NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, operated by the Alliance for Sustainable Energy, LLC.

Quantifying the Level of 

Cross-State Renewable 

Energy Transactions 

Project Team: Jenny Heeter, Philipp Beiter, Francisco 

Flores-Espino, David Hurlbut, Chang Liu

Clean Energy States Alliance webinar

February 2015

NREL/PR-6A20-63458
2

Purpose of Analysis

• Provide first-ever assessment of the 

extent to which renewable energy is 

crossing state borders to be used to meet 

renewable portfolio standard (RPS) 

requirements. 
3

Two Primary Methods for Data Collection

Collect data from regional 

REC tracking systems, state 

agencies, and utility 

compliance reports to 

understand how cross-state 

transactions have been used 

to meet RPS compliance.

Estimate regional renewable 

energy flow using 

generator-specific 

information primarily 

sourced from EIA, SNL 

Energy, and FERC Form 1 

filings. The renewable 

energy examined through 

this method may or may not 

have actually been used to 

meet RPS compliance.

1. Renewable Energy 

Certificate (REC) Tracking 2. Power Flow Estimates
4

These Approaches are Complementary

• The two approaches are complementary but do not 

yield identical results: 

o What is GENERATED (power flow analysis) in a given year is 

NOT necessarily USED FOR COMPLIANCE (REC 

transactions) in that same year. 

o Generation may be contracted through a power purchase 

agreement (PPA) to a counterparty in State X, but the RECs 

from that generation may be sold to state Y.

• Here we provide an analysis “snapshot” for 2012; we 

provide 2013 compliance data, where available, in the 

associated data file provided here: 

http://www.nrel.gov/analysis/policy_state_local.html
5

Limitations

• Data on REC tracking include actual MWh used to meet RPS 

compliance; power flow data are estimates.

• Data on power purchase agreements (PPAs) is incomplete, as 

a result, only 43% of the total net generation from those 

agreements is reflected in the power flow estimate. 

• Power flows were restricted to NERC region boundaries, 

which resulted in an additional 5% of the total net generation 

being excluded from the analysis.

• Estimates do not fully capture contributions from small 

generators.
1. REC Tracking & 

Compliance Data
7

Background: REC Tracking Systems

• Electronic REC tracking 

systems ensure that RECs are 

“retired” (used to meet 

compliance or substantiate a 

voluntary claim) only once by 

assigning a unique serial 

number to each MWh of 

renewable energy generation. 

• In the United States, there are 

ten different tracking systems 

(New York’s system is under 

development). REC tracking 

systems generally follow the 

same boundaries as regional 

transmission organizations or 

independent system 

operators. Source: ETNNA (2015). Full references on slide 28. 
8

Methodology: REC Tracking

• Data are RECs retired to meet 2012 compliance.

o In some cases, states allow older vintage RECs to be used

o In some cases, states allow REC retirements for 2012 compliance to occur 

post-2012 (e.g. in the first quarter of 2013).

• Data include all RPS Tiers/Classes.

• Data do not include multipliers (e.g., Michigan’s Incentive 

RECs, in-state generation multipliers).

• Data sources:

o Tracking systems: M-RETS, PJM-EIS, NEPOOL, NC-RETS

o RPS administrators, through use of tracking system or other mechanism: MI, 

MO, CA, NM

o RPS Compliance Reports: WA, OR, CO, KS, NY, TX

o Data incomplete and not readily available: AZ, NV.

• This presentation is focused on 2012 compliance; we also 

gathered 2013 where possible and provide it in the 

associated data file available here: 

http://www.nrel.gov/analysis/policy_state_local.html. 
9

2012 RPS Compliance Data by State

• States are presented by region.

• Each pie chart represents the source of RECs retired 

to comply with the state’s RPS in 2012 (unless 

noted).

• State data representing less than 0.01% of 2012 

compliance are not shown. 

