This collaborative study explored ways for energy efficiency programs to achieve greater savings in the industrial sector. The study examined programs in Canada, South Africa, and the United States. It looked at case studies of facilities that implemented energy management systems and took measures to reduce the energy consumption of their motor-driven systems. The study provides insights on optimizing energy efficiency programs to get the most out of energy management systems and unlock energy savings from motor-related measures. Systems driven by electric motors are responsible for about 70 percent of the electricity consumed in this sector worldwide. Energy management systems, such as ISO 50001, enable facility managers to discover and implement energy-saving measures.

The study was conducted by Advanced Energy under the direction of CLASP and in collaboration with the U.S. Department of Energy, Natural Resources Canada, Berkeley Lab, and the Electric Motor Systems Annex (EMSA) to the IEA Technology Collaboration Programme on Energy Efficient End-Use Equipment (4E).

Comparing energy performance requirements for appliances from country to country is difficult because of variations in product definitions, misaligned energy test procedures, and divergent efficiency metrics. This complex landscape can prevent policymakers from identifying or adopting global best practices in appliance energy efficiency policy.

To address this challenge, CLASP and the Policy Partners, along with many other technical product experts, collected data to compare appliance energy efficiency policies, test methods, and efficiency metrics for more than 100 products across nine economies—Australia, China, the European Union, India, Indonesia, Mexico, Russia, South Africa, and the United States.

The resulting analysis represents the largest and most comprehensive comparison of energy standards and labels ever compiled. It describes which product policies are comparable across economies; which are not; and which could be. It is intended to provide policymakers and experts with useful tools for analyzing country data at a macro-level and to enable more informed decisions about the most appropriate policies.

The results are presented in several components:

• The Policymakers’ Summary provides an overview of the analysis.
• The webinar provides additional insights from the report authors.
• The full report, Improving Global Comparability of Appliance Energy Efficiency Standards and Labels, contains the background, methodology, and high-level product specific information.
• Annex 1: Overview Table (Microsoft Excel file) contains quantitative information for all products.
• Annex 2: Product Fact Sheets contains additional product-by-product detail.

Many economies around the world are beginning to regulate commercial refrigeration equipment (CRE). CRE products include vending machines, reach-in coolers, among other products.  Due to the limited availability of data for many products in the CRE product category, economies often face challenges when trying to implement S&L policies.

CLASP’s product and policy mapping and benchmarking studies inform policymakers about opportunities and pathways to raise the ambition of national policies in order to maximize energy savings and CO2 emissions reductions.  The data collected and benchmarks determined by this study can provide economies with better information and ambitious targets when setting or revising product policies.

Following the completion of the CRE scoping study in 2012, CLASP conducted a benchmarking analysis for CRE in collaboration with the SEAD Initiative and Waide Strategic Efficiency, Saint Trofee and Cemafroid. Based on recommendations from the scoping study, this benchmarking study focuses on products that are most commonly used and regulated, such as commercial reach-in coolers (including refrigerated display cabinets and beverage coolers) and refrigerated vending machines.

This analysis focuses on nine economies – including Australia, Brazil, China, Europe, India, Japan, Mexico, South Africa and the US – that demonstrate high energy savings potential through adopting more proactive policy measures for CRE.  By including more economies in the study, the study provides additional country-specific data and complements International Energy Agency Efficient Electrical End-Use Equipment (IEA 4E)’s existing mapping and benchmarking reports for vending machines and retail display cabinets.

In order to facilitate the comparability of efficiency policies across these economies, this study:

• Identifies the national test procedures applied in the target economies and their equivalence to international or national test procedures;
• Compares the differences in the testing procedures to assess the expected impact on rated energy performance;
• Develops energy performance benchmarks; and
• Assesses higher energy efficiency design options and potential efficiency improvement cost-benefits.

Based on the analysis, both reach-in coolers and vending machines demonstrate great potential for significant energy savings by implementing or improving energy efficiency standards and labelling policies in the nine targeted economies.

