Clean Energy and
Multiple Benefits of Clean
Energy Initiatives
Reducing energy demand and/
or increasing renewable energy
generation from state and local clean
energy initiatives—such as goals,
standards, codes, funds and programs-
generate many benefits including:
• Security, diversity, and overall reliability
improvements for the electric system.
• Improved environmental quality, human
health, and quality of life.
• Positive economic gains through energy
costs saved, avoided medical costs,
higher disposable incomes, increased
labor productivity, and more jobs
This brochure is part of a series and focuses
on direct energy impacts.
State and local governments
can analyze their clean
energy initiatives using
methods and tools described
in this brochure.
What's Inside:
O How can state and local governments
estimate the potential direct energy
impacts of clean energy policies?
O Steps to estimating energy impacts of
clean energy.
O Retrospective vs. prospective calculation of
energy savings.
O Quantitative examples of how clean energy
programs result in direct energy benefits.
O How to find more information.
&EPA
United States
Environmental Protection
Agency
of State and Local
Clean Energy Initiatives
What are the direct energy impacts of
clean energy initiatives?
Clean energy initiatives, including those that advance energy efficiency,
renewable energy and clean distributed generation, directly impact energy
by:
Reducing demand for conventional fossil-fuel-powered electricity,
Reducing demand for natural gas used for heating, and/or
Increasing the amount of electricity generated with clean, renewable energy
sources.
How do direct energy impacts from
clean energy benefit states and
localities?
Reducing fossil fuel-based electricity—and generating more electricity from
clean, renewable energy—benefits several state and local priority areas.
Environment:
- Clean energy initiatives reduce or avoid air pollution and greenhouse gas
emissions, improving air quality, protecting peoples health, and lowering
contributions to climate change.
Economy:
Energy efficiency can lower the cost of complying with national air
standards by reducing air pollution.
Clean energy initiatives can reduce costs for fuel, energy, and new
electric power plant construction, and improved air quality helps avoid
illnesses which reduces medical costs.
- Clean energy can also increase personal disposable income and revenues
for business, increase labor productivity and support jobs in the clean
technology sector as well as in the businesses that support it.
Electric System:
Energy efficiency can reduce the need for additional generation and
transmission assets.
Clean energy from domestic sources can increase energy security,
diversity, and overall reliability in the electricity grid.
Diversified utility resource portfolios that include energy efficiency and
renewable energy can reduce uncertainty associated with fluctuating fuel
prices and reduce dependence on imported fuels and other risk factors.
Slate and Local
Climate and Energy Program
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Retrospective vs. Prospective
Calculation of Energy Savings
State and local governments can assess energy
impacts from two perspectives: retrospectively,
to evaluate impacts of existing investments,
or prospectively, to plan new or modified
initiatives.
• Retrospective approaches are based on
measurements of actual impacts that
have already accrued from past clean
energy actions. Actual energy savings
from energy-efficiency programs, for
example, are calculated using measurement
and verification (M&V) methods, where
measurements determine actual savings
from measures implemented in an individual
facility.
• Prospective techniques for estimating
energy savings or renewable-energy
generation include methods and models
that calculate expected energy impacts
resulting from proposed clean energy
initiatives. Prospective analyses of energy
impacts are appropriate, for example, when
a state or locality is assessing the relative
costs and benefits of alternative policies to
select the most cost-effective approach or
determining the budget level required to
meet clean energy goals.
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The Texas Emissions Reduction Plan (TERP)
promotes energy-efficiency and renewable-
energy measures to meet federal ambient air
quality standards. Estimated cumulative annual
energy savings from code-compliant residential
and commercial construction in Texas were:
• 1,440,885 MWh of electricity each
year from 2001-2007.
• Approximately 2.9 million MWh by
2013, accounting for 10 percent of the
cumulative total electricity savings under
all energy efficiency and renewable energy
programs implemented under the TERP
(2008 and 2013).
Estimated reduction of NOX emissions:
« 1,014 tons /year in 2007.
« 2,047 tons/year by 2013.
Analysis of data from the Texas Commission
on Environmental Quality and EPA (including
eGRID) provided an estimate of the energy
savings and NOX reductions from energy code
compliance in new residential construction.
Source: Texas A&M Energy Systems Laboratory (ESL).
2008.
Why estimate the direct energy
impacts of clean energy initiatives?
Direct energy impact estimates are the foundation for calculating and
communicating the potential cost savings and other benefits to the economy,
energy system, environment, and human health.
By understanding the direct energy impacts of clean energy initiatives, policy
makers can:
1. Evaluate the implications of new goals, targets, or legislative actions.
2. Measure progress toward meeting clean energy- and other related goals.
3. Review the actual and potential effectiveness of technology- or sector-
specific clean energy initiatives in achieving energy savings.
4. Estimate the actual and potential co-benefits of clean energy policies,
including benefits to the energy system, economy, environment, and
human health.
5. Communicate clearly the comprehensive impacts of existing and potential
clean energy initiatives to their partners and stakeholders.
