ridge Forest 75.0%

• Shrubland 50.0%

• Water 100.0%

• Wetland 99.0%

• Other 50.0%

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Resource Potential: Phase-In Constraints

• Can’t build everything overnight (but the model doesn’t know that)– Development & construction lead-time, infrastructure, public

acceptance, etc.• Applied Phase-in to Developable Potential Totals

– Default assumption: Limit of 25% of each resource block available in 2005 unless otherwise specified.

– On-shore wind: each state assigned permitting difficulty based on judgment, near-transmission developed before far from transmission; also considered biggest demand drivers with locational bias

– Offshore wind: 25% of developable potential phased in each 3 years starting 2009 modeling year

– Biomass limited to 15% of max in 2006

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Developing Resource Potential: Imports to RGGI region

• U.S. RE imports into RGGI modeling footprint ignored as immaterial…– Except West Virginia wind

• Canadian Imports assumed:– Ignored as unlikely to be material:

• Biomass: environmental constraints, economic options available• LFG: limited quantities, not likely to be available for export• Hydro: constrained by 30 MW, no new dam eligibility assumption • Offshore wind: uncompetitive vs. US off-shore + delivery cosrts

– Considered onshore wind resources from Ontario and Quebec.• constrained by transmission capacity

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Resource Potential: Hydro & Landfill Gas

Hydro• Assume no new dams built during study period

• Assume 30 MW cutoff

• Source: “U.S. Hydropower Resource Assessment Final Report,” Idaho National Engineering and Environmental Laboratory (INEEL), 1998.

• Used quantities in INEEL, applying INEEL probability factors

Landfill Gas• EPA’s Landfill Methane Outreach Program database of potential sources

– Candidate landfills– Under construction projects– Shut-down projects

• Estimated impact of increased new sources of waste offset (in part) by degradation of methane available in existing sources; resulted in 3.1% CAGR in MW available through 2020.

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Resource Costs: Other Sources

Biomass• Costs taken from DOE/EPRI study, adjusted to reflect communication

with manufacturers and developers.Hydro• DOE Hydropower Program database (INEEL)Landfill Gas• NY RPS Cost Study and NYSERDA Technology AssessmentFuel Cells• NJ Renewable Energy Market Assessment, Navigant Consulting, and

NY RPS Cost Study.Solar PV• NY RPS Cost Study

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Cost Blocks in Each IPM Modeling ZoneResource Quantity and Cost Block

Onshore Wind

(ex: 106 blocks for US only)

•Wind Farms and Wind Clusters

•By wind class

•Near and far from transmission

Offshore Wind •By wind class

Landfill Gas •With collection systems in place

•Without collection systems

Biomass •Co-firing, Direct fire, & gasification

• Blocks differentiated by fuel cost

Hydroelectric • New generation at existing dams

• Incremental upgrades to dams with existing generation

Solar/PV •Residential

•Commercial

Fuel Cells •MCFC and SOFC