• For states marked with *, see Notes on REC 

Transaction Data for more information. 
10

Western U.S.: 2012 RPS Compliance

CA 72%

Out-ofState

28%

CA* 54,057,767 MWh

CO 92%

WY

8%

CO* 3,306,732 MWh 

NM 

100%

NM 1,352,815 MWh 

OR 58%

WA 16% MT

CA 3% BC 9%

ID 2%

UT 1%

WY

11%

OR 1,537,731 MWh 

WA 57%

MT 2%

OR 34%

ID 7%

WA 2,800,917 MWh

• States in the western U.S. used primarily in-state RECs (57%-100%) for compliance; out-ofstate RECs were typically drawn from adjacent western states.

• Arizona and Nevada are not included due to incomplete or not readily available data.

MT

94%

ND

3%

OR

WA 2%

1%

MT 717,347 MWh

* See Notes Slide

NOTES: State data representing less than 0.01% of 2012 compliance are not shown here. See Notes and Reference slides for more information on data sources.
11

New England: 2012 RPS Compliance

RI 23%

ME 16%

MA 8% NH 13%

NY 23%

VT 17%

RI 765,747 MWh

MA 39%

ME 15%

NH 12%

NY 9%

QC 4%

RI 12% PE 2%

VT 7%

MA 6,854,865 MWh 

ME

82%

CT

4%

MA

5% QC

5%

RI 1%

VT

3%

ME 3,516,022 MWh

NH

65%

CT

1%

ME

7%

MA

2%

NY

2%

RI

17%

VT

6%

NH 1,061,636 MWh

CT

41%

ME

17%

MA

1%

NH

19%

NY

1%

QC

1%

RI

10%

VT

10%

CT 4,584,201 MWh

CT 0.28%

• New England states used 23%-65% in-state RECs; they relied on a mix of out-of-state RECs, 

primarily from New England, but also from New York state and Canadian provinces. 

NOTES: State data representing less than 0.01% of 2012 compliance are not shown here. See Notes and Reference slides for more information on data sources.
12

Midwest: 2012 RPS Compliance

MN

76%

IA

1%

MB

4%

ND

12%

SD

2%

WI

5%

MN 9,638,920 MWh

WI

59%

IA

16% MB

6%

MI

7%

MN

12%

WI 3,294,576 MWh

MO

6%

IA

63%

KS

29%

Unknown

2%

MO 1,132,519 MWh

KS

90%

Unknown

10%

KS* 1,168 MW

IA

100%

IA 294,575 MWh

MI

94%

IN 2%

WI

4%

MI 3,423,994 MWh

IA 0.18%

SD 0.34%

IL

40%

IN

5% IA

15%

MD

17%

MN

4%

MO

4%

ND

4%

OH

5%

PA

2%

SD

1%

WV

1%

WI

2%

IL 3,842,200 MWh 

VA 0.01%

NY 0.18%

NOTES: State data representing less than 0.01% of 2012 compliance are not shown here. See Notes and Reference slides for more information on data sources.

• Midwestern states compliance approach varied, ranging from Iowa’s use of 100% in-state 

RECs to Missouri’s use of 6% in-state RECs.

* See Notes slide
13

Mid-Atlantic: 2012 RPS Compliance

NJ

24%

IL

26%

IN

15%

MD

2%

OH

4%

PA

17%

VA

3% WV

9%

NJ* 7,830,728 MWh

OH

43%

IN

22%

KY

12%

PA

11%

WV

12%

OH 1,967,546 MWh

DE 0.32%

DE 0.29%

NC 0.36%

TN 0.18%

DE

6%

IL

10%

IN

8%

MD

24%

PA

49% VA

3%

DE* 543,844 MWh

CT 0.02%

WV 0.22%

• Mid-Atlantic states used 6% to 53% in-state RECs and sourced out-of-state RECs mostly from the MidAtlantic and Midwest.