6. Demonstrate the full value of a clean energy program.
How can state and local governments
estimate the potential direct energy
impacts of clean energy policies?
There are a series of steps state and local governments can take to
estimate the direct energy impacts of clean energy:
STEP 1: Develop a business-as-usual (BAU) energy forecast
State and local governments can compile, adopt, or develop the historical,
current and projected pattern of energy supply and demand using basic or
sophisticated approaches. This creates a baseline against which to measure
the energy impacts of policies.
Sources of data include: Utilities; consumer energy profiles; state energy
offices; public utility commissions; independent system operators, North
American Electric Reliability Corporation; US DOE's Energy Information
Administration; National Renewable Energy Laboratory; and US EPA.
STEP 2: Quantify implications of targets and goals
Targets and goals are often presented in percentages that don't necessarily
specify the quantities of energy reductions or generation desired, such as:
• Achieve a rate of zero load growth by 2020.
Reduce electricity demand by 2 percent per year by 2015, and 2 percent
every year thereafter, with reductions to be based on prior three years of
actual sales.
Meet 20 percent of generation requirements or sales through renewable
energy sources by some date in the future.
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It can be helpful to estimate the potential implications of a target or goal and
determine how much energy must be saved or generated before evaluating
specific clean energy programs and implementation options.
STEP 3: Estimate potential direct energy impacts
There are a range of basic to sophisticated approaches available for estimating
the potential direct energy impacts of clean energy, including:
Extrapolation of energy efficiency or renewable energy potential studies,
Adapting the results of similar programs in other states or localities to local
conditions, and
Understanding the amount of clean energy equipment in the market to
determine the feasible amount of investment a new initiative could induce.
Resources available to facilitate estimation include: Market Assessment and
Program Evaluation (MAPE) Clearinghouse, Lawrence Berkeley National
Laboratory (LBL), Renewable Energy Policy Project (REPA), American Council
on Energy Efficient Economy (ACEEE), Tellus Institute, National Renewable
Energy Laboratory (NREL), California Database of Energy Efficiency Resources
(DEER), Regional Technical Forum (RTF) deemed savings database, and
Entergy Texas Deemed Savings.
Tools available include: ENERGY STAR* Savings Calculators, ENERGY
STAR Roofing Comparison Calculator, ENERGY STAR Target Finder, and
ENERGY STAR Portfolio Manager.
Key assumptions to consider include: Program period, program target,
anticipated compliance or penetration rate, annual degradation factor of the
measure, transmission & distribution loss, non-program effects, funding, and
administration.
New York's Energy SmartSM Public Benefits
Program was implemented in 1998 to
improve the state's energy reliability, reduce
energy costs, mitigate environmental and
public health effects related to energy use,
and enhance the state economy. Between
1998 and 2007, the overall program had:
« Achieved more than 3,000 GWh of
electricity savings;
• Created and retained 4,700 jobs;
• Reduced nearly 2,600 and 4,700
tons of NOx and SOx, respectively;
• Decreased annual CO2 emissions
by 2 million tons; and
• Reduced annual energy bills
by $570 million for participating
customers.
By 2027, the program is expected to:
• Create more than 7,200 jobs.
• Increase labor income more than
$300 million each year.
« Increase total annual output in the
state by $503 million
Each year, the New York State Energy
Research and Development Authority
(NYSERDA) collects data on progress toward
meeting the program's energy savings goals.
Source: New York State Energy Research and
Development Authority. 2008.
STEP 4: Create an alternative policy forecast
Once the direct energy impacts are estimated, an alternative policy forecast is
created to reflect the new energy supply or demand conditions expected after
the implementation of a new clean energy initiative. All BAU forecasts and
energy savings projections should be reevaluated periodically (every one to
two years) and it is important to document all sources and assumptions.
For more information about these steps, please see the next page.
References:
• New York Energy SMARTSMProgram Evaluation and Status Report for the Year Ending December
2007 New York Public Service Commission and New York State Energy Research and Development
Authority. March. 2008.
Vermont's Department of Public Service
(DPS) forecasts energy demand and energy
efficiency program savings as part of its
state energy policy and planning process.
The 2008 forecast showed growing energy
demand and a potentially large supply gap
if major power contracts were not replaced.
As a result, Vermont committed to pursuing
aggressive energy efficiency measures.
The forecast projected that without new
DSM measures, electricity demand would
grow an average of 0.93 percent on an
average annual basis until 2028.
When new DSM measures are implemented,
the DPS anticipates that energy demand will
Texas Engineering Experiment Station. Texas A&M University System. Volume I—Summary Report:
Annual Report to the Texas Commission on Environmental Quality. January 2007-December 2007.
August 2008. Revised December 2008. Energy Systems Laboratory.
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Where can state and local governments and policy makers
go for more information about tools, methods, and resources
available to estimate the benefits of clean energy initiatives?
Assessing the Multiple Benefits of Clean Energy: A Resource for States, an essential manual to help estimate and
communicate the benefits of clean energy, provides tools and approaches for state and local governments.
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