Greenhouse Gas Emissions Reductions from Wind Energy :

Location, Location, Location?

Duncan CallawaySNRE &

Department of Mechanical Engineeringdcall@umich.edu

Meredith FowlieFord School of Public Policy &

Department of Economicsmfowlie@umich.edu

With support from the University of California Energy Institute and the University of Michigan Energy Science, Technology, and Policy Award Program

“The issue of how much generation of emissions is displaced by production of electricity generation through wind energy is complex, but it needs to be understood properly.... Emissions displacement analysis is essential for policy and regulatory decisions.”

National Academy of Sciences (2007)

How are these emissions displacement estimates used in the policy process?

• Policy implementation EX: Used to distribute incentives to operators based

on avoided emissions (e.g. the NOx Budget Program)

• Policy design/ evaluation EX: Estimating (ex ante and ex post) emissions

reductions achieved through policy interventions that promote renewables development.

Estimating emissions displacement

A seemingly simple calculation is complicated by three stylized facts:

1.Resource performance profiles vary across sites.

2.Emissions displacement profiles vary across regions.

3.Correlation between resource availability and emissions displacement rates.

Annual average wind speed at 50 meters

- Red = 11 m/s

- Orange = 6.5 m/s

- Blue = 3 m/s

Wind Resources in New York

Data from AWS Truewind

5

Stylized example : Wind resource profilesA

vera

ge p

rodu

ctio

n (%

of p

eak

capa

city

)*

Profile 1: average capacity factor : 30%Profile 2 : average capacity factor : 30%

Stylized example : Estimating emissions displacement

• Next- estimate how system emissions would respond to the addition of a new wind resource.

• Anticipate how the electricity market will respond to an increase in intermittent, low marginal cost power production at a given site.

• This requires some understanding of how electricity markets work….

Stylized example : Emissions displacement profilesRegion A

Natural gas always on margin

Mar

gina

l em

issi

ons

rate

(lb

s C

O2/

MW

h)

• US average emissions rate of 2249 lbs CO2/MWh for coal generation.

• US average emissions rate of 1135 lbs CO2/MWh for natural gas generation.

1135 1135

2249

off-peak peak off-peak

Region B

Coal off peak

Natural gas on peak

off-peak peak off-peak

Mar

gina

l em

issi

ons

rate

(lb

s C

O2/

MW

h)

8

Stylized example : Estimated emissions displacement

Profile 1 Profile 2

Region A 204 tons/day*

(1135 lbs/MWh)203 tons/day*

(1135 lbs/MWh)

Region B 301 tons/day*

(1674 lbs/MWh)346 tons/day*

(1939 lbs/MWh)

* These estimates assume a 50 MW development

lbs

CO

2/M

Wh)

off-peak peak off-peak

lbs

CO

2/M

Wh)

off-peak peak off-peak

9

Emissions reductions from wind energy: Location, location, location?

• Do emissions displacement benefits vary significantly across wind sites in the U.S.?

• What explains variation across locations a. variation in wind profiles?b. variation in emissions displacement

profiles?c. correlation between (a) and (b) ?

• What are possible policy implications of the variation we document?

Research objectives

• Possibly improve upon methods currently used to estimate marginal emissions displacement rates.

• Estimate, with unprecedented precision, the marginal emissions displacement potential at wind sites across the Eastern U.S.

• Investigate the relative importance of inter-temporal correlations in resource availability and marginal emissions displacement profiles.

Past and present approaches to estimating emissions displacement• Regional system average emissions rates often used to

estimate marginal operating emissions displacement rates (US DOE, AWEA).

• Late 1990s/early 2000s, most serious studies used grid dispatch simulation models (ISO NE, US EPA, OTC, NESCAUM).

• Significant efforts underway to develop /improve methods to estimating emissions displacement benefits. (CEC, 2004; ISONE, 2006; Gil and Joos, 2007; Keith et al., 2004; NAS, 2007; NREL, 2007; Schiller et al., 2007; US DOE, 2006; US EPA, 2004; WRI, 2007; etc.).

• We are taking a regression-based approach

m indexes market region, h indexes hour of day, t indexes time,Z is a proxy for changes in wind, X includes variables that affect

dispatch /system operations.

• Data:– Hourly, unit level emissions and generation from

units in three regional markets (NY, NE, PJM).– Forecast load and RT load from ISOs and FERC 714– Imports / exports from ISOs– Other covariates (temp, fuel prices, etc)

14

Our approach

mhtmhtmhtmhmhmht ZXe )'(

15

Marginal emissions displacement profile: New York electricity market (Z = non-hydro generation)

NYISO system average

OTC estimate

Location

Average CO2

emissions rate

(lbs/MWh)

EU ETSCO2 value1

($/MWh)

RGGICO2 value2

($/MWh)

Current policy

incentive3 ($/MWh)

Z=combustion generation

Profile a 1162 $11.94 $1.78$35

Profile b 1178 $12.11 $1.81

16

Putting early results in context

1 The EU ETS price: approx. $22.61 / metric ton CO2 in October 20082 The RGGI price: $3.07 / ton CO2 in September 20083 All new wind eligible for Federal Production Tax Credit ($20/MWh). The weighted average price that NYSERDA paid for RPS Attributes for the most recent solicitation is $15 per Megawatt hour. 4 Source: FERC Oversight Electric Power Market Summaries

Estimated marginal emissions displacement profiles by region

NY MISO EAST

PJM NE

Y- a

xes

mea

sure

lbs

CO2/

MW

h

Next steps…..

• Continue to refine our model using data from New York and other Eastern states.

• Take the model to the data- estimate MOERs using 3TIER data.

• Generate site-specific estimates of emissions displaced by new wind development.

• Address policy questions surrounding efficacy of production-based incentives.