MI 1%

MD

30%

IL

10%

IN

5%

IA

2% NY

5%

OH

2%

PA

21%

VA

WV 22%

2%

WI

1%

MD 5,481,176 MWh

PA

53%

DE

1%

IL

14%

IN

2%

MD

1%

NJ

2%

OH

1%

VA

24%

WV

2%

PA 14,691,375 MWh

* See Notes slide

NOTES: State data representing less than 0.01% of 2012 compliance are not shown here. See Notes and Reference slides for more information on data sources.
14

Other States: 2012 RPS Compliance

TX

100%

TX 12,119,614 MWh

NY

96%

PA

3%

QC

1%

NY* 3,670,409 MWh

NC

57%

Out-ofState

43%

NC* 3,956,052 MWh

• New York and Texas used almost entirely in-state RECs.

• North Carolina used a mix of in-state and out-of-state resources. RECs listed by the state as "in-state 

(delivered to NC)” in NC-RETS are classified as out-of-state renewables in this analysis; as a consequence, 

the percentage of out-of-state renewables is calculated as higher than the state’s 25% limit for 

unbundled RECs from out-of-state facilities. 

* See Notes slide
15

Registration by Small Generators Varies

A small data gap exists in the REC tracking analysis because not all small generators are registered in tracking 

systems. Typically, small generation is counted toward RPS compliance in the state where it is sourced. In the 

table below, we present tracking system data on “small generators.” Because there is not a single definition of 

“small generator,” we present three sets of data: renewable generators ≤ 1 MW, renewable generators ≤ 10 

MW, and solar PV generators.

Whether a small generator registers depends on a variety of factors, including:

• State requirements (for example, in order to receive incentive payments)

• Level of incentive payment

• Cost to register 

• Cost of metering requirements, if any.

Tracking 

System

# of 

Renewable 

Generators 

≤ 1 MW

# of 

Renewable 

Generators 

≤ 10 MW

Total Capacity 

of Renewable 

Generators 

≤ 1 MW (in 

MW)

Total Capacity 

of Renewable

Generators ≤ 

10 MW (in 

MW)

# of Solar 

PV 

Generators

Total Capacity of 

Solar PV 

Generators (in

MW)

# Solar PV 

Certificates Issued 

and Year of Issue

WREGIS * * 696 3,767 2,143 7,062 9,221,379 (2014) 

M-RETS 240 446 69 69 101 77 41,377 (2014) 

MI-RECS 73 142 34 300 41 17 not available 

NC-RETS 400 646 90 1,048 363 548 387,546 (2013) 

NAR 50 118 31 302 47 72 not available 

ERCOT not available not available not available not available 22 175 178,325 (2013) 

PJM-EIS 53,060 53,346 1,152 1842 53,357 2,028 1,946,597 (2014) 

NEPOOL not available not available not available not available 6,626 not available 386,031 (2013) 

* WREGIS has 2,149 registrants <=1 MW and 2,895 <=10 MW, but each may contain several hundred “aggregated” units that bundle even smaller units.
16

Summary: 2012 RPS Compliance

• States on average sourced 61% of 2012 RPS requirements 

from in-state resources (65% on weighted average basis).

• States in New England and PJM used greater percentages of 

out-of-state RECs than states in the Midwest and West. 

• States that used out-of-state RECs sourced them according to 

their RPS requirements, which typically restrict eligible RECs 

to the state’s region (e.g., ISO or neighboring states). 

• Utilities may have sourced RECs from out-of-state to reduce 

the cost of compliance, to source RECs from specific 

generation types, or for other reasons.

• California’s RPS limits the use of out-of-state RECs, but the 

limitation only applies to contracts executed after June 1, 

2010.
17

Notes on REC Transaction Data

AZ: Compliance data by state or fuel are not available.

CA: Source states for out-of-state generation are not available. Data are only available for 

the 2011-2013 compliance period; we divide the period value by three to estimate 

2012 retirements. Data have not been verified by the California Energy Commission.

CO: Data for cooperative utilities not purchasing through Tri-State are not available. TriState data are from 2013. Fort Collins and Colorado Springs data are estimates.

