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Clean Energy Policies Analysis

The Role of Policy in Clean Energy Market Transformation

Elizabeth Doris

Senior Project Leader: 

State and Local Policy

National Renewable 

Energy Laboratory

TAP Webinar 

Nov 17, 2010

NREL/PR-7A20-50036
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FY07-FY09 Structure and Outcomes

DOE and NREL 

Leadership

Technical 

Working Group

SOS: Link policy 

and 

development

SCEPA: Link 

individual policy 

to state drivers

Reports:

2007: SCEPA: Summary of Working Group 

Input and Methodology Development

2008

•SCEPA: RPS, RFS, Tax Incentives

•SOS 2008 (2006 Data)

2009

•SCEPA: FIT, Manufacturing Policies, Loan 

Programs

•SOS 2009 (2008 Data)

Outreach: Presentations, websites, TA

Goals: 

1) Quantify the role of state policy in CE development 

2) Connect CE policy to state goals
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State Clean Energy Data Book

http://www.nrel.gov/cepa
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State of the States 2010

5

Purpose

Background

Methods

Results

Conclusions
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Definition: Clean Energy

6

Renewable 

Energy

Energy 

Efficiency

Clean 

Energy
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Purpose

7

To augment and build on traditional case study and 

narrower quantitative analyses to develop a quantitative 

understanding of policy impacts using statistical and 

empirical methods 

To open the 

door for 

more 

thorough 

analyses of 

policy 

options

To inform 

future policy 

development

To ultimately 

optimize the 

market 

share of 

clean 

energy
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State of the States 2010

8

Purpose

Background

Methods

Results

Conclusions
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Background

9

Increasing use of state policy to drive clean energy market 

transformation is leading to extensive research working to 

determine the best policies 

Result: numerous best practice guidebooks have 

emerged to assist the development of effective policy

Clean Energy: 

Environment

Guide to Action

Case studies on

projects and policy

implementation

Case studies and

examples of RE

and EE projects

Design best

practices and a

local policymaker’s

guidebook
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Background

10

Energy Efficiency Renewable Energy 

Behavior 

Change

Education

Transmission 

Policies

Rebates

Feed in Tariffs

RPS

EERS

Weatherization

Grants

Interconnection Access

Net 

metering

Tax 

incentives

State policymakers have many policy options aiming at the 

development of clean energy resources, including various rules, 

regulations, and incentives
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State of the States 2010

11

Purpose

Background

Methods

Results

Conclusions
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Methods – Renewable Energy

12

Policies Serving as Independent Variables

PV Wind Geothermal Biomass

Access Laws x

Bonds

Construction and Design 

Contractor Licensing x x x x

Corporate Tax Incentives x x x

Equipment Certification x

Generation Disclosure

Grants x

Industry Support x x x

Interconnection x x

Line Extension Analysis x x

Loans x x

Net Metering x x

Personal Tax Incentives x x

Production Incentives x x x x

Property Tax Incentives x x

Rebates x

RPS x x

RPS with Solar Set Aside x

Sales Tax Incentives x x

Voluntary & Mandatory 

Green Power x x
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Commercial or 

Residential 

Energy 

Efficiency

Dependent 

Variable

Commercial 

Energy 

Use/GSP

Independent 

Variables

High Efficiency 

Statewide 

Building 

Code(1)

Average 

Electricity Price

Energy 

Efficiency 

Resource 

Standard 

Methods – Energy Efficiency

13

Personal Tax 

Incentives

State Rebates

State Loans

Residential 

Energy 

Use/Population

OR

(1) Equal to or better than ASHRAE 90.1 2004.
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Methods – Renewable Energy

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Solar

Wind

Biomass

Geothermal

Dependent 

Variable

2009 Cumulative 

Capacity 

Installed

Independent 

Variables

Selected 

Policies

Average 

electricity price

FTG 

Interconnection 

Grade(1)

Restructuring

Population

Number of 

Policies

2009 Annual 

Electric 

Generation

OR

Number of 

RPS Effective 

Years 

(1) Refers to a grade of “C” or better from the Freeing the Grid report (NNEC, 2009).
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• Constrains the number of variables that 

may be tested in the regression

• Policies are binary

Small 

Sample Size

• Data for policies beyond 2007 would 

allow for the construction of a more 

robust model

Time Series 

Data

Policy Terms • Vary from state to state

• RE capacity or generation installed, not 

the percent of generation that is RE, 

which is typically targeted by RPS

Dependent 

Variable

Methods – Challenges

15
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State of the States 2010

16

Purpose

Background

Methods

Results

Conclusions
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Percent of Variation Between States Explained by Models (Adjusted R2

)

2009 Capacity/Generation vs 2008 Policies 2009 Capacity/Generation vs 2007 Policies

(One Year Lag) (Two Year Lag)

Technology Capacity (MW) Generation (MWh) Capacity (MW) Generation (MWh)

Biomass 43.7% 46.7% 49.8% 52.6%

Geothermal 47.2% 47.4% 49.8% 50.5%

PV 58.2% 63.3%

Wind 47.5% 45.7% 45.5% 43.6%

Impact of Policy on Efficiency

Commercial 67.5%

Residential 46.1%

Results

17

The regression models produced were able to explain 

between 44% and 63% of the variation between states in 

capacity and generation (depending on technology), and 

between 46% and 68% of energy use
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Results – Commercial Energy Use

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• Expected: a negative relationship between efficiency building codes, 

energy efficiency resource standards (EERS), commercial electricity 

price, and commercial energy consumption

• Unexpected: the existence of personal tax incentives is associated 

with increased commercial energy use

Impact of Policy on Commercial Efficiency: Commercial 

Consumption/GSP (2008 Incentives)

Variable Beta P-Value

Constant 2,029.5 0.000

High Efficiency Commerical Building Code -104.7 0.042

2008 Personal Tax Incentives 154.4 0.010

Average Commercial Electricity Price (2009) -48.8 0.000

Energy Efficiency Resource Standard (EERS) -193.8 0.000

Adjusted R2 0.675

Number of Observations 51
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State of the States 2010

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Purpose

Background

Methods

Results

Conclusions
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Conclusions

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• Does not explain variability in 

state clean energy growth

• Results are better when other 

variables (population, electricity 

price, number of years a policy is 

in place) are incorporated into the 

models

Policy 

Alone
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Conclusions

21

•Current set of policies is more 

targeted at influencing wind and 

solar development than 

development of biomass and 

geothermal

•State policies, while broadly 

applicable across renewable 

energy resources, may not be 

usable by developers of those 

resources because the policies do 

not meet the resource’s needs

Targeting
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Conclusions

22

•Policies are more connected with 

clean energy development the 

longer they are in place

•Policy longevity is an important 

aspect of effectiveness

Time
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Conclusions

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•Where significant relationships 

were found, mixes of policies 

explain growth best

•Creating an environment for 

investment in clean energy by 

implementing a suite of policies 

may be more effective than 

choosing a single or small number 

of mechanisms

Policy 

Mixes
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Conclusions and Next Steps

24

This research provides another piece in the understanding of how 

policy interacts with market development of clean energy

More experience with policies and further research are necessary 

to better understand these relationships

As policies are in place for longer periods of time, their impacts on 

clean energy development will become clearer, as it takes time to 

develop clean energy projects once the environment is established for 

their development
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Conclusions

25

Thank you for your time!

For more information: http://www.nrel.gov/cepa

Elizabeth Doris

National Renewable Energy Laboratory

(303) 384-7489

Elizabeth.Doris@nrel.gov