Energy efficiency – How far can we raise the bar? Revealing the potential of best available technologies
Introduction
Many countries have adopted energy efficiency standards and labeling programs for appliances, lighting, and commercial building equipment. Such regulatory programs aid in the development of more energy-efficient products and help mitigate potential energy security and climate change impacts. The design and execution of a balanced energy efficiency standards and labeling program requires careful consideration of many factors [1]. Standards levels are generally chosen to be cost effective for the consumer, in other words so that savings from operating a more efficient product outweigh the added cost of purchasing it. Many studies have documented and quantified the retrospective success of standards and/or labeling programs in saving consumers energy and money [2], [3], [4]. Although country-specific prospective studies have been attempted [5], [6], [7], [8], [9] few studies have consistently and systematically assessed the global potential that is technically achievable by means of standards [10], [11].
Although the savings achieved/identified in these studies are impressive, the results are difficult to place in the context of “what might have been.” That is, these studies do not compare actual savings to savings from the highest-efficiency scenario that is technically feasible (regardless of whether the highest-efficiency scenario is cost-effective). Some individual programs consider high-efficiency (or “maximum technology”) designs, but the definition of “maximum technology” is not consistent from program to program, resulting in an incomplete assessment. In some cases, true maximum technology designs are excluded from consideration in potential standards because of statutory or other constraints. The following analysis presents a complete understanding of the highest-efficiency scenario. The results of this analysis suggest the extent of energy savings that are not addressed by existing energy efficiency standards and labeling programs in the major energy-consuming economies; knowing the extent of these potential savings enables us to determine the true global technical energy efficiency potential.
As part of the ongoing effort to estimate the foreseeable impacts of aggressive standards and labeling programs in the world's major economies, Lawrence Berkeley National Laboratory (LBNL) has developed a modeling framework, the Bottom Up Energy Analysis System (BUENAS), to assess the technical potential of standards around the world [10]. In this analysis, we bring together the engineering knowledge of the technologies evaluated in studies such as Max Tech and Beyond [12] with BUENAS' capability to model international minimum efficiency performance standards (MEPS). The best available technology (BAT) scenario that we developed for this analysis seeks to determine the maximum potential savings through the use of best available technologies worldwide and thus to provide the most accurate estimate of maximum potential savings achievable by means of global standards.
The analysis uses BUENAS to estimate potential impacts and savings of the BAT scenario for a wide range of residential and industrial end uses. BUENAS has been used to support the activities of the Super-Efficient Appliance Deployment (SEAD), an initiative within the Clean Energy Ministerial process.1 Therefore, the countries included in BUENAS are SEAD participating countries, as well as China. BUENAS is designed to provide policy makers with estimates of potential international or regional impacts of efficiency market transformation for a variety of products. A recent study covering 13 major world economies found that 80 percent of the potential energy savings and 90 percent of potential emissions savings are in the United States (U.S.), European Union (EU), China, and India [13]. For this reason, this paper focuses on those major energy-consuming and carbon-emitting economies, which, in 2008, represented more than half of the world's primary energy consumption [14].
This paper is organized into the following sections: Section 2 describes the scope of the study, the BAT scenario, and the calculation methodology. Sections 3 Residential sector, 4 Industrial sector, 5 Calculation of potential savings describe the assumptions and data inputs for each end use for both the residential and industrial sectors, as well as the calculation methodology. Section 6 discusses the energy savings and carbon dioxide (CO2) emissions impacts of the BAT scenario for each country and each end use in 2020 and 2030. We also compare these results to a business-as-usual (BAU) scenario. Section 7 is dedicated to uncertainties of our results. Finally, Section 8 summarizes our findings and presents our conclusions.
Section snippets
Scenario description
In the BAT scenario, we identify targets representing the maximum achievable energy efficiency, based on both an engineering analysis and on single emerging technologies. We then simulate the effects of MEPS taking effect in 2015 at that level. MEPS provide a concrete policy scenario because they generally require that 100 percent of new sales meet the standard. However, we note that our results do not apply only to MEPS; any program that results in a market average efficiency at the BAT level
Lighting
Our analysis considers LEDs to be the BAT for residential lighting. Typical LEDs are designed to operate with low currents to provide efficient, low-level illumination. They are thus ideal for applications such as small flashlights and headlamps. White LEDs for general-purpose lighting are more problematic, however. LEDs typically suffer severe drops in efficiency at high currents and high temperatures. Powerful LEDs therefore require extensive heat sinks to provide optimum illumination. In
Motors
The MotorMaster database [39] was used to determine the best available motors sold in the U.S. for each representative capacity of the product classes analyzed in BUENAS. These efficiencies were assumed to be the international BAT. The most efficient motor is a brushless DC permanent-magnet motor with an efficient core design (e.g., laminated amorphous metal), low-resistance conductors, and low-friction bearings. DC motors also allow for easy adaptation to variable-speed applications, which can
Calculation of potential savings
BUENAS calculates national energy savings ΔE(y) in each year by comparing the national energy consumption E(y) of the end use under study in the BAU to the BAT case, as follows:BUENAS calculates final energy demand according to the UEC of equipment sold in previous years:where Sales (y) = unit sales (shipments) in year y; UEC(y) = unit energy consumption of units sold in year y; Surv(age) = probability of surviving to age years.
Calculated potential savings results
Table 5 presents the estimated energy savings in 2020 and 2030 by country and end use based on the calculation method and the assumptions described above.
A few noteworthy results:
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With the introduction of heat-pump and solar water heaters, water heaters show the largest savings of all end uses. This end use usually has a high baseline energy consumption because of the abundant usage of hot water in countries with temperate climates. Moreover, the improvement potential of high-efficiency water
Discussion of uncertainty
As with all models projecting into the future, our results are subject to various sources of uncertainty. In general, there are two categories of uncertainty for the BUENAS model: (a) errors in determination of data-driven parameters; and (b) uncertainties in forecast parameters because of the impossibility of predicting the future. Examples of data-driven parameters include historical shipments of products, historical efficiency distributions, and usage patterns. In principle, errors in these
Discussion and conclusions
This study shows that the implementation of MEPS targeting technically achievable best available efficiencies for a handful of end uses can reduce final energy consumption by 20 percent in 2030 in the residential and industrial sectors compared to BAU. As a result, worldwide annual CO2 emissions would be reduced by 0.7 Gt in 2020 and 1.5 Gt in 2030, or 6.5 percent and 13 percent, respectively, compared to our projected BAU CO2 emissions. As a comparison, recently implemented or in-progress
Acknowledgments
This work was supported by the Collaborative Labeling and Appliance Standards Program through the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. The authors would like to thank Won Park and Nihar Shah from LBNL for their precious guidance and Nan Wishner, our technical editor for this article.
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