DE: Compliance period used: June 2012 - May 2013.

IL: Compliance period used: June 2012 - May 2013.

KS: RPS compliance is reported on a capacity basis (MW). Source states for out-of-state 

generation are not available.

NV: Compliance data by state or fuel are not available.

NJ: Compliance period used: June 2012 - May 2013.

NY: Data are sourced from NYSERDA's "Maximum Annual Contract Quantity" reported in 

“The New York State Renewable Portfolio Standard Performance Report: Through 

December 31, 2012" and do not necessarily reflect actual REC retirements.

NC: Source states for out-of-state generation are not available. RECs listed by the state as 

"in-state (delivered to NC)” are classified as out-of-state renewables in this analysis; as 

a consequence, the percentage of out-of-state renewables is calculated as higher than 

the state’s 25% limit for unbundled RECs from out-of-state facilities. 

PA: Compliance period used: June 2012 - May 2013.
2. Power Flow Estimates
19

Power Flow Estimates

• We analyzed power purchase agreements (PPAs) to estimate crossstate renewable transactions. PPA agreements do NOT necessarily 

correlate with REC purchases and also are not necessarily used to 

meet RPS compliance.

• The following renewable resource types were included in this 

analysis: small hydropower (generator capacity <30 MW), solar, 

wind, geothermal, and biomass. These resource types are generally 

consistent with eligible RPS resources, given that each state has its 

own eligibility definition.

• We used data from SNL Energy, EIA, FERC, and other sources to 

allocate renewable generation from the generation plant to 

contracted parties.
20

Allocating Generation to Power Purchasers

We assigned generation from power plants to power purchasers using two different 

methodologies, depending on whether a PPA was in place for the generation. 

• Where a PPA was in place, power flows were allocated in a two-step procedure: 

First, we allocated flows to the largest PPA counterparty of a power plant. In a 

second step, we proportionally allocated this energy flow to those states in which 

the largest PPA counterparty has a customer base in. 

o Due to data limitations, only a subset of PPA counterparties could be matched with power plants; as 

a consequence, only 43% of the total net generation from power plants with a PPA in place are 

reflected in the analysis.

• We restricted flows for a PPA to occur within only the encompassing NERC region. 

For instance, recorded flows from Texas to New Mexico refer only to the part of 

Texas falling within the SPP NERC region. As a consequence of this assumption, HI 

and AK do not show flows to other states. We did not reallocate flows that were 

restricted by NERC region boundaries, which resulted in an additional 5% of the 

total net generation being excluded from the analysis.

o This restriction is a simplifying assumption for modeling purposes, but may not reflect how energy 

actually flowed in 2012.

• Where no PPA was in place, we allocated the 2012 net generation of a plant to the 

RTO in which the plant was geographically located. While this method is less 

precise than the method for allocating generation where a PPA was in place, the 

level of precision is consistent with the data available.
21

• California, Utah, and Arizona were net importers of PPA-based renewable generation; 

several other Western states were net exporters on a total generation basis.

Renewable Generation from Power Plants with PPAs: 

2012 Net Exports in the Western Interconnection, By State

-5,000,000

-4,000,000

-3,000,000

-2,000,000

-1,000,000

0

1,000,000

2,000,000

3,000,000

CA UT AZ CO WA ID MT NV NM WY OR

Net exports (MWh)

Net exports (in MWh)
22

Renewable Generation from Power Plants with PPAs: 

2012 Net Exports in the Eastern Interconnection, By RTO and State

• States rich in wind resources (e.g. Kansas, Illinois, South Dakota, Minnesota) were 

large net exporters of renewable generation, on a total generation basis.