• Reach-in coolers: if all new products sold from 2014 onwards use the maximum technically achievable efficiency today, the energy savings would be of 56 TWh in 2035 – equivalent to removing the emissions of 11 coal-fired power plants for a year.
• Vending machines: If all new vending machines sold from 2014 onwards were to be at the maximum technically achievable efficiency today, the energy savings would be of 18.5 TWh by 2035 – equivalent to removing the emissions of 3.7 coal-fired power plants for a year.

CLASP completed a cooling study in 2011, the first in a series intended to provide an international comparison of energy efficiency performance and policy measures for various appliances. The objectives of these studies are to lay the foundation for strong and comparable energy performance requirements at the global level and to pull the market towards higher levels of efficiency.

In order to maximize efficiency in its studies, CLASP has conducted a scoping study in partnership with Klinckenberg Consultants and Puddle Consultancy to define the work that will be needed for the benchmarking of commercial refrigeration equipment – these include beverage vending machines, walk-in coolers, and reach-in coolers. The study covers the following countries and economies: Australia, Canada, Denmark, European Union, Italy, Japan, Korea, New Zealand, South Africa, United Kingdom, and the USA (Federal, California, Washington State).

Mapping and Benchmarking projects can be challenging, and it is often not easy to find an approach that results in information that is directly beneficial to policy makers and program managers in a variety of countries, all at a different stage of development of their S&L policies. Most mapping and benchmarking projects have also experienced challenges due to incomparability of products in different parts of the world, different approaches to testing and lack of or unavailability of critical data.

This report describes the findings of the scoping study. It includes a summary report, which provides an overview of product definitions, main test procedures and comparability issues for the commercial refrigeration products covered, as well as an overview of the needs identified by S&L program managers in various countries. The report further includes three sections providing detailed information on Reach-in coolers (Section A), Cold vending machines (Section B), and Walk-in cold rooms (Section C).

The Bottom-Up Energy Analysis System (BUENAS) is a policy analysis tool created by Lawrence Berkeley National Laboratory (LBNL) and supported by CLASP, the Super-efficient Equipment and Appliance Deployment (SEAD) initiative, and the International Copper Association.

BUENAS, which covers 13 major economies contributing to 77% of global energy demand, is designed to provide estimates of potential CO2 and energy savings impacts for a wide range of residential, commercial, and industrial end uses. BUENAS also enables consistent comparison of impacts of the energy efficiency standards and labeling (S&L) policies across major economies.

The characteristics that, taken together, distinguish BUENAS from other modeling tools are that BUENAS:

• Covers multiple economies around the world;
• Models energy end use demand from the bottom-up according to engineering and use patterns; and
• Projects energy and CO2 savings based on specific efficiency targets judged to be achievable through near- to mid-term S&L policy implementation.

The 12 economies that are covered in this document are Australia, Brazil, Canada, the European Union, India, Indonesia, Japan, Korea, Mexico, Russia, South Africa, and the United States.

Part I

Part I of this report provides policymakers and S&L practitioners with a high-level overview of the BUENAS modeling framework, defines the scope of BUENAS, and describes potential uses of the model. For example, BUENAS has been used as an S&L policy planning and prioritization tool for developing countries as well as international initiatives such as the Association of South East Asian Nations (ASEAN) and the SEAD Initiative.

Part I also describes results from two policy scenarios – recent achievements (RA) and best practice (BP):

• The RA scenario quantifies the effectiveness of recently implemented, announced, and in progress minimum energy performance standards (MEPS) between January 1, 2000 and April 1, 2011.
• The BP scenario estimates the potential impacts of an economy adopting the most stringent standards to date (as of April 2011) by 2015.

Based on the S&L policies achieved to date in the 12 economies covered in this analysis (all of the above except China), BUENAS estimates global savings of:

• 389 terawatt hours (TWh) of electricity annually in 2030; and
• 219 million tons (Mt) of CO2 emissions annually in 2030.

Part II

Part II of this report provides a detailed description of the BUENAS methodology and data sources. It is intended for a technical audience and assumes some familiarity with the parameters used in energy demand and policy modeling.

The information in Part II includes:

• Definitions and main outputs of the model, in equation form;
• Key data inputs;
• Mechanics of key modeling variables by product group; and
• Detailed description of RA and BP scenarios.

Authors: Michael A. McNeil, Virginie E. Letschert, Stephane de la Rue du Can and Jing Ke; LBNL