Calendar Year 2009 Program Benefits for ENERGY STAR Labeled Products

Homan, Gregory; Sanchez, Marla; Brown, Richard E.

doi:10.2172/1007224

Cited by 1 publication

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“…Combined with stock accounting based on tracking of different vintages of products and a retirement function based on average product lifetime, the unit energy savings is used to calculate the annual energy savings of the ENERGY STAR program and associated financial and environmental benefits using the follow equations (Homan et al 2010  X n = number of ENERGY STAR units sold in year n due to the program  UES n = unit energy savings of ENERGY STAR units sold in year n (in kWh or MBtu)  L = product lifetime  AES t = aggregate annual energy savings in year t (in kWh or MBtu)  P t = energy price in year t (in $/kWh or $/MBTu)  C t = carbon emissions factor in year t (in kgC/kWh or kgC/MBtu) Table 19 shows the results of the ENERGY STAR evaluation methodology for estimating achieved savings for 2009. Similar results are produced for estimating potential savings for future years using projected parameters such as energy prices and marginal electricity carbon emission factors.…”

Section: Energy Star Program Savings Evaluationmentioning

confidence: 99%

International Review of Frameworks for Impact Evaluation of Appliance Standards, Labeling, and Incentives

Zhou¹

2012

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In recent years, the number of energy efficiency policies implemented has grown very rapidly as energy security and climate change have become top policy issues for many governments around the world. Within the sphere of energy efficiency policy, governments (federal and local), electric utilities, and other types of businesses and institutions are implementing a wide variety of programs to spread energy efficiency practices in industry, buildings, transport, and electricity. As programs proliferate, there is an administrative and business imperative to evaluate the savings and processes of these programs to ensure that program funds spent are indeed leading to a more energy-efficient economy. The field of energy efficiency program evaluation grew out of this imperative and has the following primary objectives: 1) to measure and verify the impacts of a specific energy efficiency program 2) to evaluate the processes of a specific energy efficiency program 3) to inform program managers' and policymakers' decision making in both assessing market potential and improving program design Within these three objectives, there is an emphasis on both measuring the impacts of a program as well as analyzing the processes by which a program works. Because evaluation is becoming increasingly important, it is becoming a standard practice in certain regions to set aside a portion of a program's budget (for example, 2-4%) for evaluation, even before the project has begun. The categories and types of evaluations are summarized in Table 1. The most common types of evaluation are potential, process, and impact evaluations, although, recently, market assessment and market effects evaluation are being conducted more widely.  Potential or feasibility evaluation-also known as ex-ante evaluation-is implemented during a program planning phase to predict the program impacts.  Process evaluation is performed during program implementation to see, for example, if program participants are interacting with the program and receiving programs benefits as planned.  Finally, impact evaluation-also known as ex-post evaluation-is used to determine what energy savings and environmental impacts a program produced. This paper will focus on both 1. Frozen baseline: the efficiency of new products remains constant in the base case 2. Improvement baseline: where historic unit energy consumption (UEC) data exist, the efficiency of new products improves at a similar rate of historic autonomous efficiency improvement, which declines into the future 3. Market share baseline: where data on market share for models of different efficiencies exist, a baseline efficiency can be estimated for future years 4. Bass model baseline: the most advanced curve fitting of market adoption of energy-efficient products to predict NOMAD An example of an improvement baseline from a recent evaluation done in Australia on standards and labeling programs for refrigerators is shown in Figure 3.

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Section: Energy Star Program Savings Evaluationmentioning

confidence: 99%

International Review of Frameworks for Impact Evaluation of Appliance Standards, Labeling, and Incentives

Zhou¹

2012

View full text Add to dashboard Cite

show abstract

Calendar Year 2009 Program Benefits for ENERGY STAR Labeled Products

Cited by 1 publication

References 16 publications

International Review of Frameworks for Impact Evaluation of Appliance Standards, Labeling, and Incentives

International Review of Frameworks for Impact Evaluation of Appliance Standards, Labeling, and Incentives

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