-2,000,000

-1,500,000

-1,000,000

-500,000

0

500,000

1,000,000

1,500,000

2,000,000

2,500,000

MA VT RI CT NH ME IN ND WI MI IA MN SD IL NY NJ OH VA DE WV MD PA KY MO AL TN MS AR LA SC GA FL NC NE OK KS

ISO New England MISO NY

ISO

PJM Southeast SPP

Net Exports (MWh)

Net exports (in MWh)
23

2012 Renewable Generation from Power Plants: 

Plants Without v. With a PPA Counterparty by RTO

• The amount of PPA-based renewable generation identified in this analysis varied by 

region: In California, most renewable generation was associated with PPAs, while in 

New England and New York, the majority of renewable generation was not.

• We allocate renewable generation without an associated PPA by RTO; the greatest 

amount of renewable generation without a PPA was located in MISO.

0

5,000,000

10,000,000

15,000,000

20,000,000

25,000,000

30,000,000

35,000,000

PJM Interconnection,

LLC

California

Independent System

Operator

Electric Reliability

Council of Texas Inc.

Midcontinent

Independent System

Operator, Inc.

New York

Independent System

Operator

ISO New England Inc. Southwest Power Pool

Inc

MWh

Without PPA

Counterparty or PPA

data not available

With PPA

Counterparty
24

Summary: 2012 Power Flow Estimates

• Understanding how power is contracted can provide 

insight into how power may flow across states or 

regions. 

• However, these estimates do not provide a complete 

picture of how generation may have been used to 

meet RPS compliance requirements.

• In the Western U.S., California, Utah, Arizona, and, to 

a lesser degree, Colorado and Washington, were net 

importers of renewable generation in 2012, while 

other states were net exporters. 

• Eastern states rich in wind resources were typically 

net exporters of renewable generation in 2012. 
Observations and Further 

Research
26

Observations

• 2012 REC tracking data showed that RPS compliance used a 

significant amount of cross-state transactions.

o States on average sourced 61% of 2012 RPS requirements from instate resources (65% on weighted average basis).

• The amount of generation associated with these transactions 

varied by state and region. 

• 2012 power flow estimates of cross-state transactions at the 

level of individual plants demonstrate similar conditions.

• Not all generation from small renewable generators is 

captured in REC tracking systems or in the power flow 

estimates.
27

Questions for Further Research

The data presented here could be further examined to help 

answer the following RPS-related questions:

• To what extent are RECs from older generators used to meet 

RPS compliance requirements? 

• To what extent are RECs generated in an earlier year used to 

meet future year RPS compliance requirements?

• Which states have large banks of existing RECs that could be 

used for future year compliance? 

• In the Eastern Interconnection, to what extent do cross-state 

renewable energy PPA flows stay within NERC or RTO regions?

• What additional data sources could be developed to inform 

and strengthen future analyses?

Answers to these questions could improve our understanding of 

the impacts of RPS policies.
28

Acknowledgments

• The authors would like to thank the U.S. Department of Energy’s (DOE) 

Office of Energy Efficiency and Renewable Energy’s Strategic Programs 

Office for funding this analysis. In particular, the authors are grateful to 

Stephen Capanna and Ookie Ma for their support of this project.

• The authors would also like to thank the following individuals for providing 

data for and/or review of this work: Lori Bird, Jaquelin Cochran, Jeffrey 

Logan, Gian Porro, Robin Newmark and David Mooney of the U.S. 

Department of Energy’s National Renewable Energy Laboratory; Galen 

Barbose, Lawrence Berkeley National Laboratory; Matt Clouse, U.S. 

Environmental Protection Agency; Andrea Coon, WREGIS; Glenn 

Blackmon, Washington Department of Commerce – State Energy Office; 

Claire Eubanks, Missouri Public Service Commission; Angela Gould, 

California Energy Commission; Kelly Knutsen and Kara Podkaminer, DOE; 

Ed Hold, Ed Holt & Associates; Warren Leon, Clean Energy States Alliance; 

Julie Peacock, Oregon Department of Energy; Heidi Pitts, New Mexico 

Public Regulation Commission; Ankit Saraf, ICF; Margo Shurman, Montana 

Public Service Commission; Katherine Trachsel, Michigan Public Service 

Commission; and James Webb, APX, Inc.
29

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